Hardware content-associative data structure for acceleration of set operations

FIELD OF THE INVENTION

The present disclosure pertains to the field of processing logic, microprocessors, and associated instruction set architecture that, when executed by the processor or other processing logic, perform logical, mathematical, or other functional operations.

DESCRIPTION OF RELATED ART

Multiprocessor systems are becoming more and more common. Applications of multiprocessor systems include dynamic domain partitioning all the way down to desktop computing. In order to take advantage of multiprocessor systems, code to be executed may be separated into multiple threads for execution by various processing entities. Each thread may be executed in parallel with one another. Instructions as they are received on a processor may be decoded into terms or instruction words that are native, or more native, for execution on the processor. Processors may be implemented in a system on chip. Graph processing is a backbone of big data analytics applications. Some graph processing frameworks are based on set operations, including set union operations and set intersection operations.

DESCRIPTION OF THE FIGURES

Embodiments are illustrated by way of example and not limitation in the Figures of the accompanying drawings:

FIG. 1B illustrates a data processing system, in accordance with embodiments of the present disclosure;

FIG. 1C illustrates other embodiments of a data processing system for performing text string comparison operations;

FIG. 2 is a block diagram of the micro-architecture for a processor that may include logic circuits to perform instructions, in accordance with embodiments of the present disclosure;

FIG. 3A illustrates various packed data type representations in multimedia registers, in accordance with embodiments of the present disclosure;

FIG. 3B illustrates possible in-register data storage formats, in accordance with embodiments of the present disclosure;

FIG. 3C illustrates various signed and unsigned packed data type representations in multimedia registers, in accordance with embodiments of the present disclosure;

FIG. 3D illustrates an embodiment of an operation encoding format;

FIG. 3E illustrates another possible operation encoding format having forty or more bits, in accordance with embodiments of the present disclosure;

FIG. 3F illustrates yet another possible operation encoding format, in accordance with embodiments of the present disclosure;

FIG. 4A is a block diagram illustrating an in-order pipeline and a register renaming stage, out-of-order issue/execution pipeline, in accordance with embodiments of the present disclosure;

FIG. 4B is a block diagram illustrating an in-order architecture core and a register renaming logic, out-of-order issue/execution logic to be included in a processor, in accordance with embodiments of the present disclosure;

FIG. 5A is a block diagram of a processor, in accordance with embodiments of the present disclosure;

FIG. 5B is a block diagram of an example implementation of a core, in accordance with embodiments of the present disclosure;

FIG. 6 is a block diagram of a system, in accordance with embodiments of the present disclosure;

FIG. 7 is a block diagram of a second system, in accordance with embodiments of the present disclosure;

FIG. 8 is a block diagram of a third system in accordance with embodiments of the present disclosure;

FIG. 9 is a block diagram of a system-on-a-chip, in accordance with embodiments of the present disclosure;

FIG. 10 illustrates a processor containing a central processing unit and a graphics processing unit which may perform at least one instruction, in accordance with embodiments of the present disclosure;

FIG. 11 is a block diagram illustrating the development of IP cores, in accordance with embodiments of the present disclosure;

FIG. 12 illustrates how an instruction of a first type may be emulated by a processor of a different type, in accordance with embodiments of the present disclosure;

FIG. 14 is a block diagram of an instruction set architecture of a processor, in accordance with embodiments of the present disclosure;

FIG. 15 is a more detailed block diagram of an instruction set architecture of a processor, in accordance with embodiments of the present disclosure;

FIG. 16 is a block diagram of an execution pipeline for an instruction set architecture of a processor, in accordance with embodiments of the present disclosure;

FIG. 17 is a block diagram of an electronic device for utilizing a processor, in accordance with embodiments of the present disclosure;

FIG. 18 is an illustration of an example system to accelerate the execution of set operations, in accordance with embodiments of the present disclosure;

FIG. 19 is an illustration of another example system to accelerate the execution of set operations, in accordance with embodiments of the present disclosure;

FIG. 20 is a block diagram illustrating a set operations logic unit, in accordance with embodiments of the present disclosure;

FIG. 21 is an illustration of an operation to add a set of key-value pairs to a hardware content-associative data structure, in accordance with embodiments of the present disclosure;

FIG. 22 is an illustration of a method for adding a set of key-value pairs to the contents of a hardware content-associative data structure (CAM), in accordance with embodiments of the present disclosure;

FIG. 24 is an illustration of a method for determining whether any of the keys in an input set of key-value pairs match keys in the key-value pairs currently stored in a hardware content-associative data structure (CAM), in accordance with embodiments of the present disclosure;

FIG. 25 is an illustration of an operation to determine the current length of a hardware content-associative data structure (CAM), in accordance with embodiments of the present disclosure;

FIG. 26 is an illustration of a method for determining the current length of a hardware content-associative data structure (CAM), in accordance with embodiments of the present disclosure;

FIG. 27 is an illustration of an operation to reset the contents of a hardware content-associative data structure (CAM), in accordance with embodiments of the present disclosure;

FIG. 28 is an illustration of a method for resetting the contents of a hardware content-associative data structure (CAM), in accordance with embodiments of the present disclosure;

FIG. 29 is an illustration of an operation to move the contents of a hardware content-associative data structure (CAM) to memory, in accordance with embodiments of the present disclosure;

FIG. 30 is an illustration of a method for moving the contents of a hardware content-associative data structure (CAM) to memory, in accordance with embodiments of the present disclosure;

FIG. 31 is an illustration of a method for selectively executing a set operation using a hardware content-associative data structure (CAM), in accordance with embodiments of the present disclosure.

DETAILED DESCRIPTION

The following description describes instructions and processing logic to accelerate the execution of set operations on a processing apparatus. Such a processing apparatus may include an out-of-order processor. In the following description, numerous specific details such as processing logic, processor types, micro-architectural conditions, events, enablement mechanisms, and the like are set forth in order to provide a more thorough understanding of embodiments of the present disclosure. It will be appreciated, however, by one skilled in the art that the embodiments may be practiced without such specific details. Additionally, some well-known structures, circuits, and the like have not been shown in detail to avoid unnecessarily obscuring embodiments of the present disclosure.

Although the following embodiments are described with reference to a processor, other embodiments are applicable to other types of integrated circuits and logic devices. Similar techniques and teachings of embodiments of the present disclosure may be applied to other types of circuits or semiconductor devices that may benefit from higher pipeline throughput and improved performance. The teachings of embodiments of the present disclosure are applicable to any processor or machine that performs data manipulations. However, the embodiments are not limited to processors or machines that perform 512-bit, 256-bit, 128-bit, 64-bit, 32-bit, or 16-bit data operations and may be applied to any processor and machine in which manipulation or management of data may be performed. In addition, the following description provides examples, and the accompanying drawings show various examples for the purposes of illustration. However, these examples should not be construed in a limiting sense as they are merely intended to provide examples of embodiments of the present disclosure rather than to provide an exhaustive list of all possible implementations of embodiments of the present disclosure.

Although the below examples describe instruction handling and distribution in the context of execution units and logic circuits, other embodiments of the present disclosure may be accomplished by way of a data or instructions stored on a machine-readable, tangible medium, which when performed by a machine cause the machine to perform functions consistent with at least one embodiment of the disclosure. In one embodiment, functions associated with embodiments of the present disclosure are embodied in machine-executable instructions. The instructions may be used to cause a general-purpose or special-purpose processor that may be programmed with the instructions to perform the steps of the present disclosure. Embodiments of the present disclosure may be provided as a computer program product or software which may include a machine or computer-readable medium having stored thereon instructions which may be used to program a computer (or other electronic devices) to perform one or more operations according to embodiments of the present disclosure. Furthermore, steps of embodiments of the present disclosure might be performed by specific hardware components that contain fixed-function logic for performing the steps, or by any combination of programmed computer components and fixed-function hardware components.

Instructions used to program logic to perform embodiments of the present disclosure may be stored within a memory in the system, such as DRAM, cache, flash memory, or other storage. Furthermore, the instructions may be distributed via a network or by way of other computer-readable media. Thus a machine-readable medium may include any mechanism for storing or transmitting information in a form readable by a machine (e.g., a computer), but is not limited to, floppy diskettes, optical disks, Compact Disc, Read-Only Memory (CD-ROMs), and magneto-optical disks, Read-Only Memory (ROMs), Random Access Memory (RAM), Erasable Programmable Read-Only Memory (EPROM), Electrically Erasable Programmable Read-Only Memory (EEPROM), magnetic or optical cards, flash memory, or a tangible, machine-readable storage used in the transmission of information over the Internet via electrical, optical, acoustical or other forms of propagated signals (e.g., carrier waves, infrared signals, digital signals, etc.). Accordingly, the computer-readable medium may include any type of tangible machine-readable medium suitable for storing or transmitting electronic instructions or information in a form readable by a machine (e.g., a computer).

A design may go through various stages, from creation to simulation to fabrication. Data representing a design may represent the design in a number of manners. First, as may be useful in simulations, the hardware may be represented using a hardware description language or another functional description language. Additionally, a circuit level model with logic and/or transistor gates may be produced at some stages of the design process. Furthermore, designs, at some stage, may reach a level of data representing the physical placement of various devices in the hardware model. In cases wherein some semiconductor fabrication techniques are used, the data representing the hardware model may be the data specifying the presence or absence of various features on different mask layers for masks used to produce the integrated circuit. In any representation of the design, the data may be stored in any form of a machine-readable medium. A memory or a magnetic or optical storage such as a disc may be the machine-readable medium to store information transmitted via optical or electrical wave modulated or otherwise generated to transmit such information. When an electrical carrier wave indicating or carrying the code or design is transmitted, to the extent that copying, buffering, or retransmission of the electrical signal is performed, a new copy may be made. Thus, a communication provider or a network provider may store on a tangible, machine-readable medium, at least temporarily, an article, such as information encoded into a carrier wave, embodying techniques of embodiments of the present disclosure.

In modern processors, a number of different execution units may be used to process and execute a variety of code and instructions. Some instructions may be quicker to complete while others may take a number of clock cycles to complete. The faster the throughput of instructions, the better the overall performance of the processor. Thus it would be advantageous to have as many instructions execute as fast as possible. However, there may be certain instructions that have greater complexity and require more in terms of execution time and processor resources, such as floating point instructions, load/store operations, data moves, etc.

As more computer systems are used in internet, text, and multimedia applications, additional processor support has been introduced over time. In one embodiment, an instruction set may be associated with one or more computer architectures, including data types, instructions, register architecture, addressing modes, memory architecture, interrupt and exception handling, and external input and output (I/O).

In one embodiment, the instruction set architecture (ISA) may be implemented by one or more micro-architectures, which may include processor logic and circuits used to implement one or more instruction sets. Accordingly, processors with different micro-architectures may share at least a portion of a common instruction set. For example, Intel® Pentium 4 processors, Intel® Core™ processors, and processors from Advanced Micro Devices, Inc. of Sunnyvale Calif. implement nearly identical versions of the x86 instruction set (with some extensions that have been added with newer versions), but have different internal designs. Similarly, processors designed by other processor development companies, such as ARM Holdings, Ltd., MIPS, or their licensees or adopters, may share at least a portion of a common instruction set, but may include different processor designs. For example, the same register architecture of the ISA may be implemented in different ways in different micro-architectures using new or well-known techniques, including dedicated physical registers, one or more dynamically allocated physical registers using a register renaming mechanism (e.g., the use of a Register Alias Table (RAT), a Reorder Buffer (ROB) and a retirement register file. In one embodiment, registers may include one or more registers, register architectures, register files, or other register sets that may or may not be addressable by a software programmer.

An instruction may include one or more instruction formats. In one embodiment, an instruction format may indicate various fields (number of bits, location of bits, etc.) to specify, among other things, the operation to be performed and the operands on which that operation will be performed. In a further embodiment, some instruction formats may be further defined by instruction templates (or sub-formats). For example, the instruction templates of a given instruction format may be defined to have different subsets of the instruction format's fields and/or defined to have a given field interpreted differently. In one embodiment, an instruction may be expressed using an instruction format (and, if defined, in a given one of the instruction templates of that instruction format) and specifies or indicates the operation and the operands upon which the operation will operate.

Scientific, financial, auto-vectorized general purpose, RMS (recognition, mining, and synthesis), and visual and multimedia applications (e.g., 2D/3D graphics, image processing, video compression/decompression, voice recognition algorithms and audio manipulation) may require the same operation to be performed on a large number of data items. In one embodiment, Single Instruction Multiple Data (SIMD) refers to a type of instruction that causes a processor to perform an operation on multiple data elements. SIMD technology may be used in processors that may logically divide the bits in a register into a number of fixed-sized or variable-sized data elements, each of which represents a separate value. For example, in one embodiment, the bits in a 64-bit register may be organized as a source operand containing four separate 16-bit data elements, each of which represents a separate 16-bit value. This type of data may be referred to as ‘packed’ data type or ‘vector’ data type, and operands of this data type may be referred to as packed data operands or vector operands. In one embodiment, a packed data item or vector may be a sequence of packed data elements stored within a single register, and a packed data operand or a vector operand may a source or destination operand of a SIMD instruction (or ‘packed data instruction’ or a ‘vector instruction’). In one embodiment, a SIMD instruction specifies a single vector operation to be performed on two source vector operands to generate a destination vector operand (also referred to as a result vector operand) of the same or different size, with the same or different number of data elements, and in the same or different data element order.

SIMD technology, such as that employed by the Intel® Core™ processors having an instruction set including x86, MMX™, Streaming SIMD Extensions (SSE), SSE2, SSE3, SSE4.1, and SSE4.2 instructions, ARM processors, such as the ARM Cortex® family of processors having an instruction set including the Vector Floating Point (VFP) and/or NEON instructions, and MIPS processors, such as the Loongson family of processors developed by the Institute of Computing Technology (ICT) of the Chinese Academy of Sciences, has enabled a significant improvement in application performance (Core™ and MMX™ are registered trademarks or trademarks of Intel Corporation of Santa Clara, Calif.).

In one embodiment, destination and source registers/data may be generic terms to represent the source and destination of the corresponding data or operation. In some embodiments, they may be implemented by registers, memory, or other storage areas having other names or functions than those depicted. For example, in one embodiment, “DEST1” may be a temporary storage register or other storage area, whereas “SRC1” and “SRC2” may be a first and second source storage register or other storage area, and so forth. In other embodiments, two or more of the SRC and DEST storage areas may correspond to different data storage elements within the same storage area (e.g., a SIMD register). In one embodiment, one of the source registers may also act as a destination register by, for example, writing back the result of an operation performed on the first and second source data to one of the two source registers serving as a destination registers.

FIG. 1A is a block diagram of an exemplary computer system formed with a processor that may include execution units to execute an instruction, in accordance with embodiments of the present disclosure. System 100 may include a component, such as a processor 102 to employ execution units including logic to perform algorithms for process data, in accordance with the present disclosure, such as in the embodiment described herein. System 100 may be representative of processing systems based on the PENTIUM® III, PENTIUM® 4, Xeon™, Itanium®, XScale™ and/or StrongARM™ microprocessors available from Intel Corporation of Santa Clara, Calif., although other systems (including PCs having other microprocessors, engineering workstations, set-top boxes and the like) may also be used. In one embodiment, sample system 100 may execute a version of the WINDOWS™ operating system available from Microsoft Corporation of Redmond, Wash., although other operating systems (UNIX and Linux for example), embedded software, and/or graphical user interfaces, may also be used. Thus, embodiments of the present disclosure are not limited to any specific combination of hardware circuitry and software.

Embodiments are not limited to computer systems. Embodiments of the present disclosure may be used in other devices such as handheld devices and embedded applications. Some examples of handheld devices include cellular phones, Internet Protocol devices, digital cameras, personal digital assistants (PDAs), and handheld PCs. Embedded applications may include a micro controller, a digital signal processor (DSP), system on a chip, network computers (NetPC), set-top boxes, network hubs, wide area network (WAN) switches, or any other system that may perform one or more instructions in accordance with at least one embodiment.

Computer system 100 may include a processor 102 that may include one or more execution units 108 to perform an algorithm to perform at least one instruction in accordance with one embodiment of the present disclosure. One embodiment may be described in the context of a single processor desktop or server system, but other embodiments may be included in a multiprocessor system. System 100 may be an example of a ‘hub’ system architecture. System 100 may include a processor 102 for processing data signals. Processor 102 may include a complex instruction set computer (CISC) microprocessor, a reduced instruction set computing (RISC) microprocessor, a very long instruction word (VLIW) microprocessor, a processor implementing a combination of instruction sets, or any other processor device, such as a digital signal processor, for example. In one embodiment, processor 102 may be coupled to a processor bus 110 that may transmit data signals between processor 102 and other components in system 100. The elements of system 100 may perform conventional functions that are well known to those familiar with the art.

In one embodiment, processor 102 may include a Level 1 (L1) internal cache memory 104. Depending on the architecture, the processor 102 may have a single internal cache or multiple levels of internal cache. In another embodiment, the cache memory may reside external to processor 102. Other embodiments may also include a combination of both internal and external caches depending on the particular implementation and needs. Register file 106 may store different types of data in various registers including integer registers, floating point registers, status registers, and instruction pointer register.

Execution unit 108, including logic to perform integer and floating point operations, also resides in processor 102. Processor 102 may also include a microcode (ucode) ROM that stores microcode for certain macroinstructions. In one embodiment, execution unit 108 may include logic to handle a packed instruction set 109. By including the packed instruction set 109 in the instruction set of a general-purpose processor 102, along with associated circuitry to execute the instructions, the operations used by many multimedia applications may be performed using packed data in a general-purpose processor 102. Thus, many multimedia applications may be accelerated and executed more efficiently by using the full width of a processor's data bus for performing operations on packed data. This may eliminate the need to transfer smaller units of data across the processor's data bus to perform one or more operations one data element at a time.

Embodiments of an execution unit 108 may also be used in micro controllers, embedded processors, graphics devices, DSPs, and other types of logic circuits. System 100 may include a memory 120. Memory 120 may be implemented as a dynamic random access memory (DRAM) device, a static random access memory (SRAM) device, flash memory device, or other memory device. Memory 120 may store instructions 119 and/or data 121 represented by data signals that may be executed by processor 102.

A system logic chip 116 may be coupled to processor bus 110 and memory 120. System logic chip 116 may include a memory controller hub (MCH). Processor 102 may communicate with MCH 116 via a processor bus 110. MCH 116 may provide a high bandwidth memory path 118 to memory 120 for storage of instructions 119 and data 121 and for storage of graphics commands, data and textures. MCH 116 may direct data signals between processor 102, memory 120, and other components in system 100 and to bridge the data signals between processor bus 110, memory 120, and system I/O 122. In some embodiments, the system logic chip 116 may provide a graphics port for coupling to a graphics controller 112. MCH 116 may be coupled to memory 120 through a memory interface 118. Graphics card 112 may be coupled to MCH 116 through an Accelerated Graphics Port (AGP) interconnect 114.

System 100 may use a proprietary hub interface bus 122 to couple MCH 116 to I/O controller hub (ICH) 130. In one embodiment, ICH 130 may provide direct connections to some I/O devices via a local I/O bus. The local I/O bus may include a high-speed I/O bus for connecting peripherals to memory 120, chipset, and processor 102. Examples may include the audio controller 129, firmware hub (flash BIOS) 128, wireless transceiver 126, data storage 124, legacy I/O controller 123 containing user input interface 125 (which may include a keyboard interface), a serial expansion port 127 such as Universal Serial Bus (USB), and a network controller 134. Data storage device 124 may comprise a hard disk drive, a floppy disk drive, a CD-ROM device, a flash memory device, or other mass storage device.

For another embodiment of a system, an instruction in accordance with one embodiment may be used with a system on a chip. One embodiment of a system on a chip comprises of a processor and a memory. The memory for one such system may include a flash memory. The flash memory may be located on the same die as the processor and other system components. Additionally, other logic blocks such as a memory controller or graphics controller may also be located on a system on a chip.

FIG. 1B illustrates a data processing system 140 which implements the principles of embodiments of the present disclosure. It will be readily appreciated by one of skill in the art that the embodiments described herein may operate with alternative processing systems without departure from the scope of embodiments of the disclosure.

Computer system 140 comprises a processing core 159 for performing at least one instruction in accordance with one embodiment. In one embodiment, processing core 159 represents a processing unit of any type of architecture, including but not limited to a CISC, a RISC or a VLIW type architecture. Processing core 159 may also be suitable for manufacture in one or more process technologies and by being represented on a machine-readable media in sufficient detail, may be suitable to facilitate said manufacture.

Processing core 159 comprises an execution unit 142, a set of register files 145, and a decoder 144. Processing core 159 may also include additional circuitry (not shown) which may be unnecessary to the understanding of embodiments of the present disclosure. Execution unit 142 may execute instructions received by processing core 159. In addition to performing typical processor instructions, execution unit 142 may perform instructions in packed instruction set 143 for performing operations on packed data formats. Packed instruction set 143 may include instructions for performing embodiments of the disclosure and other packed instructions. Execution unit 142 may be coupled to register file 145 by an internal bus. Register file 145 may represent a storage area on processing core 159 for storing information, including data. As previously mentioned, it is understood that the storage area may store the packed data might not be critical. Execution unit 142 may be coupled to decoder 144. Decoder 144 may decode instructions received by processing core 159 into control signals and/or microcode entry points. In response to these control signals and/or microcode entry points, execution unit 142 performs the appropriate operations. In one embodiment, the decoder may interpret the opcode of the instruction, which will indicate what operation should be performed on the corresponding data indicated within the instruction.

Processing core 159 may be coupled with bus 141 for communicating with various other system devices, which may include but are not limited to, for example, synchronous dynamic random access memory (SDRAM) control 146, static random access memory (SRAM) control 147, burst flash memory interface 148, personal computer memory card international association (PCMCIA)/compact flash (CF) card control 149, liquid crystal display (LCD) control 150, direct memory access (DMA) controller 151, and alternative bus master interface 152. In one embodiment, data processing system 140 may also comprise an I/O bridge 154 for communicating with various I/O devices via an I/O bus 153. Such I/O devices may include but are not limited to, for example, universal asynchronous receiver/transmitter (UART) 155, universal serial bus (USB) 156, Bluetooth wireless UART 157 and I/O expansion interface 158.

One embodiment of data processing system 140 provides for mobile, network and/or wireless communications and a processing core 159 that may perform SIMD operations including a text string comparison operation. Processing core 159 may be programmed with various audio, video, imaging and communications algorithms including discrete transformations such as a Walsh-Hadamard transform, a fast Fourier transform (FFT), a discrete cosine transform (DCT), and their respective inverse transforms; compression/decompression techniques such as color space transformation, video encode motion estimation or video decode motion compensation; and modulation/demodulation (MODEM) functions such as pulse coded modulation (PCM).

FIG. 1C illustrates other embodiments of a data processing system that performs SIMD text string comparison operations. In one embodiment, data processing system 160 may include a main processor 166, a SIMD coprocessor 161, a cache memory 167, and an input/output system 168. Input/output system 168 may optionally be coupled to a wireless interface 169. SIMD coprocessor 161 may perform operations including instructions in accordance with one embodiment. In one embodiment, processing core 170 may be suitable for manufacture in one or more process technologies and by being represented on a machine-readable media in sufficient detail, may be suitable to facilitate the manufacture of all or part of data processing system 160 including processing core 170.

In one embodiment, SIMD coprocessor 161 comprises an execution unit 162 and a set of register files 164. One embodiment of main processor 166 comprises a decoder 165 to recognize instructions of instruction set 163 including instructions in accordance with one embodiment for execution by execution unit 162. In other embodiments, SIMD coprocessor 161 also comprises at least part of decoder 165 (shown as 165B) to decode instructions of instruction set 163. Processing core 170 may also include additional circuitry (not shown) which may be unnecessary to the understanding of embodiments of the present disclosure.

In operation, main processor 166 executes a stream of data processing instructions that control data processing operations of a general type including interactions with cache memory 167, and input/output system 168. Embedded within the stream of data processing instructions may be SIMD coprocessor instructions. Decoder 165 of main processor 166 recognizes these SIMD coprocessor instructions as being of a type that should be executed by an attached SIMD coprocessor 161. Accordingly, main processor 166 issues these SIMD coprocessor instructions (or control signals representing SIMD coprocessor instructions) on the coprocessor bus 166. From coprocessor bus 171, these instructions may be received by any attached SIMD coprocessors. In this case, SIMD coprocessor 161 may accept and execute any received SIMD coprocessor instructions intended for it.

Data may be received via wireless interface 169 for processing by the SIMD coprocessor instructions. For one example, voice communication may be received in the form of a digital signal, which may be processed by the SIMD coprocessor instructions to regenerate digital audio samples representative of the voice communications. For another example, compressed audio and/or video may be received in the form of a digital bit stream, which may be processed by the SIMD coprocessor instructions to regenerate digital audio samples and/or motion video frames. In one embodiment of processing core 170, main processor 166, and a SIMD coprocessor 161 may be integrated into a single processing core 170 comprising an execution unit 162, a set of register files 164, and a decoder 165 to recognize instructions of instruction set 163 including instructions in accordance with one embodiment.

FIG. 2 is a block diagram of the micro-architecture for a processor 200 that may include logic circuits to perform instructions, in accordance with embodiments of the present disclosure. In some embodiments, an instruction in accordance with one embodiment may be implemented to operate on data elements having sizes of byte, word, doubleword, quadword, etc., as well as datatypes, such as single and double precision integer and floating point datatypes. In one embodiment, in-order front end 201 may implement a part of processor 200 that may fetch instructions to be executed and prepares the instructions to be used later in the processor pipeline. Front end 201 may include several units. In one embodiment, instruction prefetcher 226 fetches instructions from memory and feeds the instructions to an instruction decoder 228 which in turn decodes or interprets the instructions. For example, in one embodiment, the decoder decodes a received instruction into one or more operations called “micro-instructions” or “micro-operations” (also called micro op or uops) that the machine may execute. In other embodiments, the decoder parses the instruction into an opcode and corresponding data and control fields that may be used by the micro-architecture to perform operations in accordance with one embodiment. In one embodiment, trace cache 230 may assemble decoded uops into program ordered sequences or traces in uop queue 234 for execution. When trace cache 230 encounters a complex instruction, microcode ROM 232 provides the uops needed to complete the operation.

Some instructions may be converted into a single micro-op, whereas others need several micro-ops to complete the full operation. In one embodiment, if more than four micro-ops are needed to complete an instruction, decoder 228 may access microcode ROM 232 to perform the instruction. In one embodiment, an instruction may be decoded into a small number of micro ops for processing at instruction decoder 228. In another embodiment, an instruction may be stored within microcode ROM 232 should a number of micro-ops be needed to accomplish the operation. Trace cache 230 refers to an entry point programmable logic array (PLA) to determine a correct micro-instruction pointer for reading the micro-code sequences to complete one or more instructions in accordance with one embodiment from micro-code ROM 232. After microcode ROM 232 finishes sequencing micro-ops for an instruction, front end 201 of the machine may resume fetching micro-ops from trace cache 230.

Out-of-order execution engine 203 may prepare instructions for execution. The out-of-order execution logic has a number of buffers to smooth out and re-order the flow of instructions to optimize performance as they go down the pipeline and get scheduled for execution. The allocator logic in allocator/register renamer 215 allocates the machine buffers and resources that each uop needs in order to execute. The register renaming logic in allocator/register renamer 215 renames logic registers onto entries in a register file. The allocator 215 also allocates an entry for each uop in one of the two uop queues, one for memory operations (memory uop queue 207) and one for non-memory operations (integer/floating point uop queue 205), in front of the instruction schedulers: memory scheduler 209, fast scheduler 202, slow/general floating point scheduler 204, and simple floating point scheduler 206. Uop schedulers 202, 204, 206, determine when a uop is ready to execute based on the readiness of their dependent input register operand sources and the availability of the execution resources the uops need to complete their operation. Fast scheduler 202 of one embodiment may schedule on each half of the main clock cycle while the other schedulers may only schedule once per main processor clock cycle. The schedulers arbitrate for the dispatch ports to schedule uops for execution.

Register files 208, 210 may be arranged between schedulers 202, 204, 206, and execution units 212, 214, 216, 218, 220, 222, 224 in execution block 211. Each of register files 208, 210 perform integer and floating point operations, respectively. Each register file 208, 210, may include a bypass network that may bypass or forward just completed results that have not yet been written into the register file to new dependent uops. Integer register file 208 and floating point register file 210 may communicate data with the other. In one embodiment, integer register file 208 may be split into two separate register files, one register file for low-order thirty-two bits of data and a second register file for high order thirty-two bits of data. Floating point register file 210 may include 128-bit wide entries because floating point instructions typically have operands from 64 to 128 bits in width.

Execution block 211 may contain execution units 212, 214, 216, 218, 220, 222, 224. Execution units 212, 214, 216, 218, 220, 222, 224 may execute the instructions. Execution block 211 may include register files 208, 210 that store the integer and floating point data operand values that the micro-instructions need to execute. In one embodiment, processor 200 may comprise a number of execution units: address generation unit (AGU) 212, AGU 214, fast ALU 216, fast ALU 218, slow ALU 220, floating point ALU 222, floating point move unit 224. In another embodiment, floating point execution blocks 222, 224, may execute floating point, MMX, SIMD, and SSE, or other operations. In yet another embodiment, floating point ALU 222 may include a 64-bit by 64-bit floating point divider to execute divide, square root, and remainder micro-ops. In various embodiments, instructions involving a floating point value may be handled with the floating point hardware. In one embodiment, ALU operations may be passed to high-speed ALU execution units 216, 218. High-speed ALUs 216, 218 may execute fast operations with an effective latency of half a clock cycle. In one embodiment, most complex integer operations go to slow ALU 220 as slow ALU 220 may include integer execution hardware for long-latency type of operations, such as a multiplier, shifts, flag logic, and branch processing. Memory load/store operations may be executed by AGUs 212, 214. In one embodiment, integer ALUs 216, 218, 220 may perform integer operations on 64-bit data operands. In other embodiments, ALUs 216, 218, 220 may be implemented to support a variety of data bit sizes including sixteen, thirty-two, 128, 256, etc. Similarly, floating point units 222, 224 may be implemented to support a range of operands having bits of various widths. In one embodiment, floating point units 222, 224, may operate on 128-bit wide packed data operands in conjunction with SIMD and multimedia instructions.

In one embodiment, uops schedulers 202, 204, 206, dispatch dependent operations before the parent load has finished executing. As uops may be speculatively scheduled and executed in processor 200, processor 200 may also include logic to handle memory misses. If a data load misses in the data cache, there may be dependent operations in flight in the pipeline that have left the scheduler with temporarily incorrect data. A replay mechanism tracks and re-executes instructions that use incorrect data. Only the dependent operations might need to be replayed and the independent ones may be allowed to complete. The schedulers and replay mechanism of one embodiment of a processor may also be designed to catch instruction sequences for text string comparison operations.

The term “registers” may refer to the on-board processor storage locations that may be used as part of instructions to identify operands. In other words, registers may be those that may be usable from the outside of the processor (from a programmer's perspective). However, in some embodiments registers might not be limited to a particular type of circuit. Rather, a register may store data, provide data, and perform the functions described herein. The registers described herein may be implemented by circuitry within a processor using any number of different techniques, such as dedicated physical registers, dynamically allocated physical registers using register renaming, combinations of dedicated and dynamically allocated physical registers, etc. In one embodiment, integer registers store 32-bit integer data. A register file of one embodiment also contains eight multimedia SIMD registers for packed data. For the discussions below, the registers may be understood to be data registers designed to hold packed data, such as 64-bit wide MMX™ registers (also referred to as ‘mm’ registers in some instances) in microprocessors enabled with MMX technology from Intel Corporation of Santa Clara, Calif. These MMX registers, available in both integer and floating point forms, may operate with packed data elements that accompany SIMD and SSE instructions. Similarly, 128-bit wide XMM registers relating to SSE2, SSE3, SSE4, or beyond (referred to generically as “SSEx”) technology may hold such packed data operands. In one embodiment, in storing packed data and integer data, the registers do not need to differentiate between the two data types. In one embodiment, integer and floating point data may be contained in the same register file or different register files. Furthermore, in one embodiment, floating point and integer data may be stored in different registers or the same registers.

In the examples of the following figures, a number of data operands may be described. FIG. 3A illustrates various packed data type representations in multimedia registers, in accordance with embodiments of the present disclosure. FIG. 3A illustrates data types for a packed byte 310, a packed word 320, and a packed doubleword (dword) 330 for 128-bit wide operands. Packed byte format 310 of this example may be 128 bits long and contains sixteen packed byte data elements. A byte may be defined, for example, as eight bits of data. Information for each byte data element may be stored in bit 7 through bit 0 for byte 0, bit 15 through bit 8 for byte 1, bit 23 through bit 16 for byte 2, and finally bit 120 through bit 127 for byte 15. Thus, all available bits may be used in the register. This storage arrangement increases the storage efficiency of the processor. As well, with sixteen data elements accessed, one operation may now be performed on sixteen data elements in parallel.

Generally, a data element may include an individual piece of data that is stored in a single register or memory location with other data elements of the same length. In packed data sequences relating to SSEx technology, the number of data elements stored in a XMM register may be 128 bits divided by the length in bits of an individual data element. Similarly, in packed data sequences relating to MMX and SSE technology, the number of data elements stored in an MMX register may be 64 bits divided by the length in bits of an individual data element. Although the data types illustrated in FIG. 3A may be 128 bits long, embodiments of the present disclosure may also operate with 64-bit wide or other sized operands. Packed word format 320 of this example may be 128 bits long and contains eight packed word data elements. Each packed word contains sixteen bits of information. Packed doubleword format 330 of FIG. 3A may be 128 bits long and contains four packed doubleword data elements. Each packed doubleword data element contains thirty-two bits of information. A packed quadword may be 128 bits long and contain two packed quad-word data elements.

FIG. 3B illustrates possible in-register data storage formats, in accordance with embodiments of the present disclosure. Each packed data may include more than one independent data element. Three packed data formats are illustrated; packed half 341, packed single 342, and packed double 343. One embodiment of packed half 341, packed single 342, and packed double 343 contain fixed-point data elements. For another embodiment one or more of packed half 341, packed single 342, and packed double 343 may contain floating-point data elements. One embodiment of packed half 341 may be 128 bits long containing eight 16-bit data elements. One embodiment of packed single 342 may be 128 bits long and contains four 32-bit data elements. One embodiment of packed double 343 may be 128 bits long and contains two 64-bit data elements. It will be appreciated that such packed data formats may be further extended to other register lengths, for example, to 96-bits, 160-bits, 192-bits, 224-bits, 256-bits or more.

FIG. 3C illustrates various signed and unsigned packed data type representations in multimedia registers, in accordance with embodiments of the present disclosure. Unsigned packed byte representation 344 illustrates the storage of an unsigned packed byte in a SIMD register. Information for each byte data element may be stored in bit 7 through bit 0 for byte 0, bit 15 through bit 8 for byte 1, bit 23 through bit 16 for byte 2, and finally bit 120 through bit 127 for byte 15. Thus, all available bits may be used in the register. This storage arrangement may increase the storage efficiency of the processor. As well, with sixteen data elements accessed, one operation may now be performed on sixteen data elements in a parallel fashion. Signed packed byte representation 345 illustrates the storage of a signed packed byte. Note that the eighth bit of every byte data element may be the sign indicator. Unsigned packed word representation 346 illustrates how word seven through word zero may be stored in a SIMD register. Signed packed word representation 347 may be similar to the unsigned packed word in-register representation 346. Note that the sixteenth bit of each word data element may be the sign indicator. Unsigned packed doubleword representation 348 shows how doubleword data elements are stored. Signed packed doubleword representation 349 may be similar to unsigned packed doubleword in-register representation 348. Note that the necessary sign bit may be the thirty-second bit of each doubleword data element.

FIG. 3D illustrates an embodiment of an operation encoding (opcode). Furthermore, format 360 may include register/memory operand addressing modes corresponding with a type of opcode format described in the “IA-32 Intel Architecture Software Developer's Manual Volume 2: Instruction Set Reference,” which is available from Intel Corporation, Santa Clara, Calif. on the world-wide-web (www) at intel.com/design/litcentr. In one embodiment, an instruction may be encoded by one or more of fields 361 and 362. Up to two operand locations per instruction may be identified, including up to two source operand identifiers 364 and 365. In one embodiment, destination operand identifier 366 may be the same as source operand identifier 364, whereas in other embodiments they may be different. In another embodiment, destination operand identifier 366 may be the same as source operand identifier 365, whereas in other embodiments they may be different. In one embodiment, one of the source operands identified by source operand identifiers 364 and 365 may be overwritten by the results of the text string comparison operations, whereas in other embodiments identifier 364 corresponds to a source register element and identifier 365 corresponds to a destination register element. In one embodiment, operand identifiers 364 and 365 may identify 32-bit or 64-bit source and destination operands.

FIG. 3E illustrates another possible operation encoding (opcode) format 370, having forty or more bits, in accordance with embodiments of the present disclosure. Opcode format 370 corresponds with opcode format 360 and comprises an optional prefix byte 378. An instruction according to one embodiment may be encoded by one or more of fields 378, 371, and 372. Up to two operand locations per instruction may be identified by source operand identifiers 374 and 375 and by prefix byte 378. In one embodiment, prefix byte 378 may be used to identify 32-bit or 64-bit source and destination operands. In one embodiment, destination operand identifier 376 may be the same as source operand identifier 374, whereas in other embodiments they may be different. For another embodiment, destination operand identifier 376 may be the same as source operand identifier 375, whereas in other embodiments they may be different. In one embodiment, an instruction operates on one or more of the operands identified by operand identifiers 374 and 375 and one or more operands identified by operand identifiers 374 and 375 may be overwritten by the results of the instruction, whereas in other embodiments, operands identified by identifiers 374 and 375 may be written to another data element in another register. Opcode formats 360 and 370 allow register to register, memory to register, register by memory, register by register, register by immediate, register to memory addressing specified in part by MOD fields 363 and 373 and by optional scale-index-base and displacement bytes.

FIG. 3F illustrates yet another possible operation encoding (opcode) format, in accordance with embodiments of the present disclosure. 64-bit single instruction multiple data (SIMD) arithmetic operations may be performed through a coprocessor data processing (CDP) instruction. Operation encoding (opcode) format 380 depicts one such CDP instruction having CDP opcode fields 382 and 389. The type of CDP instruction, for another embodiment, operations may be encoded by one or more of fields 383, 384, 387, and 388. Up to three operand locations per instruction may be identified, including up to two source operand identifiers 385 and 390 and one destination operand identifier 386. One embodiment of the coprocessor may operate on eight, sixteen, thirty-two, and 64-bit values. In one embodiment, an instruction may be performed on integer data elements. In some embodiments, an instruction may be executed conditionally, using condition field 381. For some embodiments, source data sizes may be encoded by field 383. In some embodiments, Zero (Z), negative (N), carry (C), and overflow (V) detection may be done on SIMD fields. For some instructions, the type of saturation may be encoded by field 384.

FIG. 4A is a block diagram illustrating an in-order pipeline and a register renaming stage, out-of-order issue/execution pipeline, in accordance with embodiments of the present disclosure. FIG. 4B is a block diagram illustrating an in-order architecture core and a register renaming logic, out-of-order issue/execution logic to be included in a processor, in accordance with embodiments of the present disclosure. The solid lined boxes in FIG. 4A illustrate the in-order pipeline, while the dashed lined boxes illustrates the register renaming, out-of-order issue/execution pipeline. Similarly, the solid lined boxes in FIG. 4B illustrate the in-order architecture logic, while the dashed lined boxes illustrates the register renaming logic and out-of-order issue/execution logic.

In FIG. 4A, a processor pipeline 400 may include a fetch stage 402, a length decode stage 404, a decode stage 406, an allocation stage 408, a renaming stage 410, a scheduling (also known as a dispatch or issue) stage 412, a register read/memory read stage 414, an execute stage 416, a write-back/memory-write stage 418, an exception handling stage 422, and a commit stage 424.

In FIG. 4B, arrows denote a coupling between two or more units and the direction of the arrow indicates a direction of data flow between those units. FIG. 4B shows processor core 490 including a front end unit 430 coupled to an execution engine unit 450, and both may be coupled to a memory unit 470.

Core 490 may be a reduced instruction set computing (RISC) core, a complex instruction set computing (CISC) core, a very long instruction word (VLIW) core, or a hybrid or alternative core type. In one embodiment, core 490 may be a special-purpose core, such as, for example, a network or communication core, compression engine, graphics core, or the like.

Front end unit 430 may include a branch prediction unit 432 coupled to an instruction cache unit 434. Instruction cache unit 434 may be coupled to an instruction translation lookaside buffer (TLB) 436. TLB 436 may be coupled to an instruction fetch unit 438, which is coupled to a decode unit 440. Decode unit 440 may decode instructions, and generate as an output one or more micro-operations, micro-code entry points, microinstructions, other instructions, or other control signals, which may be decoded from, or which otherwise reflect, or may be derived from, the original instructions. The decoder may be implemented using various different mechanisms. Examples of suitable mechanisms include, but are not limited to, look-up tables, hardware implementations, programmable logic arrays (PLAs), microcode read-only memories (ROMs), etc. In one embodiment, instruction cache unit 434 may be further coupled to a level 2 (L2) cache unit 476 in memory unit 470. Decode unit 440 may be coupled to a rename/allocator unit 452 in execution engine unit 450.

Execution engine unit 450 may include rename/allocator unit 452 coupled to a retirement unit 454 and a set of one or more scheduler units 456. Scheduler units 456 represent any number of different schedulers, including reservations stations, central instruction window, etc. Scheduler units 456 may be coupled to physical register file units 458. Each of physical register file units 458 represents one or more physical register files, different ones of which store one or more different data types, such as scalar integer, scalar floating point, packed integer, packed floating point, vector integer, vector floating point, etc., status (e.g., an instruction pointer that is the address of the next instruction to be executed), etc. Physical register file units 458 may be overlapped by retirement unit 454 to illustrate various ways in which register renaming and out-of-order execution may be implemented (e.g., using one or more reorder buffers and one or more retirement register files, using one or more future files, one or more history buffers, and one or more retirement register files; using register maps and a pool of registers; etc.). Generally, the architectural registers may be visible from the outside of the processor or from a programmer's perspective. The registers might not be limited to any known particular type of circuit. Various different types of registers may be suitable as long as they store and provide data as described herein. Examples of suitable registers include, but might not be limited to, dedicated physical registers, dynamically allocated physical registers using register renaming, combinations of dedicated and dynamically allocated physical registers, etc. Retirement unit 454 and physical register file units 458 may be coupled to execution clusters 460. Execution clusters 460 may include a set of one or more execution units 462 and a set of one or more memory access units 464. Execution units 462 may perform various operations (e.g., shifts, addition, subtraction, multiplication) and on various types of data (e.g., scalar floating point, packed integer, packed floating point, vector integer, vector floating point). While some embodiments may include a number of execution units dedicated to specific functions or sets of functions, other embodiments may include only one execution unit or multiple execution units that all perform all functions. Scheduler units 456, physical register file units 458, and execution clusters 460 are shown as being possibly plural because certain embodiments create separate pipelines for certain types of data/operations (e.g., a scalar integer pipeline, a scalar floating point/packed integer/packed floating point/vector integer/vector floating point pipeline, and/or a memory access pipeline that each have their own scheduler unit, physical register file unit, and/or execution cluster—and in the case of a separate memory access pipeline, certain embodiments may be implemented in which only the execution cluster of this pipeline has memory access units 464). It should also be understood that where separate pipelines are used, one or more of these pipelines may be out-of-order issue/execution and the rest in-order.

The set of memory access units 464 may be coupled to memory unit 470, which may include a data TLB unit 472 coupled to a data cache unit 474 coupled to a level 2 (L2) cache unit 476. In one exemplary embodiment, memory access units 464 may include a load unit, a store address unit, and a store data unit, each of which may be coupled to data TLB unit 472 in memory unit 470. L2 cache unit 476 may be coupled to one or more other levels of cache and eventually to a main memory.

By way of example, the exemplary register renaming, out-of-order issue/execution core architecture may implement pipeline 400 as follows: 1) instruction fetch 438 may perform fetch and length decoding stages 402 and 404; 2) decode unit 440 may perform decode stage 406; 3) rename/allocator unit 452 may perform allocation stage 408 and renaming stage 410; 4) scheduler units 456 may perform schedule stage 412; 5) physical register file units 458 and memory unit 470 may perform register read/memory read stage 414; execution cluster 460 may perform execute stage 416; 6) memory unit 470 and physical register file units 458 may perform write-back/memory-write stage 418; 7) various units may be involved in the performance of exception handling stage 422; and 8) retirement unit 454 and physical register file units 458 may perform commit stage 424.

Core 490 may support one or more instructions sets (e.g., the x86 instruction set (with some extensions that have been added with newer versions); the MIPS instruction set of MIPS Technologies of Sunnyvale, Calif.; the ARM instruction set (with optional additional extensions such as NEON) of ARM Holdings of Sunnyvale, Calif.).

It should be understood that the core may support multithreading (executing two or more parallel sets of operations or threads) in a variety of manners. Multithreading support may be performed by, for example, including time sliced multithreading, simultaneous multithreading (where a single physical core provides a logical core for each of the threads that physical core is simultaneously multithreading), or a combination thereof. Such a combination may include, for example, time sliced fetching and decoding and simultaneous multithreading thereafter such as in the Intel® Hyperthreading technology.

While register renaming may be described in the context of out-of-order execution, it should be understood that register renaming may be used in an in-order architecture. While the illustrated embodiment of the processor may also include a separate instruction and data cache units 434/474 and a shared L2 cache unit 476, other embodiments may have a single internal cache for both instructions and data, such as, for example, a Level 1 (L1) internal cache, or multiple levels of internal cache. In some embodiments, the system may include a combination of an internal cache and an external cache that may be external to the core and/or the processor. In other embodiments, all of the caches may be external to the core and/or the processor.

FIG. 5A is a block diagram of a processor 500, in accordance with embodiments of the present disclosure. In one embodiment, processor 500 may include a multicore processor. Processor 500 may include a system agent 510 communicatively coupled to one or more cores 502. Furthermore, cores 502 and system agent 510 may be communicatively coupled to one or more caches 506. Cores 502, system agent 510, and caches 506 may be communicatively coupled via one or more memory control units 552. Furthermore, cores 502, system agent 510, and caches 506 may be communicatively coupled to a graphics module 560 via memory control units 552.

Processor 500 may include any suitable mechanism for interconnecting cores 502, system agent 510, and caches 506, and graphics module 560. In one embodiment, processor 500 may include a ring-based interconnect unit 508 to interconnect cores 502, system agent 510, and caches 506, and graphics module 560. In other embodiments, processor 500 may include any number of well-known techniques for interconnecting such units. Ring-based interconnect unit 508 may utilize memory control units 552 to facilitate interconnections.

Processor 500 may include a memory hierarchy comprising one or more levels of caches within the cores, one or more shared cache units such as caches 506, or external memory (not shown) coupled to the set of integrated memory controller units 552. Caches 506 may include any suitable cache. In one embodiment, caches 506 may include one or more mid-level caches, such as level 2 (L2), level 3 (L3), level 4 (L4), or other levels of cache, a last level cache (LLC), and/or combinations thereof.

In various embodiments, one or more of cores 502 may perform multi-threading. System agent 510 may include components for coordinating and operating cores 502. System agent unit 510 may include for example a power control unit (PCU). The PCU may be or include logic and components needed for regulating the power state of cores 502. System agent 510 may include a display engine 512 for driving one or more externally connected displays or graphics module 560. System agent 510 may include an interface 514 for communications busses for graphics. In one embodiment, interface 514 may be implemented by PCI Express (PCIe). In a further embodiment, interface 514 may be implemented by PCI Express Graphics (PEG). System agent 510 may include a direct media interface (DMI) 516. DMI 516 may provide links between different bridges on a motherboard or other portion of a computer system. System agent 510 may include a PCIe bridge 518 for providing PCIe links to other elements of a computing system. PCIe bridge 518 may be implemented using a memory controller 520 and coherence logic 522.

Cores 502 may be implemented in any suitable manner. Cores 502 may be homogenous or heterogeneous in terms of architecture and/or instruction set. In one embodiment, some of cores 502 may be in-order while others may be out-of-order. In another embodiment, two or more of cores 502 may execute the same instruction set, while others may execute only a subset of that instruction set or a different instruction set.

Processor 500 may include a general-purpose processor, such as a Core™ i3, i5, i7, 2 Duo and Quad, Xeon™, Itanium™, XScale™ or StrongARM™ processor, which may be available from Intel Corporation, of Santa Clara, Calif. Processor 500 may be provided from another company, such as ARM Holdings, Ltd, MIPS, etc. Processor 500 may be a special-purpose processor, such as, for example, a network or communication processor, compression engine, graphics processor, co-processor, embedded processor, or the like. Processor 500 may be implemented on one or more chips. Processor 500 may be a part of and/or may be implemented on one or more substrates using any of a number of process technologies, such as, for example, BiCMOS, CMOS, or NMOS.

In one embodiment, a given one of caches 506 may be shared by multiple ones of cores 502. In another embodiment, a given one of caches 506 may be dedicated to one of cores 502. The assignment of caches 506 to cores 502 may be handled by a cache controller or other suitable mechanism. A given one of caches 506 may be shared by two or more cores 502 by implementing time-slices of a given cache 506.

Graphics module 560 may implement an integrated graphics processing subsystem. In one embodiment, graphics module 560 may include a graphics processor. Furthermore, graphics module 560 may include a media engine 565. Media engine 565 may provide media encoding and video decoding.

FIG. 5B is a block diagram of an example implementation of a core 502, in accordance with embodiments of the present disclosure. Core 502 may include a front end 570 communicatively coupled to an out-of-order engine 580. Core 502 may be communicatively coupled to other portions of processor 500 through cache hierarchy 503.

Front end 570 may be implemented in any suitable manner, such as fully or in part by front end 201 as described above. In one embodiment, front end 570 may communicate with other portions of processor 500 through cache hierarchy 503. In a further embodiment, front end 570 may fetch instructions from portions of processor 500 and prepare the instructions to be used later in the processor pipeline as they are passed to out-of-order execution engine 580.

Out-of-order execution engine 580 may be implemented in any suitable manner, such as fully or in part by out-of-order execution engine 203 as described above. Out-of-order execution engine 580 may prepare instructions received from front end 570 for execution. Out-of-order execution engine 580 may include an allocate module 582. In one embodiment, allocate module 582 may allocate resources of processor 500 or other resources, such as registers or buffers, to execute a given instruction. Allocate module 582 may make allocations in schedulers, such as a memory scheduler, fast scheduler, or floating point scheduler. Such schedulers may be represented in FIG. 5B by resource schedulers 584. Allocate module 582 may be implemented fully or in part by the allocation logic described in conjunction with FIG. 2. Resource schedulers 584 may determine when an instruction is ready to execute based on the readiness of a given resource's sources and the availability of execution resources needed to execute an instruction. Resource schedulers 584 may be implemented by, for example, schedulers 202, 204, 206 as discussed above. Resource schedulers 584 may schedule the execution of instructions upon one or more resources. In one embodiment, such resources may be internal to core 502, and may be illustrated, for example, as resources 586. In another embodiment, such resources may be external to core 502 and may be accessible by, for example, cache hierarchy 503. Resources may include, for example, memory, caches, register files, or registers. Resources internal to core 502 may be represented by resources 586 in FIG. 5B. As necessary, values written to or read from resources 586 may be coordinated with other portions of processor 500 through, for example, cache hierarchy 503. As instructions are assigned resources, they may be placed into a reorder buffer 588. Reorder buffer 588 may track instructions as they are executed and may selectively reorder their execution based upon any suitable criteria of processor 500. In one embodiment, reorder buffer 588 may identify instructions or a series of instructions that may be executed independently. Such instructions or a series of instructions may be executed in parallel from other such instructions. Parallel execution in core 502 may be performed by any suitable number of separate execution blocks or virtual processors. In one embodiment, shared resources—such as memory, registers, and caches—may be accessible to multiple virtual processors within a given core 502. In other embodiments, shared resources may be accessible to multiple processing entities within processor 500.

Cache hierarchy 503 may be implemented in any suitable manner. For example, cache hierarchy 503 may include one or more lower or mid-level caches, such as caches 572, 574. In one embodiment, cache hierarchy 503 may include an LLC 595 communicatively coupled to caches 572, 574. In another embodiment, LLC 595 may be implemented in a module 590 accessible to all processing entities of processor 500. In a further embodiment, module 590 may be implemented in an uncore module of processors from Intel, Inc. Module 590 may include portions or subsystems of processor 500 necessary for the execution of core 502 but might not be implemented within core 502. Besides LLC 595, Module 590 may include, for example, hardware interfaces, memory coherency coordinators, interprocessor interconnects, instruction pipelines, or memory controllers. Access to RAM 599 available to processor 500 may be made through module 590 and, more specifically, LLC 595. Furthermore, other instances of core 502 may similarly access module 590. Coordination of the instances of core 502 may be facilitated in part through module 590.

FIGS. 6-8 may illustrate exemplary systems suitable for including processor 500, while FIG. 9 may illustrate an exemplary system on a chip (SoC) that may include one or more of cores 502. Other system designs and implementations known in the arts for laptops, desktops, handheld PCs, personal digital assistants, engineering workstations, servers, network devices, network hubs, switches, embedded processors, digital signal processors (DSPs), graphics devices, video game devices, set-top boxes, micro controllers, cell phones, portable media players, hand held devices, and various other electronic devices, may also be suitable. In general, a huge variety of systems or electronic devices that incorporate a processor and/or other execution logic as disclosed herein may be generally suitable.

FIG. 6 illustrates a block diagram of a system 600, in accordance with embodiments of the present disclosure. System 600 may include one or more processors 610, 615, which may be coupled to graphics memory controller hub (GMCH) 620. The optional nature of additional processors 615 is denoted in FIG. 6 with broken lines.

Each processor 610,615 may be some version of processor 500. However, it should be noted that integrated graphics logic and integrated memory control units might not exist in processors 610,615. FIG. 6 illustrates that GMCH 620 may be coupled to a memory 640 that may be, for example, a dynamic random access memory (DRAM). The DRAM may, for at least one embodiment, be associated with a non-volatile cache.

GMCH 620 may be a chipset, or a portion of a chipset. GMCH 620 may communicate with processors 610, 615 and control interaction between processors 610, 615 and memory 640. GMCH 620 may also act as an accelerated bus interface between the processors 610, 615 and other elements of system 600. In one embodiment, GMCH 620 communicates with processors 610, 615 via a multi-drop bus, such as a frontside bus (FSB) 695.

Furthermore, GMCH 620 may be coupled to a display 645 (such as a flat panel display). In one embodiment, GMCH 620 may include an integrated graphics accelerator. GMCH 620 may be further coupled to an input/output (I/O) controller hub (ICH) 650, which may be used to couple various peripheral devices to system 600. External graphics device 660 may include a discrete graphics device coupled to ICH 650 along with another peripheral device 670.

In other embodiments, additional or different processors may also be present in system 600. For example, additional processors 610, 615 may include additional processors that may be the same as processor 610, additional processors that may be heterogeneous or asymmetric to processor 610, accelerators (such as, e.g., graphics accelerators or digital signal processing (DSP) units), field programmable gate arrays, or any other processor. There may be a variety of differences between the physical resources 610, 615 in terms of a spectrum of metrics of merit including architectural, micro-architectural, thermal, power consumption characteristics, and the like. These differences may effectively manifest themselves as asymmetry and heterogeneity amongst processors 610, 615. For at least one embodiment, various processors 610, 615 may reside in the same die package.

FIG. 7 illustrates a block diagram of a second system 700, in accordance with embodiments of the present disclosure. As shown in FIG. 7, multiprocessor system 700 may include a point-to-point interconnect system, and may include a first processor 770 and a second processor 780 coupled via a point-to-point interconnect 750. Each of processors 770 and 780 may be some version of processor 500 as one or more of processors 610,615.

While FIG. 7 may illustrate two processors 770, 780, it is to be understood that the scope of the present disclosure is not so limited. In other embodiments, one or more additional processors may be present in a given processor.

Processors 770 and 780 are shown including integrated memory controller units 772 and 782, respectively. Processor 770 may also include as part of its bus controller units point-to-point (P-P) interfaces 776 and 778; similarly, second processor 780 may include P-P interfaces 786 and 788. Processors 770, 780 may exchange information via a point-to-point (P-P) interface 750 using P-P interface circuits 778, 788. As shown in FIG. 7, IMCs 772 and 782 may couple the processors to respective memories, namely a memory 732 and a memory 734, which in one embodiment may be portions of main memory locally attached to the respective processors.

Processors 770, 780 may each exchange information with a chipset 790 via individual P-P interfaces 752, 754 using point to point interface circuits 776, 794, 786, 798. In one embodiment, chipset 790 may also exchange information with a high-performance graphics circuit 738 via a high-performance graphics interface 739.

A shared cache (not shown) may be included in either processor or outside of both processors, yet connected with the processors via P-P interconnect, such that either or both processors' local cache information may be stored in the shared cache if a processor is placed into a low power mode.

Chipset 790 may be coupled to a first bus 716 via an interface 796. In one embodiment, first bus 716 may be a Peripheral Component Interconnect (PCI) bus, or a bus such as a PCI Express bus or another third generation I/O interconnect bus, although the scope of the present disclosure is not so limited.

As shown in FIG. 7, various I/O devices 714 may be coupled to first bus 716, along with a bus bridge 718 which couples first bus 716 to a second bus 720. In one embodiment, second bus 720 may be a low pin count (LPC) bus. Various devices may be coupled to second bus 720 including, for example, a keyboard and/or mouse 722, communication devices 727 and a storage unit 728 such as a disk drive or other mass storage device which may include instructions/code and data 730, in one embodiment. Further, an audio I/O 724 may be coupled to second bus 720. Note that other architectures may be possible. For example, instead of the point-to-point architecture of FIG. 7, a system may implement a multi-drop bus or other such architecture.

FIG. 8 illustrates a block diagram of a third system 800 in accordance with embodiments of the present disclosure. Like elements in FIGS. 7 and 8 bear like reference numerals, and certain aspects of FIG. 7 have been omitted from FIG. 8 in order to avoid obscuring other aspects of FIG. 8.

FIG. 8 illustrates that processors 770, 780 may include integrated memory and I/O control logic (“CL”) 872 and 882, respectively. For at least one embodiment, CL 872, 882 may include integrated memory controller units such as that described above in connection with FIGS. 5 and 7. In addition. CL 872, 882 may also include I/O control logic. FIG. 8 illustrates that not only memories 732, 734 may be coupled to CL 872, 882, but also that I/O devices 814 may also be coupled to control logic 872, 882. Legacy I/O devices 815 may be coupled to chipset 790.

FIG. 9 illustrates a block diagram of a SoC 900, in accordance with embodiments of the present disclosure. Similar elements in FIG. 5 bear like reference numerals. Also, dashed lined boxes may represent optional features on more advanced SoCs. An interconnect units 902 may be coupled to: an application processor 910 which may include a set of one or more cores 502A-N and shared cache units 506; a system agent unit 510; a bus controller units 916; an integrated memory controller units 914; a set or one or more media processors 920 which may include integrated graphics logic 908, an image processor 924 for providing still and/or video camera functionality, an audio processor 926 for providing hardware audio acceleration, and a video processor 928 for providing video encode/decode acceleration; an static random access memory (SRAM) unit 930; a direct memory access (DMA) unit 932; and a display unit 940 for coupling to one or more external displays.

FIG. 10 illustrates a processor containing a central processing unit (CPU) and a graphics processing unit (GPU), which may perform at least one instruction, in accordance with embodiments of the present disclosure. In one embodiment, an instruction to perform operations according to at least one embodiment could be performed by the CPU. In another embodiment, the instruction could be performed by the GPU. In still another embodiment, the instruction may be performed through a combination of operations performed by the GPU and the CPU. For example, in one embodiment, an instruction in accordance with one embodiment may be received and decoded for execution on the GPU. However, one or more operations within the decoded instruction may be performed by a CPU and the result returned to the GPU for final retirement of the instruction. Conversely, in some embodiments, the CPU may act as the primary processor and the GPU as the co-processor.

In some embodiments, instructions that benefit from highly parallel, throughput processors may be performed by the GPU, while instructions that benefit from the performance of processors that benefit from deeply pipelined architectures may be performed by the CPU. For example, graphics, scientific applications, financial applications and other parallel workloads may benefit from the performance of the GPU and be executed accordingly, whereas more sequential applications, such as operating system kernel or application code may be better suited for the CPU.

In FIG. 10, processor 1000 includes a CPU 1005, GPU 1010, image processor 1015, video processor 1020, USB controller 1025, UART controller 1030, SPI/SDIO controller 1035, display device 1040, memory interface controller 1045, MIPI controller 1050, flash memory controller 1055, dual data rate (DDR) controller 1060, security engine 1065, and I²S/I²C controller 1070. Other logic and circuits may be included in the processor of FIG. 10, including more CPUs or GPUs and other peripheral interface controllers.

One or more aspects of at least one embodiment may be implemented by representative data stored on a machine-readable medium which represents various logic within the processor, which when read by a machine causes the machine to fabricate logic to perform the techniques described herein. Such representations, known as “IP cores” may be stored on a tangible, machine-readable medium (“tape”) and supplied to various customers or manufacturing facilities to load into the fabrication machines that actually make the logic or processor. For example, IP cores, such as the Cortex™ family of processors developed by ARM Holdings, Ltd. and Loongson IP cores developed the Institute of Computing Technology (ICT) of the Chinese Academy of Sciences may be licensed or sold to various customers or licensees, such as Texas Instruments, Qualcomm, Apple, or Samsung and implemented in processors produced by these customers or licensees.

FIG. 11 illustrates a block diagram illustrating the development of IP cores, in accordance with embodiments of the present disclosure. Storage 1100 may include simulation software 1120 and/or hardware or software model 1110. In one embodiment, the data representing the IP core design may be provided to storage 1100 via memory 1140 (e.g., hard disk), wired connection (e.g., internet) 1150 or wireless connection 1160. The IP core information generated by the simulation tool and model may then be transmitted to a fabrication facility 1165 where it may be fabricated by a 3^rdparty to perform at least one instruction in accordance with at least one embodiment.

In some embodiments, one or more instructions may correspond to a first type or architecture (e.g., x86) and be translated or emulated on a processor of a different type or architecture (e.g., ARM). An instruction, according to one embodiment, may therefore be performed on any processor or processor type, including ARM, x86, MIPS, a GPU, or other processor type or architecture.

FIG. 12 illustrates how an instruction of a first type may be emulated by a processor of a different type, in accordance with embodiments of the present disclosure. In FIG. 12, program 1205 contains some instructions that may perform the same or substantially the same function as an instruction according to one embodiment. However the instructions of program 1205 may be of a type and/or format that is different from or incompatible with processor 1215, meaning the instructions of the type in program 1205 may not be able to execute natively by the processor 1215. However, with the help of emulation logic, 1210, the instructions of program 1205 may be translated into instructions that may be natively be executed by the processor 1215. In one embodiment, the emulation logic may be embodied in hardware. In another embodiment, the emulation logic may be embodied in a tangible, machine-readable medium containing software to translate instructions of the type in program 1205 into the type natively executable by processor 1215. In other embodiments, emulation logic may be a combination of fixed-function or programmable hardware and a program stored on a tangible, machine-readable medium. In one embodiment, the processor contains the emulation logic, whereas in other embodiments, the emulation logic exists outside of the processor and may be provided by a third party. In one embodiment, the processor may load the emulation logic embodied in a tangible, machine-readable medium containing software by executing microcode or firmware contained in or associated with the processor.

FIG. 13 illustrates a block diagram contrasting the use of a software instruction converter to convert binary instructions in a source instruction set to binary instructions in a target instruction set, in accordance with embodiments of the present disclosure. In the illustrated embodiment, the instruction converter may be a software instruction converter, although the instruction converter may be implemented in software, firmware, hardware, or various combinations thereof. FIG. 13 shows a program in a high level language 1302 may be compiled using an x86 compiler 1304 to generate x86 binary code 1306 that may be natively executed by a processor with at least one x86 instruction set core 1316. The processor with at least one x86 instruction set core 1316 represents any processor that may perform substantially the same functions as an Intel processor with at least one x86 instruction set core by compatibly executing or otherwise processing (1) a substantial portion of the instruction set of the Intel x86 instruction set core or (2) object code versions of applications or other software targeted to run on an Intel processor with at least one x86 instruction set core, in order to achieve substantially the same result as an Intel processor with at least one x86 instruction set core. x86 compiler 1304 represents a compiler that may be operable to generate x86 binary code 1306 (e.g., object code) that may, with or without additional linkage processing, be executed on the processor with at least one x86 instruction set core 1316. Similarly, FIG. 13 shows the program in high level language 1302 may be compiled using an alternative instruction set compiler 1308 to generate alternative instruction set binary code 1310 that may be natively executed by a processor without at least one x86 instruction set core 1314 (e.g., a processor with cores that execute the MIPS instruction set of MIPS Technologies of Sunnyvale, Calif. and/or that execute the ARM instruction set of ARM Holdings of Sunnyvale, Calif.). Instruction converter 1312 may be used to convert x86 binary code 1306 into code that may be natively executed by the processor without an x86 instruction set core 1314. This converted code might not be the same as alternative instruction set binary code 1310; however, the converted code will accomplish the general operation and be made up of instructions from the alternative instruction set. Thus, instruction converter 1312 represents software, firmware, hardware, or a combination thereof that, through emulation, simulation or any other process, allows a processor or other electronic device that does not have an x86 instruction set processor or core to execute x86 binary code 1306.

FIG. 14 is a block diagram of an instruction set architecture 1400 of a processor, in accordance with embodiments of the present disclosure. Instruction set architecture 1400 may include any suitable number or kind of components.

For example, instruction set architecture 1400 may include processing entities such as one or more cores 1406, 1407 and a graphics processing unit 1415. Cores 1406, 1407 may be communicatively coupled to the rest of instruction set architecture 1400 through any suitable mechanism, such as through a bus or cache. In one embodiment, cores 1406, 1407 may be communicatively coupled through an L2 cache control 1408, which may include a bus interface unit 1409 and an L2 cache 1411. Cores 1406, 1407 and graphics processing unit 1415 may be communicatively coupled to each other and to the remainder of instruction set architecture 1400 through interconnect 1410. In one embodiment, graphics processing unit 1415 may use a video code 1420 defining the manner in which particular video signals will be encoded and decoded for output.

Instruction set architecture 1400 may also include any number or kind of interfaces, controllers, or other mechanisms for interfacing or communicating with other portions of an electronic device or system. Such mechanisms may facilitate interaction with, for example, peripherals, communications devices, other processors, or memory. In the example of FIG. 14, instruction set architecture 1400 may include a liquid crystal display (LCD) video interface 1425, a subscriber interface module (SIM) interface 1430, a boot ROM interface 1435, a synchronous dynamic random access memory (SDRAM) controller 1440, a flash controller 1445, and a serial peripheral interface (SPI) master unit 1450. LCD video interface 1425 may provide output of video signals from, for example, GPU 1415 and through, for example, a mobile industry processor interface (MIPI) 1490 or a high-definition multimedia interface (HDMI) 1495 to a display. Such a display may include, for example, an LCD. SIM interface 1430 may provide access to or from a SIM card or device. SDRAM controller 1440 may provide access to or from memory such as an SDRAM chip or module 1460. Flash controller 1445 may provide access to or from memory such as flash memory 1465 or other instances of RAM. SPI master unit 1450 may provide access to or from communications modules, such as a Bluetooth module 1470, high-speed 3G modem 1475, global positioning system module 1480, or wireless module 1485 implementing a communications standard such as 802.11.

FIG. 15 is a more detailed block diagram of an instruction set architecture 1500 of a processor, in accordance with embodiments of the present disclosure. Instruction architecture 1500 may implement one or more aspects of instruction set architecture 1400. Furthermore, instruction set architecture 1500 may illustrate modules and mechanisms for the execution of instructions within a processor.

Instruction architecture 1500 may include a memory system 1540 communicatively coupled to one or more execution entities 1565. Furthermore, instruction architecture 1500 may include a caching and bus interface unit such as unit 1510 communicatively coupled to execution entities 1565 and memory system 1540. In one embodiment, loading of instructions into execution entities 1565 may be performed by one or more stages of execution. Such stages may include, for example, instruction prefetch stage 1530, dual instruction decode stage 1550, register rename stage 1555, issue stage 1560, and writeback stage 1570.

In one embodiment, memory system 1540 may include an executed instruction pointer 1580. Executed instruction pointer 1580 may store a value identifying the oldest, undispatched instruction within a batch of instructions. The oldest instruction may correspond to the lowest Program Order (PO) value. A PO may include a unique number of an instruction. Such an instruction may be a single instruction within a thread represented by multiple strands. A PO may be used in ordering instructions to ensure correct execution semantics of code. A PO may be reconstructed by mechanisms such as evaluating increments to PO encoded in the instruction rather than an absolute value. Such a reconstructed PO may be known as an “RPO.” Although a PO may be referenced herein, such a PO may be used interchangeably with an RPO. A strand may include a sequence of instructions that are data dependent upon each other. The strand may be arranged by a binary translator at compilation time. Hardware executing a strand may execute the instructions of a given strand in order according to the PO of the various instructions. A thread may include multiple strands such that instructions of different strands may depend upon each other. A PO of a given strand may be the PO of the oldest instruction in the strand which has not yet been dispatched to execution from an issue stage. Accordingly, given a thread of multiple strands, each strand including instructions ordered by PO, executed instruction pointer 1580 may store the oldest—illustrated by the lowest number—PO in the thread.

In another embodiment, memory system 1540 may include a retirement pointer 1582. Retirement pointer 1582 may store a value identifying the PO of the last retired instruction. Retirement pointer 1582 may be set by, for example, retirement unit 454. If no instructions have yet been retired, retirement pointer 1582 may include a null value.

Execution entities 1565 may include any suitable number and kind of mechanisms by which a processor may execute instructions. In the example of FIG. 15, execution entities 1565 may include ALU/multiplication units (MUL) 1566, ALUs 1567, and floating point units (FPU) 1568. In one embodiment, such entities may make use of information contained within a given address 1569. Execution entities 1565 in combination with stages 1530, 1550, 1555, 1560, 1570 may collectively form an execution unit.

Unit 1510 may be implemented in any suitable manner. In one embodiment, unit 1510 may perform cache control. In such an embodiment, unit 1510 may thus include a cache 1525. Cache 1525 may be implemented, in a further embodiment, as an L2 unified cache with any suitable size, such as zero, 128 k, 256 k, 512 k, 1M, or 2M bytes of memory. In another, further embodiment, cache 1525 may be implemented in error-correcting code memory. In another embodiment, unit 1510 may perform bus interfacing to other portions of a processor or electronic device. In such an embodiment, unit 1510 may thus include a bus interface unit 1520 for communicating over an interconnect, intraprocessor bus, interprocessor bus, or other communication bus, port, or line. Bus interface unit 1520 may provide interfacing in order to perform, for example, generation of the memory and input/output addresses for the transfer of data between execution entities 1565 and the portions of a system external to instruction architecture 1500.

To further facilitate its functions, bus interface unit 1520 may include an interrupt control and distribution unit 1511 for generating interrupts and other communications to other portions of a processor or electronic device. In one embodiment, bus interface unit 1520 may include a snoop control unit 1512 that handles cache access and coherency for multiple processing cores. In a further embodiment, to provide such functionality, snoop control unit 1512 may include a cache-to-cache transfer unit that handles information exchanges between different caches. In another, further embodiment, snoop control unit 1512 may include one or more snoop filters 1514 that monitors the coherency of other caches (not shown) so that a cache controller, such as unit 1510, does not have to perform such monitoring directly. Unit 1510 may include any suitable number of timers 1515 for synchronizing the actions of instruction architecture 1500. Also, unit 1510 may include an AC port 1516.

Memory system 1540 may include any suitable number and kind of mechanisms for storing information for the processing needs of instruction architecture 1500. In one embodiment, memory system 1540 may include a load store unit 1546 for storing information such as buffers written to or read back from memory or registers. In another embodiment, memory system 1540 may include a translation lookaside buffer (TLB) 1545 that provides look-up of address values between physical and virtual addresses. In yet another embodiment, memory system 1540 may include a memory management unit (MMU) 1544 for facilitating access to virtual memory. In still yet another embodiment, memory system 1540 may include a prefetcher 1543 for requesting instructions from memory before such instructions are actually needed to be executed, in order to reduce latency.

The operation of instruction architecture 1500 to execute an instruction may be performed through different stages. For example, using unit 1510 instruction prefetch stage 1530 may access an instruction through prefetcher 1543. Instructions retrieved may be stored in instruction cache 1532. Prefetch stage 1530 may enable an option 1531 for fast-loop mode, wherein a series of instructions forming a loop that is small enough to fit within a given cache are executed. In one embodiment, such an execution may be performed without needing to access additional instructions from, for example, instruction cache 1532. Determination of what instructions to prefetch may be made by, for example, branch prediction unit 1535, which may access indications of execution in global history 1536, indications of target addresses 1537, or contents of a return stack 1538 to determine which of branches 1557 of code will be executed next. Such branches may be possibly prefetched as a result. Branches 1557 may be produced through other stages of operation as described below. Instruction prefetch stage 1530 may provide instructions as well as any predictions about future instructions to dual instruction decode stage 1550.

Dual instruction decode stage 1550 may translate a received instruction into microcode-based instructions that may be executed. Dual instruction decode stage 1550 may simultaneously decode two instructions per clock cycle. Furthermore, dual instruction decode stage 1550 may pass its results to register rename stage 1555. In addition, dual instruction decode stage 1550 may determine any resulting branches from its decoding and eventual execution of the microcode. Such results may be input into branches 1557.

Register rename stage 1555 may translate references to virtual registers or other resources into references to physical registers or resources. Register rename stage 1555 may include indications of such mapping in a register pool 1556. Register rename stage 1555 may alter the instructions as received and send the result to issue stage 1560.

Issue stage 1560 may issue or dispatch commands to execution entities 1565. Such issuance may be performed in an out-of-order fashion. In one embodiment, multiple instructions may be held at issue stage 1560 before being executed. Issue stage 1560 may include an instruction queue 1561 for holding such multiple commands. Instructions may be issued by issue stage 1560 to a particular processing entity 1565 based upon any acceptable criteria, such as availability or suitability of resources for execution of a given instruction. In one embodiment, issue stage 1560 may reorder the instructions within instruction queue 1561 such that the first instructions received might not be the first instructions executed. Based upon the ordering of instruction queue 1561, additional branching information may be provided to branches 1557. Issue stage 1560 may pass instructions to executing entities 1565 for execution.

Upon execution, writeback stage 1570 may write data into registers, queues, or other structures of instruction set architecture 1500 to communicate the completion of a given command. Depending upon the order of instructions arranged in issue stage 1560, the operation of writeback stage 1570 may enable additional instructions to be executed. Performance of instruction set architecture 1500 may be monitored or debugged by trace unit 1575.

FIG. 16 is a block diagram of an execution pipeline 1600 for an instruction set architecture of a processor, in accordance with embodiments of the present disclosure. Execution pipeline 1600 may illustrate operation of, for example, instruction architecture 1500 of FIG. 15.

Execution pipeline 1600 may include any suitable combination of steps or operations. In 1605, predictions of the branch that is to be executed next may be made. In one embodiment, such predictions may be based upon previous executions of instructions and the results thereof. In 1610, instructions corresponding to the predicted branch of execution may be loaded into an instruction cache. In 1615, one or more such instructions in the instruction cache may be fetched for execution. In 1620, the instructions that have been fetched may be decoded into microcode or more specific machine language. In one embodiment, multiple instructions may be simultaneously decoded. In 1625, references to registers or other resources within the decoded instructions may be reassigned. For example, references to virtual registers may be replaced with references to corresponding physical registers. In 1630, the instructions may be dispatched to queues for execution. In 1640, the instructions may be executed. Such execution may be performed in any suitable manner. In 1650, the instructions may be issued to a suitable execution entity. The manner in which the instruction is executed may depend upon the specific entity executing the instruction. For example, at 1655, an ALU may perform arithmetic functions. The ALU may utilize a single clock cycle for its operation, as well as two shifters. In one embodiment, two ALUs may be employed, and thus two instructions may be executed at 1655. At 1660, a determination of a resulting branch may be made. A program counter may be used to designate the destination to which the branch will be made. 1660 may be executed within a single clock cycle. At 1665, floating point arithmetic may be performed by one or more FPUs. The floating point operation may require multiple clock cycles to execute, such as two to ten cycles. At 1670, multiplication and division operations may be performed. Such operations may be performed in four clock cycles. At 1675, loading and storing operations to registers or other portions of pipeline 1600 may be performed. The operations may include loading and storing addresses. Such operations may be performed in four clock cycles. At 1680, write-back operations may be performed as required by the resulting operations of 1655-1675.

FIG. 17 is a block diagram of an electronic device 1700 for utilizing a processor 1710, in accordance with embodiments of the present disclosure. Electronic device 1700 may include, for example, a notebook, an ultrabook, a computer, a tower server, a rack server, a blade server, a laptop, a desktop, a tablet, a mobile device, a phone, an embedded computer, or any other suitable electronic device.

Electronic device 1700 may include processor 1710 communicatively coupled to any suitable number or kind of components, peripherals, modules, or devices. Such coupling may be accomplished by any suitable kind of bus or interface, such as I²C bus, system management bus (SMBus), low pin count (LPC) bus, SPI, high definition audio (HDA) bus, Serial Advance Technology Attachment (SATA) bus, USB bus (versions 1, 2, 3), or Universal Asynchronous Receiver/Transmitter (UART) bus.

Such components may include, for example, a display 1724, a touch screen 1725, a touch pad 1730, a near field communications (NFC) unit 1745, a sensor hub 1740, a thermal sensor 1746, an express chipset (EC) 1735, a trusted platform module (TPM) 1738, BIOS/firmware/flash memory 1722, a digital signal processor 1760, a drive 1720 such as a solid state disk (SSD) or a hard disk drive (HDD), a wireless local area network (WLAN) unit 1750, a Bluetooth unit 1752, a wireless wide area network (WWAN) unit 1756, a global positioning system (GPS) 1775, a camera 1754 such as a USB 3.0 camera, or a low power double data rate (LPDDR) memory unit 1715 implemented in, for example, the LPDDR3 standard. These components may each be implemented in any suitable manner.

Furthermore, in various embodiments other components may be communicatively coupled to processor 1710 through the components discussed above. For example, an accelerometer 1741, ambient light sensor (ALS) 1742, compass 1743, and gyroscope 1744 may be communicatively coupled to sensor hub 1740. A thermal sensor 1739, fan 1737, keyboard 1736, and touch pad 1730 may be communicatively coupled to EC 1735. Speakers 1763, headphones 1764, and a microphone 1765 may be communicatively coupled to an audio unit 1762, which may in turn be communicatively coupled to DSP 1760. Audio unit 1762 may include, for example, an audio codec and a class D amplifier. A SIM card 1757 may be communicatively coupled to WWAN unit 1756. Components such as WLAN unit 1750 and Bluetooth unit 1752, as well as WWAN unit 1756 may be implemented in a next generation form factor (NGFF).

Embodiments of the present disclosure involve instructions, a hardware content-associative data structure, and processing logic for accelerating the execution of one or more commonly used set operations. FIG. 18 is an illustration of a system 1800 to accelerate the execution of set operations, in accordance with embodiments of the present disclosure. System 1800 may include a processor, SoC, integrated circuit, or other mechanism. For example, system 1800 may include processor 1804. Although processor 1804 is shown and described as an example in FIG. 18, any suitable mechanism may be used. Processor 1804 may include any suitable mechanisms for accelerating the execution of one or more commonly used set operations. In one embodiment, such mechanisms may be implemented in hardware. Processor 1804 may be implemented fully or in part by the elements described in FIGS. 1-17.

Processor 1804 may include a front end 1806, which may include an instruction fetch pipeline stage (such as instruction fetch unit 1808) and a decode pipeline stage (such as decide unit 1810). Front end 1806 may receive and decode instructions from instruction stream 1802 using decode unit 1810. The decoded instructions may be dispatched, allocated, and scheduled for execution by an allocation stage of a pipeline (such as allocator 1814) and allocated to specific execution units 1816 or to SOLU 1820. One or more specific instructions to be executed by SOLU 1820 may be included in a library defined for execution by processor 1804 or SOLU 1820. In another embodiment, SOLU 1820 may be targeted by portions of processor 1804, wherein processor 1804 recognizes an attempt in instruction stream 1802 to execute a set operation in software and issues one or more of the specific instructions to SOLU 1820.

During execution, access to data or additional instructions (including data or instructions resident in memory system 1830) may be made through memory subsystem 1826. Moreover, results from execution may be stored in memory subsystem 1826 and may subsequently be flushed to memory system 1830. Memory subsystem 1826 may include, for example, memory, RAM, or a cache hierarchy, which may include one or more Level 1 (L1) caches 1827 or Level 2 (L2) caches 1828, some of which may be shared by multiple cores 1812 or processors 1804. After execution by execution units 1816 or by SOLU 1820, instructions may be retired by a writeback stage or retirement stage in retirement unit 1818. Various portions of such execution pipelining may be performed by one or more cores 1812.

Set operations, such as set union and set intersection operations, may be used in application domains such as graph processing and data analytics. Set union and set intersection operations on sorted sets may be common tasks in such application domains. More specifically, many graph operations may include set union operations and set intersection operations that target sets containing ordered lists of key-value pairs. In many cases, the elements in these input sets may be ordered and sorted by their keys. Both set union and set intersection operations may include finding matching indices in the elements of two sets. For example, a set intersection operation may identify key-value pairs in two different sets whose keys match, after which a user-defined reduction operation may be performed on the corresponding values. The set intersection operation may ignore (or discard) any key-value pair in either of the two sets whose key does not match a key of any key-value pair in the other one of the two sets (e.g., key-value pairs in either of the two sets that have unique keys). A set union operation may perform a user-defined reduction operation on the values of any key-value pairs in two different sets whose keys match, but may also retain (unmodified) any key-value pair in either of the two sets whose key does not match a key of any key-value pair in the other one of the two sets (e.g., key-value pairs in either of the two sets that have unique keys). In either of these operations, the output set may include a list of key-value pairs that are ordered and sorted by their keys.

These set union and set intersection operations (as well as other set operations) may be computationally expensive. In some software-based solutions, code for identifying matching indices or for combining two sets using set union operations and/or set intersection operations may simply be executed on typical execution units, as decoded by a decode unit 1810 on a processor 1804. These software-based solution may be slow and/or power hungry. Other approaches may attempt to map these set operations to single instruction multiple data (SIMD) arithmetic operations in order to explore instruction level parallelism. These approaches depend on the ability to identify the matching keys, which may introduce significant cache pressure. Still other approaches may include scatter operations and gather operations, which may also increase cache pressure. In some cases, these approaches may incur relatively high rates of branch mispredictions, which may be incompatible with SIMD.

In embodiments of the present disclosure, system 1800 may include hardware support to accelerate these set operations and thus to speed up processing of modern graph analytics. For example, in one embodiment, system 1800 may include a set operations logic unit (SOLU) that provides key-based associative search functionality. As described in more detail below, the SOLU may include logic and/or circuitry to execute one or more set operations efficiently.

As illustrated in FIG. 18, in one embodiment, system 1800 may include a set operations logic unit (SOLU) 1820 to execute one or more set operations. SOLU 1820 may be implemented in any suitable manner. System 1800 may include an SOLU 1820 in any suitable portion of system 1800. In one embodiment, system 1800 may include SOLU 1820A, which is implemented as a stand-alone circuit in processor 1804. In another embodiment, system 1800 may include SOLU 1820B, which is implemented as a component of one or more cores 1812 or as a component of another element of an execution pipeline in processor 1804. In yet another embodiment, system 1800 may include 1820C, which is implemented in system 1800 and communicatively coupled to processor 1804. SOLU 1820 may be implemented by any suitable combination of circuitry or hardware computational logic, in different embodiments. In one embodiment, SOLU 1820 may accept inputs from other portions of system 1800 and return results of one or more set operations.

In one embodiment, SOLU 1820 may include or may be communicatively coupled to memory elements to store information necessary to perform one or more set operations. For example, SOLU 1820 may include a content-associative data structure (CAM data structure 1824) in which sets of key-value pairs may be stored. In one embodiment, CAM data structure 1824 may be implemented within SOLU 1820. In another embodiment, CAM data structure 1824 may be implemented within any suitable memory within system 1800. In one embodiment, SOLU 1820 may be implemented by circuitry including CAM control logic 1822, which may control access to and perform operations on the contents of CAM data structure 1824. For example, in one embodiment, SOLU 1820 may include circuitry to add a set of key-value pairs to a set of key-value pairs resident in CAM data structure 1824 and to perform a reduction operation on key-value pairs with matching keys. In another embodiment, SOLU 1820 may include circuitry to identify key-value pairs in a set of key-value pairs resident in CAM data structure 1824 whose keys match those of key-value pairs in an input set of key-value pairs. In yet another embodiment, SOLU 1820 may include circuitry to determine and return the current length of CAM data structure 1824 (e.g., the number of valid or active key-value pairs resident in CAM data structure 1824). In another embodiment, SOLU 1820 may include circuitry to reset the contents of CAM data structure 1824. Resetting the contents of CAM data structure 1824 may include deleting or otherwise invalidating any key-value pairs that are resident in CAM data structure 1824 and resetting its length to zero. In one embodiment, SOLU 1820 may include circuitry to move the contents of CAM data structure 1824 to memory (e.g., to one or more output arrays in memory subsystem 1826 and/or memory system 1830).

Processor 1804 may recognize, either implicitly or through decoding and execution of specific instructions, that a set operation is to be performed. In such cases, the performance of the set operation may be offloaded to SOLU 1820. In one embodiment, SOLU 1820 may be targeted by one or more specific instructions in instruction stream 1802. Such specific instructions may be generated by, for example, a compiler, just-in-time interpreter, or other suitable mechanism (which may or may not be included in system 1800), or may be designated by a drafter of code resulting in instruction stream 1802. For example, a compiler may take application code and generate executable code in the form of instruction stream 1802. Instructions may be received by processor 1804 from instruction stream 1802. Instruction stream 1802 may be loaded to processor 1804 in any suitable manner. For example, instructions to be executed by processor 1804 may be loaded from storage, from other machines, or from other memory, such as memory system 1830. The instructions may arrive and be available in resident memory, such as RAM, wherein instructions are fetched from storage to be executed by processor 1804. The instructions may be fetched from resident memory by, for example, a prefetcher or fetch unit (such as instruction fetch unit 1808). Note that instruction stream 1802 may include instructions other than those that perform set operations.

In one embodiment, the specific instructions for performing set operations that target the contents of a content-associative data structure such as CAM data structure 1824 may include an instruction to add a set of key-value pairs to a set of key-value pairs resident in CAM data structure 1824. In one embodiment, the specific instructions for performing set operations that target the contents of CAM data structure 1824 may include an instruction to perform a reduction operation on key-value pairs with matching keys. In another embodiment, the specific instructions for performing set operations that target the contents of CAM data structure 1824 may include an instruction to identify key-value pairs in a set of key-value pairs resident in CAM data structure 1824 whose keys match those of key-value pairs in an input set of key-value pairs. In one embodiment, the specific instructions for performing set operations that target the contents of CAM data structure 1824 may include an instruction to determine and return the current length of CAM data structure 1824. In another embodiment, the specific instructions for performing set operations that target the contents of CAM data structure 1824 may include an instruction to reset the contents of CAM data structure 1824. In yet another embodiment, the specific instructions for performing set operations that target the contents of CAM data structure 1824 may include an instruction to delete or otherwise invalidate any key-value pairs that are resident in CAM data structure 1824 or to reset the length of CAM data structure 1824 to zero. In one embodiment, the specific instructions for performing set operations that target the contents of CAM data structure 1824 may include an instruction to move the contents of CAM data structure 1824 to memory. These instructions may include, for example, “CAMADD”, “CAMINDMATCH”, “CAMSIZE”, “CAMRESET”, and/or “CAMMOVE”, each of which is described in more detail below.

In one embodiment of the present disclosure, a set operations logic unit such as SOLU 1820 may be implemented by dedicated circuitry or logic to accelerate the execution of set operations that are directed to a particular processor 1804. For example, system 1800 may include one SOLU 1820 for multiple cores 1812 within the processor 1804. In this example, each thread of the multiple cores 1812 may access a different portion of a single hardware content-associative data structure, such as CAM data structure 1824. In another embodiment, a set operations logic unit such as SOLU 1820 may be implemented by dedicated circuitry or logic to accelerate the execution of set operations that are directed to a particular core 1812 within a processor 1804. For example, system 1800 may include a dedicated SOLU 1820 for each of multiple cores 1812 within a processor 1804. In this example, each thread of a particular core 1812 may access a different portion of a single CAM data structure 1824 that is shared among the threads. In yet another embodiment, system 1800 may include a dedicated SOLU 1820 (and corresponding CAM data structure 1824) for each of multiple threads of a core 1812 within a processor 1804. In one embodiment, the portion of a shared CAM data structure 1824 that is accessible by each processor 1804, core 1812, or thread thereof for storing and operating on a set of key-value pairs may have a fixed size. In another embodiment, the size of the portion of a shared CAM data structure 1824 that is accessible by each processor 1804, core 1812, or thread thereof for storing and operating on a set of key-value pairs may be dynamically configurable at runtime, based on the workload.

In one embodiment, each thread or core that shares a CAM data structure 1824 with one or more other threads or cores may access a respective set of key-value pairs within the CAM data structure 1824. In one embodiment, the CAM control logic 1822 of the SOLU 1820 for a particular processor 1804, core 1812, or thread thereof may include circuitry or logic to track the sizes of the sets that are stored in the shared CAM data structure 1824 for each thread. In another embodiment, CAM control logic 1822 may include circuitry or logic to generate the correct offsets into the shared CAM data structure 1824 to provide access to the respective portion of the shared CAM data structure 1824 for each thread. In yet another embodiment, system 1800 may include shared CAM control logic 1822 (e.g., a shared CAM processing engine) to which multiple processor 1804, cores 1812, or threads thereof submit requests to perform set operations. In this example, the shared CAM control logic 1822 may access the appropriate CAM data structures 1824 (or portions thereof) to execute the requested set operations on behalf of the requesting processors, cores, or threads.

In one embodiment, CAM data structure 1824 may be communicatively coupled to the memory system 1826, and the results of the execution of set operations by SOLU 1820 may be stored in memory subsystem 1826. In some embodiments, SOLU 1820 may be communicatively coupled directly to memory subsystem 1826 to provide the results of set operations executed by SOLU 1820. For example, the results of the execution of set operations by SOLU 1820 may be written to any suitable cache within the cache hierarchy of memory subsystem 1826, such as an L1 cache 1827 or L2 cache 1828. The results that are written to the cache hierarchy may subsequently be flushed to memory system 1830.

FIG. 19 is an illustration of another example system to accelerate the execution of set operations, in accordance with other embodiments of the present disclosure. Like elements in FIGS. 18 and 19 bear like reference numerals. FIG. 19 illustrates that, in one embodiment of the present disclosure, SOLU 1820A may include CAM control logic 1922A, which may control access to and perform operations on the contents of a CAM data structure 1924A that is implemented by circuitry within memory subsystem 1826, rather than by circuitry within SOLU 1820A. In another embodiment, SOLU 1820C may include CAM control logic 1922B, which may control access to and perform operations on the contents of a CAM data structure 1924B that is implemented by circuitry within memory system 1830, rather than by circuitry within SOLU 1820C. While FIGS. 18 and 19 illustrate multiple suitable locations for SOLU 1820, CAM control logic 1822/1922, and CAM data structure 1824/1924 within systems 1800 and 1900 (or within processors 1804 thereof), these example implementations are merely illustrative and are not meant to be limiting on the implementation of the mechanisms described herein for accelerating set operations.

FIG. 20 is a block diagram illustrating a set operations logic unit (SOLU), in accordance with embodiments of the present disclosure. In this example, set operations logic unit (SOLU) 2010 includes a hardware content-associative data structure (CAM data structure 2030) and CAM control logic 2020 to control access to and perform operations on the contents of CAM data structure 2030. In one embodiment, CAM control logic 2020 may include one or more set operations execution units 2025, each of which include circuitry for executing all or a portion of one or more set operations that target CAM data structure 2030. For example, one or more of set operations execution units 2025 may include circuitry to add a set of key-value pairs to a set of key-value pairs resident in CAM data structure 2030, to perform a reduction operation on key-value pairs with matching keys, to identify key-value pairs in a set of key-value pairs resident in CAM data structure 2030 whose keys match those of key-value pairs in an input set of key-value pairs, to determine and return the current length of CAM data structure 2030, to reset the contents of CAM data structure 2030, to delete or otherwise invalidate any key-value pairs that are resident in CAM data structure 2030, to reset the length of CAM data structure 2030 to zero, or to move the contents of CAM data structure 2030 to memory.

In one embodiment, CAM data structure 2030 may include multiple elements 2031-2036, each of which may store information representing a key-value pair. Each such element may include n bits, a subset of which are used an index into CAM data structure 2030 to access that element, and another subset of which contain a value to be retrieved using that index. For example, element 2031, which is shown in an expanded form in FIG. 20, includes a key in bits (n−1) to (m+1), and a value in bits m to 0. In this example, in order to retrieve the value stored in bits m to 0 within element 2031, the key stored in bits (n−1) to (m+1) may be presented to the hardware content-associative data structure (CAM data structure 2030). The key-value pairs stored in CAM data structure 2030 may be encoded in any suitable key-value format, in different embodiments.

In embodiments of the present disclosure, a system (such as system 1800 or 1900) that includes a set operations logic unit such as SOLU 1820 may support several application programming interfaces (APIs) to perform set operations. These set operations may access and operate on a hardware content-associative data structure, such as CAM data structure 1824 or CAM data structure 1924. In some embodiments, the set operations executed by SOLU 1820 may be performed asynchronously. In such embodiments, other instructions may be executed by execution units 1816 within processor 1804 at the same time. In one embodiment, each of these APIs may be implemented in hardware as an instruction in the instruction set architecture (ISA) of the processor 1804. In one embodiment, each of the set operations may be invoked by a machine language or assembly language instruction that is included a program. In another embodiment, each of the set operations may be invoked by calling a function or method defined in a high level procedural or object oriented programming language. The programming language may be a compiled or interpreted language, in different embodiments.

In one embodiment, each of the APIs that defines a set operation may be implemented by one or more micro-instructions or micro-operations that are executed by processor 1804. For example, decode unit 1810 may receive an instruction representing a set operation that is defined by one of the APIs. Decode unit 1810 may decode the received instruction into one or more micro-instructions or micro-operations, each of which is to be executed by one of the execution units 1816 or by SOLU 1820. Allocator 1814 may receive the micro-instruction(s) or micro-operation(s) from decode unit 1810 and may direct each of them to the appropriate execution unit 1816 or SOLU 1820 in order to perform the requested set operation. In one embodiment, SOLU 1820 may include circuitry or logic to execute a micro-instruction or micro-operation to load data into CAM data structure 1824/1924. In another embodiment, SOLU 1820 may include circuitry or logic to execute a micro-instruction or micro-operation to perform an index matching operation on the keys of key-value pairs of multiple sets of key-value pairs. These and other micro-instructions or micro-operations may be executed in various combinations to perform the set operations defined by the APIs. In one embodiment, two or more of the set operations may be performed by assembly language instructions that share a single opcode. For example, the opcode may indicate that the instruction is to be directed to (and executed by) SOLU 1820. In this example, these assembly language instructions may include multiple control fields whose respective values define the specific set operation to be performed. One of the control fields may indicate the number of iterations performed when executing the instruction. For example, if the instruction is to add a set of key-value pairs to the CAM data structure 1824/1924, one of the control fields may indicate the number of key-value pairs in the input set.

In one embodiment, SOLU 1820 may include circuitry and logic to perform a set operation defined by a “camadd” API. This API may define an instruction to insert a set of key-value pairs into the contents a hardware content-associative data structure, such as CAM data structure 1824 or CAM data structure 1924. In one embodiment, the camadd instruction may be invoked from within a program as illustrated in the following pseudo-code:

camadd ( keys, // a pointer to a source array of keys

values, // a pointer to a source array of values

npairs, // the number of key-value pairs in the source arrays to be

// added to the CAM data structure

op // a reduction operation to be performed on key-value pairs

// that have matching indices/keys, e.g., sum, difference,

min, max

)

In this example, the source of the input set of key-value pairs is a structure that includes one array (a key input array) containing the keys for the input set of key-value pairs and another array (a value input array) containing the values for the input set of key-value pairs. In one embodiment, the instruction defined by the camadd API may operate on the assumption that the keys and corresponding values for the key-value pairs of the input set are ordered and stored in the two source arrays in the same order. For example, the instruction may operate on the assumption that the key stored in the first location in the key input array is the key of a key-value pair whose value stored in the first location in the value input array, the key stored in the second location in the key input array is the key of a key-value pair whose value stored in the second location in the value input array, and so on. In one embodiment, the specified number of key-value pairs to be added to the CAM data structure 1824/1924 may be the same as the number of key-value pairs stored in the source arrays, in which case the full input set of key-value pairs stored in the source arrays may be added to the CAM data structure 1824/1924. In another embodiment, the specified number of key-value pairs to be added to the CAM data structure 1824/1924 may be the less than the number of key-value pairs stored in the source arrays, in which case a subset of the input set of key-value pairs stored in the source arrays may be added to the CAM data structure 1824/1924.

In embodiments of the present disclosure, an instruction defined by the camadd API may be used to perform a set union operation that takes an input set of key-value pairs and adds it to a set of key-value pairs that are already resident in the CAM data structure 1824/1924. In one embodiment, while adding the input set of key-value pairs, the instruction may perform an index matching operation. For example, the instruction may step through the source arrays and the CAM data structure 1824/1924, searching for existing entries in the CAM data structure 1824/1924 whose keys match those of the key-value pairs of the input set of key-value pairs. If an entry with a matching key is found in the CAM data structure 1824/1924, the instruction may apply the specified reduction operation to the value of the entry in the CAM data structure 1824/1924 and the value of the key-value pair of the input set that have the same key. In some embodiments, the specified reduction operation may be an arithmetic operation. In other embodiments, the specified reduction operation may identify a minimum or maximum value. In still other embodiments, more complex reduction operations, including user-defined operations, may he specified for the camadd instruction. The one embodiment, the instruction may replace the value of the key-value pair in the CAM data structure 1824/1924 with the result of the reduction operation. In one embodiment, any key-value pairs in the input set for which no entry having a matching key is found in the CAM data structure 1824/1924 (e.g., any key-value pairs that have unique keys) may be added to the contents of the CAM data structure 1824/1924 as a new entry, thus increasing the used capacity of the CAM data structure 1824/1924 (which may be referred to as its “length”).

FIG. 21 is an illustration of an operation to add a set of key-value pairs to a hardware content-associative data structure, according to embodiments of the present disclosure. In one embodiment, system 1800 may execute an instruction to add a set of key-value pairs to a set of key-value pairs resident in CAM data structure 1824 and to perform a reduction operation on key-value pairs with matching keys. For example, a “CAMADD” instruction may be executed. This instruction may include any suitable number and kind of operands, bits, flags, parameters, or other elements. In one embodiment, a call of CAMADD may reference a first pointer that identifies where the keys for the set of key-value pairs to be added to CAM data structure 1824 are stored. A call of CAMADD may also reference a second pointer that identifies where the values for the set of key-value pairs to be added to CAM data structure 1824 are stored. In another embodiment, a call of CAMADD may reference an integer, which may specify the number of key-value pairs to be added to CAM data structure 1824. In one embodiment, the number of key-value pairs to be added to the CAM data structure 1824 may be equal to the number of key-value pairs that are stored in the identified source arrays. In another embodiment, the number of key-value pairs to be added to the CAM data structure 1824 may be less than the number of key-value pairs that are stored in the identified source arrays.

In one embodiment, a call of CAMADD may include a parameter identifying a reduction operation to be performed when one of the key-value pairs to be added to CAM data structure 1824 has the same key as one of the key-value pairs that is already stored in CAM data structure 1824. The reduction operation may be an arithmetic or aggregation operation. For example, this parameter may specify that a single key-value pair having the common key and a value that represents the sum of the values of the two key-value pairs having the same key should be stored in the output set. In another example, this parameter may specify that a single key-value pair having the common key and a value that represents the signed or unsigned difference between the values of the two key-value pairs having the same key should be stored in the output set. In yet another example, this parameter may specify that a single key-value pair having the common key and a value that represents the minimum value of the values of the two key-value pairs having the same key should be stored in the output set. In another example, this parameter may specify that a single key-value pair having the common key and a value that represents the maximum value of the values of the two key-value pairs having the same key should be stored in the output set. In other embodiments, other reduction operations may be specified and performed when matching keys are identified.

In the example embodiment illustrated in FIG. 21, at (1) the CAMADD instruction and its parameters (which may include any or all of the two pointers described above, the integer specifying the number of key-value pairs to be added, and/or the parameter specifying a reduction operation) may be received from one of the cores 1812 by CAM control logic 1822. For example, the CAMDD instruction may be issued to CAM control logic 1822 within a set operations logic unit 1820 (not shown in FIG. 21) by an allocator 1814 (not shown in FIG. 21) within the core 1812, in one embodiment. CAMADD may be executed logically by CAM control logic 1822.

As illustrated in this example, the set of key-value pairs to be added to CAM data structure 1824 may be stored in two input arrays within memory system 1830. For example, key input array 2102 may store the keys for the set of key-value pairs to be added to CAM data structure 1824. The keys may be sorted according to any of various sorting algorithms and stored in key input array 2102 in their sorted order. Value input array 2104 may store the values for the set of key-value pairs to be added to CAM data structure 1824. The values may be stored in the same order as the order in which the keys to which they correspond are stored. For example, the first entry in value input array 2104 may store the value of a key-value pair whose key is stored in the first entry in key input array 2102, the second entry in value input array 2104 may store the value of a key-value pair whose key is stored in the second entry in key input array 2102, and so on.

Execution of CAMADD by CAM control logic 1822 may include, at (2) reading an input key from a location identified by the first pointer referenced in the instruction call. For example, the first pointer may identify key input array 2102 as the source of the keys for the set of key-value pairs to be added to CAM data structure 1824, and CAM control logic 1822 may read a key from a first entry in key input array 2102. Execution of CAMADD by CAM control logic 1822 may include, at (3) reading an input value from a location identified by the second pointer referenced in the instruction call. For example, the second pointer may identify value input array 2104 as the source of the values for the set of key-value pairs to be added to CAM data structure 1824, and CAM control logic 1822 may read a value from a first entry in value input array 2104.

At (4), CAM control logic 1822 may search CAM data structure 1824 to determine whether a key-value pair stored in CAM structure 1824 has the same key as the one read from key input array 2102 at (2). If so, the entry containing the matching key may be returned to CAM control logic 1822. In one embodiment, this may include returning the value of the key-value pair stored in CAM structure 1824 that has the matching key.

If at (4), a matching key is found and the value of the key-value pair stored in CAM structure 1824 that has the matching key is returned, at (5) CAM control logic 1822 may apply the specified reduction operation to the key-value pairs that share the common key. In this case, at (6), CAM control logic 1822 may replace the key-value pair stored in CAM structure 1824 that has the matching key with a new key-value pair that includes the matching key, and a value that is dependent on the result of the reduction operation. For example, the value may represent the sum of the values of the two key-value pairs that share the common key, the difference between the values of the two key-value pairs that share the common key, the minimum value of the values of the two key-value pairs that share the common key, or the maximum value of the values of the two key-value pairs that share the common key, in different embodiments. Because key-value pairs are stored in a sorted order by their keys in CAM data structure 1824, the new key-value pair may be stored in CAM data structure 1824 in the location at which the key-value pair that had the matching key was previously stored in CAM structure 1824.

If at (4), no entry with a matching key is found in CAM data structure 1824, the reduction operation shown at (5) may be omitted. In this case, at (6), CAM control logic 1822 may store the key obtained from key input array 2102 and the value obtained from value input array 2104 as a new key-value pair entry in CAM data structure 1824. The new key-value pair may be stored in CAM data structure 1824 in a location determined by its key, according to the sorting algorithm used to sort and store all of the key-value pairs in the set of key-value pairs stored in CAM data structure 1824.

In one embodiment, execution of the CAMADD instruction may include repeating any or all of steps of the operation illustrated in FIG. 21 for each of the key-value pairs in the set of key-value pairs to be added to CAM data structure 1824. For example, if the call of CAMADD includes an integer n specifying the number of key-value pairs to be added to CAM data structure 1824, steps (2)-(6) may be performed (as appropriate) n times (once for each of the key-value pairs to be added to CAM data structure 1824). In this example, for each iteration, at (2) and (3) CAM control logic 1822 may read a key from the next entry in key input array 2102 and a value from the next entry in value input array 2104, respectively. CAM control logic 1822 may then perform step (4), step (5) (if appropriate), and step (6) for that input key-value pair, after which the CAMADD instruction may be retired (not shown).

FIG. 22 illustrates an example method 2200 for adding a set of key-value pairs to the contents of a hardware content-associative (CAM) data structure, according to embodiments of the present disclosure. Method 2200 may be implemented by any of the elements shown in FIGS. 1-21. Method 2200 may be initiated by any suitable criteria and may initiate operation at any suitable point. In one embodiment, method 2200 may initiate operation at 2205. Method 2200 may include greater or fewer steps than those illustrated. Moreover, method 2200 may execute its steps in an order different than those illustrated below. Method 2200 may terminate at any suitable step. Moreover, method 2200 may repeat operation at any suitable step. Method 2200 may perform any of its steps in parallel with other steps of method 2200, or in parallel with steps of other methods. Furthermore, method 2200 may be executed multiple times to add multiple sets of key-value pairs to the contents of the hardware content-associative data structure.

At 2205, in one embodiment, an instruction to add a set of key-value pairs to the CAM data structure may be received and decoded. At 2210, the input stream containing the key-value pairs and one or more parameters of the instruction may be directed to a set operations logic unit (SOLU) for execution. In one embodiment, the instruction parameters may include respective pointers to a key input array and a value input array, which collectively store the input set of key-value pairs to be added to the CAM data structure. In this example, the input stream may be obtained from the two source arrays identified by these input parameters. In one embodiment, the instruction parameters may include an integer value indicating the number of key-value pairs in the input set that are to be added to the CAM data structure. In another embodiment, the instruction parameters may include an identifier of a reduction operation to be applied to the values of key-value pairs having matching keys.

At 2215, for a given key-value pair in the input stream, it may be determined whether or not a set of key-value pairs currently stored in the CAM data structure includes a key-value pair with the same key. If it is determined, at step 2220, that a set of key-value pairs currently stored in the CAM data structure includes a key-value pair with the same key, then at step 2225, an operation that is specified in the instruction may be applied to the key-value pairs that have the same key. At 2230, the result of the operation may be stored as a key-value pair in the CAM data structure, and this key-value pair may be indexed in the CAM data structure by the common key.

If it is determined, at step 2220, that the set of key-value pairs currently stored in the CAM data structure does not include a key-value pair with the same key, then at step 2235, the given key-value pair in the input stream may be stored in the CAM data structure, and this key-value pair may be indexed by its key. While there are more key-value pairs in the input stream (as determined at 2240), method 2200 may repeat beginning at 2215 for each additional key-value pair in the input stream. Once there are no additional key-value pairs in the instruction stream, the instruction may be retired at 2245. For example, the instruction may be retired once the number of key-value pairs specified by an input parameter of the instruction has been added to the CAM data structure.

In one embodiment, SOLU 1820 may include circuitry and logic to perform a set operation defined by a “camindmatch” API. This API may define an instruction to perform an index matching operation on an input set of key-value pairs and on the contents of the CAM data structure 1824/1924. In one embodiment, the camindmatch instruction may be invoked from within a program as illustrated in the following pseudo-code:

camindmatch (

inkeys, // a pointer to a source array of keys

invalues, // a pointer to a source array of values

innpairs, // a scalar indicating the number of input key-value pairs

// to be compared to the contents of the CAM data

structure

outkeys, // a pointer to an output array for keys that match keys

// of entries in the CAM data structure

outvalues, // a pointer to an output array for values whose keys

// match keys of entries in the CAM data structure

poutpairs // a scalar indicating the number of output key-value pairs

// (the number of key-value pairs with matching keys)

)

In this example, the source of the input set of key-value pairs is a structure that includes one array (a key input array) containing the keys for the input set of key-value pairs and another array (a value input array) containing the values for the input set of key-value pairs. In one embodiment, the instruction defined by the camindmatch API may operate on the assumption that the keys and corresponding values for the key-value pairs of the input set are ordered and stored in the two source arrays in the same order. For example, the instruction may operate on the assumption that the key stored in the first location in the key input array is the key of a key-value pair whose value stored in the first location in the value input array, the key stored in the second location in the key input array is the key of a key-value pair whose value stored in the second location in the value input array, and so on. In one embodiment, the specified number of key-value pairs whose keys are to be compared to the keys of key-value pairs resident in the CAM data structure 1824/1924 may be the same as the number of key-value pairs stored in the source arrays, in which case the keys of the full input set of key-value pairs stored in the source arrays may be compared to the keys in the contents of CAM data structure 1824/1924. In another embodiment, the specified number of key-value pairs whose keys are to be compared to the keys of key-value pairs resident in the CAM data structure 1824/1924 may be the less than the number of key-value pairs stored in the source arrays, in which case the keys of a subset of the input set of key-value pairs stored in the source arrays may be compared to the keys in the contents of CAM data structure 1824/1924.

In embodiments of the present disclosure, an instruction defined by the camindmatch API may be used to perform a set intersection operation that takes an input set of key-value pairs and compares it to a set of key-value pairs that are already resident in the CAM data structure 1824/1924. In one embodiment, the instruction may operate on the assumption that the CAM data structure stores a set of key-value pairs when the instruction is invoked. In one embodiment, to compare the input set of key-value pairs to the key-value pairs stored in the CAM data structure 1824/1924, the instruction may perform an index matching operation. For example, the instruction may step through the source arrays and the CAM data structure 1824/1924, searching for existing entries in the CAM data structure 1824/1924 whose keys match those of the key-value pairs of the input set of key-value pairs. In one embodiment, if an entry with a matching key is found in the CAM data structure 1824/1924 for a given key-value pair in the input set, the instruction may add the matching key to the output array specified in the instruction for storing matching keys. In another embodiment, if an entry with a matching key is found in the CAM data structure 1824/1924 for a given key-value pair in the input set, the instruction may add the value of the given key-value pair in the input set to the output array specified in the instruction for storing the values of key-value pairs having matching keys. In yet another embodiment, if an entry with a matching key is found in the CAM data structure 1824/1924 for a given key-value pair in the input set, the instruction may increment the value to be output by the instruction indicating the number of matching keys that were found. In one embodiment, if no entry with a matching key is found in the CAM data structure 1824/1924 for a given key-value pair in the input set (e.g., if the given key-value pair has a unique key), the instruction may discard or ignore the given key-value pair.

In one embodiment, as each key-value pair of the input set whose key matches the key of a key-value pair in the CAM data structure 1824/1924 is identified, the matching key may be written to a key output array and then streamed out into the cache hierarchy. For example, the keys may be streamed from the CAM data structure 1824/1924 to an L1 cache 1827 or to an L2 cache 1828 in memory subsystem 1826. In another embodiment, as each key-value pair of the input set whose key matches the key of a key-value pair in the CAM data structure 1824/1924 is identified, the value of the key-value pair of the input set having the matching key may be written to a value output array and then streamed out into the cache hierarchy. For example, the values may be streamed from the CAM data structure 1824/1924 to an L1 cache 1827 or to an L2 cache 1828 in memory subsystem 1826. In one embodiment, each entry of the output set may represent a key-value pair that is to be subsequently inserted into the CAM data structure 1824/1924. For example, following the execution of the camindmatch instruction, the camadd instruction may be invoked to add the key-value pairs in the output set produced by the camindmatch instruction to the CAM data structure 1824/1924.

FIG. 23 is an illustration of an operation to determine whether any of the keys in an input set of key-value pairs match keys in the key-value pairs currently stored in a hardware content-associative (CAM) data structure, in accordance with embodiments of the present disclosure. In one embodiment, system 1800 may execute an instruction to identify key-value pairs in a set of key-value pairs resident in CAM data structure 1824 whose keys match those of key-value pairs in an input set of key-value pairs. For example, a “CAMINDMATCH” instruction may be executed. This instruction may include any suitable number and kind of operands, bits, flags, parameters, or other elements. In one embodiment, a call of CAMINDMATCH may reference a first pointer that identifies where the keys for the input set of key-value pairs are stored. A call of CAMINDMATCH may also reference a second pointer that identifies where the values for the input set of key-value pairs are stored.

In some embodiments, a call of CAMINDMATCH may reference a third pointer that identifies where the keys for any key-value pairs in the input set of key-value pairs whose keys match the keys of key-value pairs stored in CAM data structure 1824 are to be stored. A call of CAMINDMATCH may also reference a fourth pointer that identifies where the values for any key-value pairs in the input set of key-value pairs whose keys match the keys of key-value pairs stored in CAM data structure 1824 are to be stored. In one embodiment, a call of CAMINDMATCH may reference an integer, which may specify the number of key-value pairs in the input set of key-value pairs. In another embodiment, an integer whose value indicates the number of key-value pairs in the input set of key-value pairs whose keys were found to match the keys of key-value pairs stored in CAM data structure 1824 may be returned. In yet another embodiment, a call of CAMINDMATCH may reference a result parameter whose value may, following execution of the CAMINDMATCH instruction, indicate the number of key-value pairs in the input set of key-value pairs whose keys were found to match the keys of key-value pairs stored in CAM data structure 1824.

In the example embodiment illustrated in FIG. 23, at (1) the CAMINDMATCH instruction and its parameters (which may include any or all of the four pointers described above and/or the integer specifying the number of key-value pairs in the input set of key-value pairs) may be received from one of the cores 1812 by CAM control logic 1822. For example, the CAMINDMATCH instruction may be issued to CAM control logic 1822 within a set operations logic unit 1820 (not shown in FIG. 23) by an allocator 1814 (not shown in FIG. 23) within the core 1812, in one embodiment. CAMINDMATCH may be executed logically by CAM control logic 1822.

As illustrated in this example, the input set of key-value pairs may be stored in two input arrays within memory system 1830. For example, key input array 2302 may store the keys for the input set of key-value pairs. The keys may be sorted according to any of various sorting algorithms and stored in key input array 2302 in their sorted order. Value input array 2304 may store the values for the input set of key-value pairs. The values may be stored in the same order as the order in which the keys to which they correspond are stored. For example, the first entry in value input array 2304 may store the value of a key-value pair whose key is stored in the first entry in key input array 2302, the second entry in value input array 2304 may store the value of a key-value pair whose key is stored in the second entry in key input array 2302, and so on.

Execution of CAMINDMATCH by CAM control logic 1822 may include, at (2) reading an input key from a location identified by the first pointer referenced in the instruction call. For example, the first pointer may identify key input array 2302 as the source of the keys for the input set of key-value pairs, and CAM control logic 1822 may read a key from a first entry in key input array 2302. Execution of CAMINDMATCH by CAM control logic 1822 may include, at (3) reading an input value from a location identified by the second pointer referenced in the instruction call. For example, the second pointer may identify value input array 2304 as the source of the values for the input set of key-value pairs, and CAM control logic 1822 may read a value from a first entry in value input array 2304.

At (4), CAM control logic 1822 may search CAM data structure 1824 to determine whether a key-value pair stored in CAM structure 1824 has the same key as the one read from key input array 2302 at (2). If so, the entry containing the matching key may be returned to CAM control logic 1822. In one embodiment, this may include returning the value of the key-value pair stored in CAM structure 1824 that has the matching key.

If at (4), a matching key is found and the value of the key-value pair stored in CAM structure 1824 that has the matching key is returned, at (5) CAM control logic 1822 may increment a count value that indicates the number of key-value pairs in the input set of key-value pairs whose keys were found to match the keys of key-value pairs stored in CAM data structure 1824. For example, in one embodiment, CAM control logic 1822 may increment a counter that is maintained within CAM control logic 1822. In another embodiment, CAM control logic 1822 may increment a counter that is maintained within CAM data structure 1824. In yet another embodiment, CAM control logic 1822 may increment a counter that is maintained within memory subsystem 1826. Subsequently, at (6), CAM control logic 1822 may store the matching key to a location identified by the third pointer referenced in the instruction call. For example, the third pointer may identify key output array 2306 as the location at which matching keys are to be stored, and CAM control logic 1822 may store the input key that was read from key input array 2302 to key output array 2306. In one embodiment, at (7) CAM control logic 1822 may also store the value of the input key-value pair with the matching key to a location identified by the fourth pointer referenced in the instruction call. For example, the fourth pointer may identify value output array 2308 as the location at which values corresponding to matching keys are to be stored, and CAM control logic 1822 may store the input value that was read from value input array 2304 to value output array 2308. If at (4), no entry with a matching key is found in CAM data structure 1824, steps (6) and (7) illustrated in FIG. 23 may be omitted.

In one embodiment, execution of the CAMINDMATCH instruction may include repeating any or all of steps of the operation illustrated in FIG. 23 for each of the key-value pairs in the input set of key-value pairs. For example, if the call of CAMINDMATCH includes an integer n specifying the number of key-value pairs in the input set of key-value pairs, steps (2)-(7) may be performed (as appropriate) n times (once for each of the key-value pairs in the input set of key-value pairs). In this example, for each iteration, at (2) and (3) CAM control logic 1822 may read a key from the next entry in key input array 2302 and a value from the next entry in value input array 2304, respectively. CAM control logic 1822 may then perform step (4), and steps (5), (6), and (7) if appropriate, for that input key-value pair. Once these operations have been performed for each of the key-value pairs in the input set of key-value pairs, at (8) CAM control logic 1822 may return a value indicating the number of key-value pairs in the input set of key-value pairs whose keys were found to match the keys of key-value pairs stored in CAM data structure 1824 to the caller of the CAMINDMATCH instruction (e.g., to the one of the cores 1812 from which the instruction was received), after which the CAMINDMATCH instruction may be retired (not shown) For example, in one embodiment, CAM control logic 1822 may return the value stored in a counter maintained within CAM control logic 1822. In another embodiment, CAM control logic 1822 may return the value stored a counter that is maintained within CAM data structure 1824. In yet another embodiment, CAM control logic 1822 may return the value stored a counter that is maintained within memory subsystem 1826. In still another embodiment, CAM control logic 1822 may write a value indicating the number of key-value pairs having matching keys to a location specified by a parameter of the instruction.

FIG. 24 illustrates an example method 2400 for determining whether any of the keys in an input set of key-value pairs match keys in the key-value pairs currently stored in a hardware content-associative (CAM) data structure, according to embodiments of the present disclosure. Method 2400 may be implemented by any of the elements shown in FIGS. 1-23. Method 2400 may be initiated by any suitable criteria and may initiate operation at any suitable point. In one embodiment, method 2400 may initiate operation at 2405. Method 2400 may include greater or fewer steps than those illustrated. Moreover, method 2400 may execute its steps in an order different than those illustrated below. Method 2400 may terminate at any suitable step. Moreover, method 2400 may repeat operation at any suitable step. Method 2400 may perform any of its steps in parallel with other steps of method 2400, or in parallel with steps of other methods. Furthermore, method 2400 may be executed multiple times to determine whether any of the keys in any other input sets of key-value pairs match keys in the key-value pairs currently stored in the hardware content-associative data structure.

At 2405, in one embodiment, an instruction to identify key-value pairs in the CAM data structure whose keys match the keys of key-value pairs in an input stream may be received and decoded. At 2410, the input stream containing the key-value pairs and one or more parameters of the instruction may be directed to a set operations logic unit (SOLU) for execution. In one embodiment, the instruction parameters may include respective pointers to a key input array and a value input array, which collectively store the input set of key-value pairs. In this example, the input stream may be obtained from the two source arrays identified by these input parameters. In one embodiment, the instruction parameters may include an integer value indicating the number of key-value pairs in the input set that are to be compared to the key-value pairs that are resident in the CAM data structure. In one embodiment, the instruction parameters may include respective pointers to a key output array and a value output array, which are to store the output set of key-value pairs in the input set whose keys are found to match those of key-value pairs that are resident in the CAM data structure. In another embodiment, the instruction parameters may include an identifier of an output parameter whose value indicates the number of key-value pairs in the input set whose keys were found match those of key-value pairs that are resident in the CAM data structure. In yet another embodiment, the instruction parameters may include an identifier of location at which a value indicating the number of key-value pairs in the input set whose keys were found match those of key-value pairs that are resident in the CAM data structure is to be written by the instruction.

At 2415, for a given key-value pair in the input stream, it may be determined whether or not a set of key-value pairs currently stored in the CAM data structure includes a key-value pair with the same key. If it is determined, at step 2420, that a set of key-value pairs currently stored in the CAM includes a key-value pair with the same key, then at step 2425 the key from the given key-value pair may be stored to an output array of matching keys whose location is specified by one of the instruction parameters. At 2430, the value from the given key-value pair may be stored to a second output array whose location is specified by one of the instruction parameters. In addition, at 2435 a count of matching keys may be incremented. For example, in one embodiment, a counter that is maintained within the CAM control logic and whose value reflects the number of matching keys may be incremented. In another embodiment, a counter that is maintained with the CAM data structure and whose value reflects the number of matching keys may be incremented. In yet another embodiment, a counter that is maintained within the memory subsystem and whose value reflects the number of matching keys may be incremented.

If, at step 2420, it is determined that the set of key-value pairs currently stored in the CAM data structure does not include a key-value pair with the same key, then at 2440, no action may be taken for the given key-value pair. While there are more key-value pairs in the input stream (as determined at 2445), method 2400 may repeat beginning at 2415 for each additional key-value pair in the input stream. Once there are no additional key-value pairs in the instruction stream, the instruction may be retired at 2450. For example, the instruction may be retired once the keys for the number of key-value pairs of the input set specified by an input parameter of the instruction has been compared to the keys of the key-value pairs resident in the CAM data structure. While not illustrated in this example, in some embodiments, following the execution of the instruction, the number of matching keys found may be returned to the caller.

In one embodiment, SOLU 1820 may include circuitry and logic to perform a set operation defined by a “camsize” API. This API may define an instruction to obtain the current length of the CAM data structure 1824/1924. In one embodiment, the camsize instruction may be invoked from within a program as illustrated in the following pseudo-code:

camsize ( )

In one embodiment, the camsize instruction may return a value indicating the number of key-value pairs that are currently stored in the CAM data structure to the caller. In another embodiment, the camsize instruction may write a value indicating the number of key-value pairs that are currently stored in the CAM data structure to a location identified by a parameter of the instruction.

FIG. 25 is an illustration of an operation to determine the current length of a hardware content-associative (CAM) data structure, in accordance with embodiments of the present disclosure. In one embodiment, system 1800 may execute an instruction to determine and return the current length of CAM data structure 1824. For example, a “CAMSIZE” instruction may be executed. This instruction may include any suitable number and kind of operands, bits, flags, parameters, or other elements. In one embodiment, a call of CAMSIZE may not include any input parameters, and may return an integer indicating the number of valid or active key-value pairs currently stored in CAM data structure 1824. In another embodiment, a call of CAMSIZE may include a parameter indicating a location at which a value indicating the number of valid or active key-value pairs currently stored in CAM data structure 1824 should be stored following execution of the CAMSIZE instruction (not shown).

In the example embodiment illustrated in FIG. 25, at (1) the CAMSIZE instruction and any instruction parameters may be received from one of the cores 1812 by CAM control logic 1822. For example, the CAMSIZE instruction may be issued to CAM control logic 1822 within a set operations logic unit 1820 (not shown in FIG. 25) by an allocator 1814 (not shown in FIG. 25) within the core 1812, in one embodiment. CAMSIZE may be executed logically by CAM control logic 1822.

Execution of the CAMSIZE instruction by CAM control logic 1822 may include, at (2) accessing CAM data structure 1824 to determine its current length. For example, in one embodiment, CAM control logic 1822 may query a counter maintained within CAM data structure 1824 whose value reflects the number of key-value pairs currently stored in the CAM data structure 1824. In another embodiment, CAM control logic 1822 may maintain a local counter (within CAM control logic 1822) whose value reflects the number of key-value pairs currently stored in the CAM data structure 1824. In one embodiment, CAM control logic 1822 may maintain one or more pointers into CAM data structure 1824 from which the length of the CAM structure 1824 can be calculated. For example, CAM control logic 1822 may maintain one pointer identifying the location of the first active or valid key-value pair stored in the CAM data structure 1824 and another pointer identifying the location of the last active or valid key-value pair stored in the CAM data structure 1824. CAM control logic 1822 may determine the length of the CAM data structure 1824 as a difference between the addresses identified by these pointers. In one embodiment, CAM control logic 1822 may maintain a pointer to the next available empty or unused entry in the CAM data structure 1824. CAM control logic 1822 may determine the length of the CAM data structure 1824 based on the address identified by that pointer.

Once the current length of CAM data structure 1824 has been determined, at (3) CAM control logic 1822 may return the current length of CAM data structure 1824 to the caller of the CAMSIZE instruction (e.g., to the one of the cores 1812 from which it received the instruction), after which the CAMSIZE instruction may be retired (not shown).

FIG. 26 illustrates an example method 2600 for determining the current length of a hardware content-associative (CAM) data structure, according to embodiments of the present disclosure. Method 2600 may be implemented by any of the elements shown in FIGS. 1-25. Method 2600 may be initiated by any suitable criteria and may initiate operation at any suitable point. In one embodiment, method 2600 may initiate operation at 2605. Method 2600 may include greater or fewer steps than those illustrated. Moreover, method 2600 may execute its steps in an order different than those illustrated below. Method 2600 may terminate at any suitable step. Moreover, method 2600 may repeat operation at any suitable step. Method 2600 may perform any of its steps in parallel with other steps of method 2600, or in parallel with steps of other methods. Furthermore, method 2600 may be executed multiple times to determine the current length of the hardware content-associative data structure at different points in time.

At 2605, in one embodiment, an instruction to return the current length of the CAM data structure may be received and decoded. At 2610, the instruction may be directed to a set operations logic unit (SOLU) for execution. At 2615, the number of key-value pairs currently stored in the CAM data structure may be returned. In one embodiment, the CAM control logic may obtain a value indicating the number of key-value pairs currently stored in the CAM data structure from a counter maintained within the CAM control logic. In another embodiment, the CAM control logic may obtain a value indicating the number of key-value pairs currently stored in the CAM data structure from a counter maintained within the CAM data structure. In yet another example, the CAM control logic may calculate the number of key-value pairs currently stored in the CAM data structure based on the addresses identified by one or more pointers into the CAM data structure. At 2620, the instruction may be retired.

In one embodiment, SOLU 1820 may include circuitry and logic to perform a set operation defined by a “camreset” API. This API may define an instruction to reset the contents of the CAM data structure 1824/1924. In one embodiment, the camreset instruction may be invoked from within a program as illustrated in the following pseudo-code:

camreset ( )

In one embodiment, the camreset instruction may be used to delete (or otherwise invalidate) the current contents of the CAM data structure and to reset its length to zero. In one embodiment, execution of the camreset instruction may clear the contents of the CAM data structure. For example, in one embodiment, the instruction may replace the data representing each of the active, valid key-value pairs stored in the CAM data structure with data representing a NULL entry, such as all zeros. In another embodiment, the camreset instruction may not modify the data stored in the CAM data structure. In one embodiment, execution of the camreset instruction may reset a pointer to the next available (empty or unused) entry so that it identifies the first entry within the CAM data structure as an empty or unused entry. Any other suitable mechanism for invalidating the current contents of the CAM data structure may be applied in other embodiments.

In one embodiment, the value of a counter maintained within CAM data structure 1824 may reflect the number of key-value pairs currently stored in the CAM data structure 1824, and the camreset instruction may reset the value of this counter to zero. In another embodiment, CAM control logic 1822 may maintain a local counter whose value reflects the number of key-value pairs currently stored in the CAM data structure 1824, and the camreset instruction may reset the value of this counter to zero. In other embodiments, CAM control logic 1822 may maintain one or more pointers into CAM data structure 1824 from which the length of the CAM structure 1824 can be calculated, and the camreset instruction may modify one or more of these pointers such that the calculated length of the CAM data structure 1824 is zero. For example, by resetting a pointer to the next available empty or unused entry in the CAM data structure 1824 to the first entry of the CAM data structure 1824, CAM control logic 1822 may effectively reset the length of the CAM data structure 1824 to zero.

FIG. 27 is an illustration of an operation to reset the contents of a hardware content-associative (CAM) data structure, in accordance with embodiments of the present disclosure. In one embodiment, system 1800 may execute an instruction to delete or otherwise invalidate any key-value pairs that are resident in CAM data structure 1824 and to reset the length of CAM data structure 1824 to zero. For example, a “CAMRESET” instruction may be executed. This instruction may include any suitable number and kind of operands, bits, flags, parameters, or other elements. In one embodiment, a call of CAMRESET may not include any parameters, and may not return any data to the caller of the CAMRESET instruction. In another embodiment, a call of CAMRESET may include a parameter indicating a location at which a value indicating the status of the operation (e.g., a value indicating success or failure of the operation or a value reflecting the length of CAM data structure 1824 following execution of the CAMRESET instruction) should be stored following execution of the CAMRESET instruction (not shown).

In the example embodiment illustrated in FIG. 27, at (1) the CAMRESET instruction and any instruction parameters may be received from one of the cores 1812 by CAM control logic 1822. For example, the CAMRESET instruction may be issued to CAM control logic 1822 within a set operations logic unit 1820 (not shown in FIG. 27) by an allocator 1814 (not shown in FIG. 27) within the core 1812, in one embodiment. CAMRESET may be executed logically by CAM control logic 1822.

Execution of the CAMRESET instruction by CAM control logic 1822 may include, at (2) accessing CAM data structure 1824 to clear or invalidate its contents. For example, in one embodiment, CAM control logic 1822 may replace the data representing each of the active, valid key-value pairs stored in the CAM data structure 1824 with data representing a NULL entry, such as all zeros. In another embodiment, CAM control logic 1822 may reset a pointer to the next available (empty or unused) entry so that it identifies the first entry within the CAM data structure as an empty or unused entry. Execution of the CAMRESET instruction may also include, at (3) accessing CAM data structure 1824 to reset an indication of the current length of CAM data structure 1824 to zero. For example, in one embodiment, CAM control logic 1822 may reset the value of a counter that is maintained within CAM data structure 1824 and whose value reflects the number of active, valid key-value pairs to zero. In another embodiment, CAM control logic 1822 may modify the value of one or more pointers into the CAM data structure 1824 to effectively reset the length of the CAM data structure 1824 to zero.

Once the contents of CAM data structure 1824 have been cleared or invalidated and the indication of the current length of CAM data structure 1824 has been reset to zero, the CAMRESET instruction may be retired (not shown).

FIG. 28 illustrates an example method 2800 for resetting the contents of a hardware content-associative (CAM) data structure, according to embodiments of the present disclosure. Method 2800 may be implemented by any of the elements shown in FIGS. 1-27. Method 2800 may be initiated by any suitable criteria and may initiate operation at any suitable point. In one embodiment, method 2800 may initiate operation at 2805. Method 2800 may include greater or fewer steps than those illustrated. Moreover, method 2800 may execute its steps in an order different than those illustrated below. Method 2800 may terminate at any suitable step. Moreover, method 2800 may repeat operation at any suitable step. Method 2800 may perform any of its steps in parallel with other steps of method 2800, or in parallel with steps of other methods. Furthermore, method 2800 may be executed multiple times to reset the contents of the hardware content-associative data structure at different points in time.

At 2805, in one embodiment, an instruction to reset the CAM data structure may be received and decoded. At 2810, the instruction may be directed to a set operations logic unit (SOLU) for execution. At 2815, the current contents of the CAM data structure may be deleted or otherwise invalidated. For example, in one embodiment, CAM control logic may replace the data representing each of the active, valid key-value pairs stored in the CAM data structure with data representing a NULL entry, such as all zeros. In another embodiment, CAM control logic may reset a pointer to the next available (empty or unused) entry so that it identifies the first entry within the CAM data structure as an empty or unused entry.

At 2820, an indication of the length of the CAM data structure may be reset to zero. For example, in one embodiment, CAM control logic may reset the value of a counter that is maintained within CAM data structure and whose value reflects the number of active, valid key-value pairs to zero. In another embodiment, CAM control logic may reset the value of a counter that is maintained locally within the CAM control logic and whose value reflects the number of active, valid key-value pairs to zero. In yet another embodiment, CAM control logic may modify the value of one or more pointers into the CAM data structure. In this example, a value representing the length of the CAM data structure that is a subsequently calculated based on the pointer value(s) may be zero. At 2825, the instruction may be retired.

In one embodiment, SOLU 1820 may include circuitry and logic to perform a set operation defined by a “cammove” API. This API may define an instruction to move the contents of the CAM data structure 1824/1924 to memory. In one embodiment, the cammove instruction may be invoked from within a program as illustrated in the following pseudo-code:

cammove ( keys, // a pointer to a destination array in memory for keys

values // a pointer to a destination array in memory for values

)

In this example, the cammove instruction may copy the current contents of the CAM data structure 1824/1924 to locations in memory that are specified by the instruction parameters. In one embodiment, the keys of the key-value pairs currently stored in memory may be written out to a destination array for keys whose location is identified in the instruction parameters by a first pointer. The values of the key-value pairs currently stored in memory may be written out to a destination array for values whose location is identified in the instruction parameters by a second pointer. In one embodiment, the cammove instruction may step through the entries of the CAM data structure 1824/1924, storing the constituent elements of each key-value pair in the two destination arrays. In one embodiment, the instruction defined by the cammove API may operate to store the keys and corresponding values for the key-value pairs currently stored in the CAM data structure 1824/1924 in the same order in the two destination arrays. For example, the key stored in the first location in the key output array may be the key of a key-value pair whose value is stored in the first location in the value output array, the key stored in the second location in the key output array may be the key of a key-value pair whose value is stored in the second location in the value output array, and so on.

In one embodiment, the cammove instruction may copy the entire contents of the CAM data structure to memory, regardless of the number of active, valid key-value pairs stored in the CAM data structure. In another embodiment, the cammove instruction may copy only the active, valid key-value pairs stored in the CAM data structure to memory. For example, CAM control logic may determine the last active, valid entry in the CAM data structure based on the values of one or more pointers maintained in the CAM data structure and may cease copying key-value pairs from the CAM data structure 1824/1924 to memory after copying the last active, valid key-value pair to memory. In another example, CAM control logic may determine the last active, valid entry in the CAM data structure 1824/1924 based on the values of one or more pointers maintained locally in the CAM control logic 1822 and may cease copying key-value pairs from the CAM data structure 1824/1924 to memory after copying the last active, valid key-value pair to memory. In one embodiment, CAM control logic 1822 may determine the number of active, valid entries in the CAM data structure 1824/1924 and may cease copying key-value pairs from the CAM data structure 1824/1924 to memory after copying that number of key-value pairs to memory. For example, CAM control logic 1822 may access a counter that is maintained within CAM data structure 1824/1924 and whose value reflects the number of active, valid key-value pairs. In another embodiment, CAM control logic 1822 may maintain a counter locally (within the CAM control logic 1822) whose value reflects the number of active, valid key-value pairs. In some embodiments, it may be the responsibility of the programmer to ensure that the destination arrays specified for the key-value pairs to be copied from CAM data structure 1824 are large enough to hold the key-value pairs that are to be copied from CAM data structure 1824.

FIG. 29 is an illustration of an operation to move the contents of a hardware content-associative data structure (CAM) to memory, in accordance with embodiments of the present disclosure. In one embodiment, system 1800 may execute an instruction to move the contents of CAM data structure 1824 to locations in memory system 1830. For example, a “CAMMOVE” instruction may be executed. This instruction may include any suitable number and kind of operands, bits, flags, parameters, or other elements. In one embodiment, a call of CAMMOVE may reference a first pointer that identifies a location in memory at which the keys for the set of key-value pairs in CAM data structure 1824 are to be stored. A call of CAMMOVE may also reference a second pointer that identifies a location in memory at which the values for the set of key-value pairs in CAM data structure 1824 are to be stored.

In the example embodiment illustrated in FIG. 29, at (1) the CAMMOVE instruction and its parameters (which may include the two pointers described above) may be received from one of the cores 1812 by CAM control logic 1822. For example, the CAMMOVE instruction may be issued to CAM control logic 1822 within a set operations logic unit 1820 (not shown in FIG. 29) by an allocator 1814 (not shown in FIG. 29) within the core 1812, in one embodiment. CAMMOVE may be executed logically by CAM control logic 1822.

In one embodiment, each key-value pair in the set of key-value pairs may be stored in CAM data structure 1824 as an entry that includes both a key and a value. The key-value pairs may be sorted based on their keys according to any of various sorting algorithms and stored in CAM data structure 1824 in their sorted order.

Execution of the CAMMOVE instruction by CAM control logic 1822 may include, at (2) retrieving a first key-value pair from CAM data structure 1824 that includes a given key. Execution of the CAMMOVE instruction may include, at (3), CAM control logic 1822 storing the given key to a location identified by the first pointer referenced in the instruction call. For example, the first pointer may identify key output array 2902 as the location at which the keys for the set of key-value pairs in CAM data structure 1824 are to be stored, and CAM control logic 1822 may store the given key to a first entry in key output array 2902. Execution of CAMMOVE by CAM control logic 1822 may include, at (4) storing the value of the first key-value pair (the value of the key-value pair containing the given key) to a location identified by the second pointer referenced in the instruction call. For example, the second pointer may identify value output array 2904 as the location at which the values for the set of key-value pairs in CAM data structure 1824 are to be stored, and CAM control logic 1822 may store the value of the key-value pair containing the given key to a first entry in value output array 2904.

In one embodiment, execution of the CAMMOVE instruction may include repeating any or all of steps of the operation illustrated in FIG. 29 for each of the key-value pairs in CAM data structure 1824. For example, if CAM data structure 1824 has a length of n, steps (3) and (4) may be performed (as appropriate) n times (once for each of the key-value pairs in CAM data structure 1824). In this example, for each iteration, at (2) CAM control logic 1822 may retrieve a key-value pair from the next entry in CAM data structure 1824. CAM control logic 1822 may then perform steps (3) and (4) to store that key-value pair in successive entries in key output array 2902 and value output array 2904 within memory system 1830. Once these operations have been performed for each of the key-value pairs in the set of key-value pairs in CAM data structure 1824, the CAMMOVE instruction may be retired (not shown). In one embodiment, execution of the CAMMOVE instruction may include determining the number of active, valid key-value pairs that are stored within CAM data structure 1824 and that are to be moved to the specified destination arrays in memory system 1830. The number of active, valid key-value pairs that are stored within CAM data structure 1824 and that are to be moved to the specified destination arrays in memory system 1830 may be determined using any suitable method include, but not limited to, those described above.

In one embodiment, the CAMMOVE instruction may store the keys and corresponding values for the key-value pairs currently stored in the CAM data structure 1824 in the same order in the two destination arrays. For example, the key stored in the first location in the key output array 2902 may be the key of a key-value pair whose value is stored in the first location in the value output array 2904, the key stored in the second location in the key output array 2902 may be the key of a key-value pair whose value is stored in the second location in the value output array 2904, and so on.

FIG. 30 illustrates an example method 3000 for moving the contents of a hardware content-associative (CAM) data structure to memory, according to embodiments of the present disclosure. Method 3000 may be implemented by any of the elements shown in FIGS. 1-29. Method 3000 may be initiated by any suitable criteria and may initiate operation at any suitable point. In one embodiment, method 3000 may initiate operation at 3005. Method 3000 may include greater or fewer steps than those illustrated. Moreover, method 3000 may execute its steps in an order different than those illustrated below. Method 3000 may terminate at any suitable step. Moreover, method 3000 may repeat operation at any suitable step. Method 3000 may perform any of its steps in parallel with other steps of method 3000, or in parallel with steps of other methods. Furthermore, method 3000 may be executed multiple times to move the contents of the hardware content-associative data structure to memory, at different points in time.

At 3005, in one embodiment, an instruction to move the contents of the CAM data structure to multiple output arrays in memory may be received and decoded. At 3010, the instruction and one or more parameters of the instruction may be directed to a set operations logic unit (SOLU) for execution. In one embodiment, the instruction parameters may include respective pointers to a key output array and a value output array, which are to store the output set of the key-value pairs that are moved from the CAM data structure to memory.

At 3015, for a given key-value pair in the CAM data structure, the key from the given key-value pair may be stored to a first output array. The first output array, whose location may be specified in the instruction parameters, may store the keys of the key-value pairs that were stored in the CAM data structure. Similarly, at 3020, for the given key-value pair in the CAM, the value from the given key-value pair may be stored to a second output array. The second output array, whose location may be specified in the instruction parameters, may store the values of the key-value pairs that were stored in the CAM data structure. While there are more key-value pairs currently stored in the CAM data structure (as determined at 3025), method 3000 may repeat beginning at 3015 for each additional key-value pair in the CAM data structure that is to be moved to memory. Once there are no additional key-value pairs in the CAM data structure, the instruction may be retired at 3030.

In one embodiment, SOLU 1820 may include circuitry and logic to perform an additional set operation that has the opposite effect of that of the cammove operation. For example, in one embodiment, SOLU 1820 may include circuitry and logic to perform a set operation defined by a “camload” API. This API may define an instruction to load an input set of key-value pairs that are stored in two source arrays into an empty CAM data structure 1824/1924. In one embodiment, the instruction parameters for this instruction may include a pointer to a key input array and a pointer to a value input array, which collectively store a set of key-value pairs. In one embodiment, the instruction defined by the camload API may operate on the assumption that the keys and corresponding values for the key-value pairs of the input set are ordered and stored in the two source arrays in the same order. For example, the instruction may operate on the assumption that the key stored in the first location in the key input array is the key of a key-value pair whose value stored in the first location in the value input array, the key stored in the second location in the key input array is the key of a key-value pair whose value stored in the second location in the value input array, and so on. In one embodiment, the instruction may operate on the assumption that the CAM data structure 1824/1924 is empty (i.e. that it does not contain any active, valid key-value pairs). The instruction may overwrite any data stored in the CAM data structure 1824/1924. The instruction may reset the length of the CAM data structure 1824/1924 to be equal to the number of key-values pairs that it loads from the source arrays into the CAM data structure 1824/1924.

The instruction parameters may also include an indication of the number of key-value pairs to be loaded from the specified source arrays into the CAM data structure 1824/1924. In one embodiment, the specified number of key-value pairs to be added to the CAM data structure 1824/1924 may be the same as the number of key-value pairs stored in the source arrays, in which case the full input set of key-value pairs stored in the source arrays may be added to the CAM data structure 1824/1924. In another embodiment, the specified number of key-value pairs to be added to the CAM data structure 1824/1924 may be the less than the number of key-value pairs stored in the source arrays, in which case a subset of the input set of key-value pairs stored in the source arrays may be added to the CAM data structure 1824/1924. In one embodiment, the camload instruction may step through the entries of the two source arrays to obtain the constituent elements of each key-value pair. The camload instruction may store the key and value obtained from corresponding entries in the two source arrays as a key-value pair in the CAM data structure 1824/1924.

In one embodiment, the functionality of the camload instruction described above may be implemented using a combination of the camreset and camadd instructions described earlier. For example, the camreset instruction may be called to reset the contents of the CAM data structure 1824/1924, after which the camadd instruction may be called to add an input set of key-value pairs into the (now empty) CAM data structure 1824/1924. In this example, because the CAM data structure was reset prior to adding the input set of key-value pairs into the CAM data structure 1824/1924, there will be no matching keys found in the CAM data structure 1824/1924. Thus, all of the key-value pairs of the input set may be inserted into the CAM data structure 1824/1924 without modification, and these key-value pairs will be the only key-value pairs stored in the CAM data structure 1824/1924 following the execution of the camadd instruction. In another example, if it is know that the CAM data structure 1824/1924 is empty, an input set of key-value pairs may be loaded into the CAM data structure 1824/1924 using the camadd instruction without first executing the camreset instruction. For example, an initial load of the CAM data structure may be performed using the camadd instruction.

The instructions and processing logic described herein for accelerating the execution of set operations may be applied to improve the performance of a system 1800 when executing a variety of big data analytics applications (including, but not limited to, graph processing applications) when compared to systems that do not include a set operations logic unit (SOLU). The use of the instructions and processing logic described herein for accelerating the execution of set operations may also simplify the programs that perform set operations, when compared to systems that do not include a set operations logic unit (SOLU). For example, a sparse matrix-sparse vector multiplication routine that is used to implement many graph algorithms typically includes both set union and set intersection operations that may be accelerated using the set operations logic unit (SOLU) described herein. This and other graph processing routines may commonly operate on a set data structure similar to that illustrated in the following pseudo-code:

typedef struct

{

int *keys; // keys

T *values; // values of user-defined datatype T

int size; // set size

} Set;

An example of a set union routine that operates on sorted input sets having this Set structure may be invoked as follows:

C[i, :]=Union(A[i, :], B[k, :], ‘+’);

In this example, the Union routine takes as parameters: a first input Set structure, a second input Set structure, an output Set structure, and a user-defined reduction function for determining the values of the entries in the output set as a function of the values of the entries in the two input sets for any entries that have matching keys. One example of the code for the Union routine in a system that does not include a set operations logic unit is illustrated by the following pseudo-code:

while (i_a < A.size && i_b < B.size {

if (A.keys[i_a] < B.keys[i_b]) {

C.keys[i_c] = A.keys[i_a];

C.values[i_c] = A.values[i_a];

i_a++;

i_c++;

}

else if (A.keys[i_a] >= B.keys[i_b] {

C.keys[i_c] = B.keys[i_b];

if (A.keys[i_a] = = B.keys[i_b]) {

// duplicate reduction

C.values[i_c] = UserFunc(A.values[i_a],

B.values [i_b]);

i_a++;

}

else

C.values[i_c] = B.values[i_b];

i_b++;

i_c++;

}

}

In one example, in order to perform a sequence of set unions in a system that does not include a set operations logic unit (SOLU), which may be common in some graph processing applications, the Union routine shown above may be called repeatedly, as follows:

for(...) {

C[i, :] = Union(C[i, :], B[k, :], ‘+’);

}

In this example, prior to the execution of the Union operation, the structure Set C contains one of the input sets for the operation. After execution of the Union operation, the structure Set C contains the output set, which is the union of the two input sets, C and B.

In embodiments of the present disclosure, the execution of a similar sequence of set union operations (one that operates on one row of a set at a time) may be invoked as illustrated in the following example pseudo-code:

camreset( );

for(...) {

start = B.rowPointer[k];

npairs = B.rowPointer[k+1] − start;

camadd(&B.columnIndex[start], &B.values[start], npairs, ‘+’);

}

start = C.rowPointer[i];

cammove(&C.columnIndex[start], &C.values[start]);

One example of the code for an Intersection routine in a system that does not include a set operations logic unit is illustrated by the following pseudo-code:

while (i_a < A.size && i_b < B.size) {

if (A.keys[i_a] = = B.keys[i_b]) {

C.keys[i_c] = A.keys[i_a];

C.values[i_c] = UserFunc(A.values[i_a], B.values [i_b]);

i_c++;

i_a++;

i_b++;

}

else if (A.keys[i_a] > B.keys[i_b] {

i_b++;

else

i_a++;

}

In this example, the Intersection routine takes as parameters: a first input Set structure, a second input Set structure, an output Set structure, and a user-defined reduction function for determining the values of the entries in the output set as a function of the values of the entries in the two input sets that have matching keys.

In embodiments of the present disclosure (i.e. in a system that includes a set operations logic unit, or SOLU), the execution of a set intersection operation may be invoked as illustrated in the following example pseudo-code:

int i1 = 0, i2 = 0;

sout = { } ; // empty set

camadd(s1[i1 : i1 + simdw]);

while(i1 + simdw < s1.size( ) && i2 + simdw < s2.size( )) {

sout = sout + camindmatch(s2[i2 : i2 + simdw]);

if(s1.key[i1] > s2.key[i2]) i2 += simdw;

else {

i1 += simdw;

camreset( );

camadd(s1[i1 : i1 + simdw]);

}

}

In this example, the pseudo-code includes a dependency on the SIMD width of the underlying processor architecture (shown as “simdw”).

In embodiments of the present disclosure, the size of the CAM data structure may affect the complexity of the CAM control logic within the SOLU and/or the complexity of an application that invokes the accelerated set operations supported by the SOLU. For example, if the CAM data structure is not large enough to accommodate all of the sets of key-value pairs that are input to a set union operation, or a useful subset of the sets of key-value pairs, the application may partition the sets at a finer granularity than if all of the sets of key-value pairs that are input to a set union operation or a useful subset of the sets of key-value pairs can be accommodated in the CAM data structure. Similarly, if the CAM data structure is not large enough to accommodate one of the sets of key-value pairs that are input to a set intersection operation, or a useful subset of the sets of key-value pairs, the application may partition the sets at a finer granularity than if any one of the sets of key-value pairs that are input to a set intersection operation or a useful subset of the sets of key-value pairs can be accommodated in the CAM data structure. Graph processing applications that aggregate multiple sets in order to produce a single output row of the output set may place particularly strenuous demands on the CAM data structure size. For these types of applications, a CAM data structure size that can accommodate at least one entire output row of the output set may be sufficiently large to achieve the acceleration of the application.

In embodiments of the present disclosure, the CAM data structure may be sized to accommodate a particular big data analytics application or a particular class of big data analytics applications. In one embodiment, a CAM data structure that can accommodate a few thousand key-value pairs and that supports an access rate of one element every two cycles may be sufficient for accelerating set operations for a wide variety of graph processing applications. In other embodiments, a CAM data structure that accommodates more or fewer key-value pairs may be sufficient for accelerating set operations for other types or classes of big data analytics applications.

In one embodiment, during execution of a big data analytics application, the system may determine whether or not to direct set operations that are supported by the SOLU to the SOLU for execution, dependent on whether a useful subset of the input and/or output sets can be accommodated by the particular CAM data structure in the system. In one embodiment, the system may estimate the CAM data structure requirements of a given set operation (the size demand on the CAM data structure) at runtime, and may selectively direct set operations to the SOLU or to a conventional execution unit for execution dependent on the estimated requirements.

FIG. 31 illustrates an example method 3100 for selectively executing a set operation using a hardware content-associative (CAM) data structure, according to embodiments of the present disclosure. Method 3100 may be implemented by any of the elements shown in FIGS. 1-30. Method 3100 may be initiated by any suitable criteria and may initiate operation at any suitable point. In one embodiment, method 3100 may initiate operation at 3105. Method 3100 may include greater or fewer steps than those illustrated. Moreover, method 3100 may execute its steps in an order different than those illustrated below. Method 3100 may terminate at any suitable step. Moreover, method 3100 may repeat operation at any suitable step. Method 3100 may perform any of its steps in parallel with other steps of method 3100, or in parallel with steps of other methods. Furthermore, method 3100 may be executed multiple times to selectively execute one or more set operations using the hardware content-associative data structure.

At 3105, in one embodiment, an instruction for selectively executing a set operation using the CAM data structure may be received and decoded. At 3105 execution of an instruction stream including one or more set operations may begin. At 3110, for a given one of the set operations, the size requirements of the output set for the set operation may be estimated. At 3115, if the results of the estimation indicate that one or more useful subsets of the output set will fit in the CAM data structure, then at 3125 a CAM-specific instruction (and its parameters) may be directed to the set operations logic unit for execution of the set operation. In one embodiment, the CAM-specific instruction may be directed to the set operations logic unit only if it is estimated that the entire output set can be accommodated in the CAM data structure at once. In another embodiment, the CAM-specific instruction may be directed to the set operations logic unit if it is estimated that a full row of the output set can be accommodated in the CAM data structure. The full row of the output set may be flushed to one of the caches in the cache hierarchy immediately after it is produced, allowing room for the next full row of the output set to be assembled in the CAM data structure.

If, however, at 3115 the results of the estimation indicate that no useful subsets of the output set will fit in the CAM data structure, then at 3120 one or more instructions and their respective parameters may be directed to a general-purpose execution unit for execution of the set operation. In either case, at 3130, if it is determined that the next operation is a set operation, method 3100 may be repeated, beginning at 3110, for the next operation. While there are more instructions in the instruction stream (as determined at step 3135), method 3100 may be repeated, beginning at 3110, for each additional set operation that is encountered in the instruction stream. Once there are no additional instructions in the instruction stream (as determined at step 3135), the method may terminate.

In embodiments of the present disclosure, the use of the hardware content-associative data structures described herein may eliminate substantial amounts of data and control overhead that are inherent when executing big data analytics applications in existing systems. The use of the hardware content-associative data structures described herein may also reduce the cache pressure that is inherent when executing big data analytics applications in existing systems. For example, even with CAM data structure access rates of 0.5 cycles per access, performance gains of between 1.5× to 3.2× have been observed for graph analytics applications, when compared to implementations that were optimized for execution in systems that do not include these hardware content-associative data structures.

Embodiments of the mechanisms disclosed herein may be implemented in hardware, software, firmware, or a combination of such implementation approaches. Embodiments of the disclosure may be implemented as computer programs or program code executing on programmable systems comprising at least one processor, a storage system (including volatile and non-volatile memory and/or storage elements), at least one input device, and at least one output device.

Program code may be applied to input instructions to perform the functions described herein and generate output information. The output information may be applied to one or more output devices, in known fashion. For purposes of this application, a processing system may include any system that has a processor, such as, for example; a digital signal processor (DSP), a microcontroller, an application specific integrated circuit (ASIC), or a microprocessor.

The program code may be implemented in a high level procedural or object oriented programming language to communicate with a processing system. The program code may also be implemented in assembly or machine language, if desired. In fact, the mechanisms described herein are not limited in scope to any particular programming language. In any case, the language may be a compiled or interpreted language.

One or more aspects of at least one embodiment may be implemented by representative instructions stored on a machine-readable medium which represents various logic within the processor, which when read by a machine causes the machine to fabricate logic to perform the techniques described herein. Such representations, known as “IP cores” may be stored on a tangible, machine-readable medium and supplied to various customers or manufacturing facilities to load into the fabrication machines that actually make the logic or processor.

Such machine-readable storage media may include, without limitation, non-transitory, tangible arrangements of articles manufactured or formed by a machine or device, including storage media such as hard disks, any other type of disk including floppy disks, optical disks, compact disk read-only memories (CD-ROMs), compact disk rewritables (CD-RWs), and magneto-optical disks, semiconductor devices such as read-only memories (ROMs), random access memories (RAMs) such as dynamic random access memories (DRAMs), static random access memories (SRAMs), erasable programmable read-only memories (EPROMs), flash memories, electrically erasable programmable read-only memories (EEPROMs), magnetic or optical cards, or any other type of media suitable for storing electronic instructions.

Accordingly, embodiments of the disclosure may also include non-transitory, tangible machine-readable media containing instructions or containing design data, such as Hardware Description Language (HDL), which defines structures, circuits, apparatuses, processors and/or system features described herein. Such embodiments may also be referred to as program products.

In some cases, an instruction converter may be used to convert an instruction from a source instruction set to a target instruction set. For example, the instruction converter may translate (e.g., using static binary translation, dynamic binary translation including dynamic compilation), morph, emulate, or otherwise convert an instruction to one or more other instructions to be processed by the core. The instruction converter may be implemented in software, hardware, firmware, or a combination thereof. The instruction converter may be on processor, off processor, or part-on and part-off processor.

Thus, techniques for performing one or more instructions according to at least one embodiment are disclosed. While certain exemplary embodiments have been described and shown in the accompanying drawings, it is to be understood that such embodiments are merely illustrative of and not restrictive on other embodiments, and that such embodiments not be limited to the specific constructions and arrangements shown and described, since various other modifications may occur to those ordinarily skilled in the art upon studying this disclosure. In an area of technology such as this, where growth is fast and further advancements are not easily foreseen, the disclosed embodiments may be readily modifiable in arrangement and detail as facilitated by enabling technological advancements without departing from the principles of the present disclosure or the scope of the accompanying claims.

Some embodiments of the present disclosure include a processor. In at least some of these embodiments, the processor may include a front end to decode at least one instruction, an allocator to pass the instruction to a set operations logic unit to execute the instruction, and a retirement unit to retire the instruction. To execute the instruction, the set operations logic unit may include a content-associative memory, a first logic to store a first set of key-value pairs in the content-associative memory, a second logic to obtain input to represent a second set of key-value pairs from one or more input locations identified in the instruction, and a third logic to identify key-value pairs in the second set of key-value pairs whose keys match a key in a key-value pair in the first set of key-value pairs. In any of the above embodiments, the second set of key-value pairs may be an ordered set of key-value pairs in which the key-value pairs are sorted dependent on their respective keys. In any of the above embodiments, keys for the second set of key-value pairs may be stored in a first input location identified in the instruction, values for the second set of key-value pairs may be stored in a second input location identified in the instruction. In combination with any of the above embodiments, the set operations logic unit may include a fourth logic to receive the input to represent the second set of key-value pairs as streamed inputs from the first input location and the second input location. In combination with any of the above embodiments, the set operations logic unit may include a fourth logic to store, as a result of the identification, keys of the key-value pairs in the second set of key-value pairs whose keys match a key in a key-value pair in the first set of key-value pairs to a first output location identified in the instruction, and a fifth logic to store, as a result of the identification, values of the key-value pairs in the second set of key-value pairs whose keys match a key in a key-value pair in the first set of key-value pairs to a second output location identified in the instruction. In combination with any of the above embodiments, the set operations logic unit may include a fourth logic to store, as a result of the identification, data to represent a number of key-value pairs in the second set of key-value pairs whose keys match a key in a key-value pair in the first set of key-value pairs to an output location identified in the instruction. In combination with any of the above embodiments, the set operations logic unit may include a fourth logic to receive the instruction to be executed by the set operations logic unit. In combination with any of the above embodiments, the set operations logic unit may include a fifth logic to produce a result of the identification. The result may include a collection of matching keys, a collection of values for key-value pairs in the second set of key-value pairs with matching keys, or an indication of a number of matching keys. In combination with any of the above embodiments, the set operations logic unit may include a fourth logic to apply an arithmetic or aggregate operation specified in the instruction to a value in each key-value pair in the second set of key-value pairs whose key matches a key in a key-value pair in the first set of key-value pairs and a value in the key-value pair in the first set of key-value pairs with the matching key to obtain a result value for each matching key. In combination with any of the above embodiments, the set operations logic unit may include a fifth logic to create third set of key-value pairs that includes a respective key-value pair for each matching key that contains the result value for the matching key and a respective key-value pair for each key-value pair in the first set of key-value pairs and each key-value pair in the second set of key-value pairs that have unique keys, and a sixth logic to store the third set of key-value pairs in the content-associative memory. In combination with any of the above embodiments, the set operations logic unit may include a fourth logic to determine the length of the content-associative memory, where the length may represent the number of key-value pairs stored in the content-associative memory, and a fifth logic to return an indication of the length of the content-associative memory. In combination with any of the above embodiments, the set operations logic unit may include a fourth logic to delete or invalidate the contents of the content-associative memory, and a fifth logic to reset an indicator of length for the content-associative memory to zero, where the length may represent the number of key-value pairs stored in the content-associative memory. In combination with any of the above embodiments, the set operations logic unit may include a fourth logic to move keys of key-value pairs stored in the content-associative memory to a first output location specified in the instruction, and a fifth logic to move values of key-value pairs stored in the content-associative memory to a second output location specified in the instruction. In any of the above embodiments, the set operations logic unit may be one of a plurality of set operations logic units in a processor, and the set operations logic unit may include a sixth logic to receive instructions to be executed by the set operations logic unit from a particular one of a plurality of processor cores in the processor. In combination with any of the above embodiments, the set operations logic unit may include a sixth logic to receive instructions to be executed by the set operations logic unit from a plurality of processor cores or hardware threads of a processor.

Some embodiments of the present disclosure include a method. In at least some of these embodiments, the method may include receiving a first instruction, decoding the first instruction, passing the first instruction to a set operations logic unit to execute the first instruction, and retiring the first instruction. Executing the first instruction may include accessing a first set of key-value pairs stored in a content-associative memory, receiving a second set of key-value pairs from one or more input locations identified in the first instruction, determining, for each key-value pair in the second set of key-value pairs, whether or not its key matches a key in a key-value pair in the first set of key-value pairs, and storing, to an output location identified in the first instruction, a result of the determination. In any of the above embodiments, the result of the determination may include the keys in the key-value pairs in the second set of key-value pairs that are determined to match keys in key-value pairs in the first set of key-value pairs, the values in the key-value pairs in the second set of key-value pairs whose keys are determined to match keys in key-value pairs in the first set of key-value pairs, or the number of keys in the key-value pairs in the second set of key-value pairs that are determined to match keys in key-value pairs in the first set of key-value pairs. In combination with any of the above embodiments, the method may include storing, as a result of the identification, keys of the key-value pairs in the second set of key-value pairs whose keys match a key in a key-value pair in the first set of key-value pairs to a first output location identified in the first instruction, and storing, as a result of the determination, values of the key-value pairs in the second set of key-value pairs whose keys match a key in a key-value pair in the first set of key-value pairs to a second output location identified in the first instruction. In combination with any of the above embodiments, the method may include storing, as a result of the determination, data representing the number of key-value pairs in the second set of key-value pairs whose keys match a key in a key-value pair in the first set of key-value pairs to an output location identified in the first instruction. In any of the above embodiments, executing the first instruction may include applying an operation specified in the first instruction to a value in each key-value pair in the second set of key-value pairs whose key matches a key in a key-value pair in the first set of key-value pairs and a value in the key-value pair in the first set of key-value pairs with the matching key to obtain a result value for each matching key, creating a third set of key-value pairs that includes a respective key-value pair for each matching key that contains the result value for the matching key and a respective key-value pair for each key-value pair in the first set of key-value pairs and each key-value pair in the second set of key-value pairs that have unique keys, and storing the third set of key-value pairs in the content-associative memory. In any of the above embodiments, the second set of key-value pairs may be an ordered set of key-value pairs in which the key-value pairs are sorted dependent on their respective keys. In any of the above embodiments, keys for the second set of key-value pairs may be stored in a first input location identified in the first instruction, values for the second set of key-value pairs may be stored in a second input location identified in the first instruction, and the method may include receiving the input representing the second set of key-value pairs as streamed inputs from the first input location and the second input location. In combination with any of the above embodiments, the method may include receiving a second instruction, decoding the second instruction, passing the second instruction to the set operations logic unit to execute the second instruction, and retiring the second instruction. Executing the second instruction may include determining the length of the content-associative memory, where the length represents the number of key-value pairs stored in the content-associative memory, and returning an indication of the length of the content-associative memory. In combination with any of the above embodiments, the method may include receiving a second instruction, decoding the second instruction, passing the second instruction to the set operations logic unit to execute the second instruction, and retiring the second instruction. Executing the second instruction may include deleting or invalidating the contents of the content-associative memory, and resetting an indicator of length for the content-associative memory to zero, where the length represents the number of key-value pairs stored in the content-associative memory. In combination with any of the above embodiments, the method may include receiving a second instruction, decoding the second instruction, passing the second instruction to the set operations logic unit to execute the second instruction, and retiring the second instruction. Executing the second instruction may include storing keys of key-value pairs stored in the content-associative memory to a first output location specified in the second instruction, and storing values of key-value pairs stored in the content-associative memory to a second output location specified in the second instruction. In combination with any of the above embodiments, executing the first instruction may include identifying key-value pairs in the second set of key-value pairs whose keys match a key in a key-value pair in the first set of key-value pairs. In combination with any of the above embodiments, the method may include producing a result of the identification. The result of the identification may include a collection of matching keys, a collection of values for key-value pairs in the second set of key-value pairs with matching keys, or an indication of the number of matching keys. In any of the above embodiments, executing the first instruction may be implemented by a set operations logic unit. The set operations logic unit may be one of multiple set operations logic units in a processor. In combination with any of the above embodiments, the method may include receiving the first instruction from one of multiple processor cores in a processor. In combination with any of the above embodiments, the method may include receiving the first instruction from one of multiple hardware threads of a processor.

Some embodiments of the present disclosure include a set operations logic unit. In at least some of these embodiments, the set operations logic unit may include a content-associative memory, a first logic to store a first set of key-value pairs in the content-associative memory, a second logic to obtain input to represent a second set of key-value pairs from one or more input locations identified in the instruction, and a third logic to identify key-value pairs in the second set of key-value pairs whose keys match a key in a key-value pair in the first set of key-value pairs. In any of the above embodiments, the second set of key-value pairs may be an ordered set of key-value pairs in which the key-value pairs are sorted dependent on their respective keys. In any of the above embodiments, keys for the second set of key-value pairs may be stored in a first input location identified in the instruction, values for the second set of key-value pairs may be stored in a second input location identified in the instruction. In combination with any of the above embodiments, the set operations logic unit may include a fourth logic to receive the input to represent the second set of key-value pairs as streamed inputs from the first input location and the second input location. In combination with any of the above embodiments, the set operations logic unit may include a fourth logic to store, as a result of the identification, keys of the key-value pairs in the second set of key-value pairs whose keys match a key in a key-value pair in the first set of key-value pairs to a first output location identified in the instruction, and a fifth logic to store, as a result of the identification, values of the key-value pairs in the second set of key-value pairs whose keys match a key in a key-value pair in the first set of key-value pairs to a second output location identified in the instruction. In combination with any of the above embodiments, the set operations logic unit may include a fourth logic to store, as a result of the identification, data to represent a number of key-value pairs in the second set of key-value pairs whose keys match a key in a key-value pair in the first set of key-value pairs to an output location identified in the instruction. In combination with any of the above embodiments, the set operations logic unit may include a fourth logic to receive the instruction to be executed by the set operations logic unit. In combination with any of the above embodiments, the set operations logic unit may include a fifth logic to produce a result of the identification. The result may include a collection of matching keys, a collection of values for key-value pairs in the second set of key-value pairs with matching keys, or an indication of a number of matching keys. In combination with any of the above embodiments, the set operations logic unit may include a fourth logic to apply an arithmetic or aggregate operation specified in the instruction to a value in each key-value pair in the second set of key-value pairs whose key matches a key in a key-value pair in the first set of key-value pairs and a value in the key-value pair in the first set of key-value pairs with the matching key to obtain a result value for each matching key. In combination with any of the above embodiments, the set operations logic unit may include a fifth logic to create third set of key-value pairs that includes a respective key-value pair for each matching key that contains the result value for the matching key and a respective key-value pair for each key-value pair in the first set of key-value pairs and each key-value pair in the second set of key-value pairs that have unique keys, and a sixth logic to store the third set of key-value pairs in the content-associative memory. In combination with any of the above embodiments, the set operations logic unit may include a fourth logic to determine the length of the content-associative memory, where the length may represent the number of key-value pairs stored in the content-associative memory, and a fifth logic to return an indication of the length of the content-associative memory. In combination with any of the above embodiments, the set operations logic unit may include a fourth logic to delete or invalidate the contents of the content-associative memory, and a fifth logic to reset an indicator of length for the content-associative memory to zero, where the length may represent the number of key-value pairs stored in the content-associative memory. In combination with any of the above embodiments, the set operations logic unit may include a fourth logic to move keys of key-value pairs stored in the content-associative memory to a first output location specified in the instruction, and a fifth logic to move values of key-value pairs stored in the content-associative memory to a second output location specified in the instruction. In any of the above embodiments, the set operations logic unit may be one of a plurality of set operations logic units in a processor, and the set operations logic unit may include a sixth logic to receive instructions to be executed by the set operations logic unit from one of a plurality of processor cores in the processor. In combination with any of the above embodiments, the set operations logic unit may include a sixth logic to receive instructions to be executed by the set operations logic unit from a plurality of processor cores or hardware threads of a processor.

Some embodiments of the present disclosure include a system. In at least some of these embodiments, the system may include a content-associative memory, a first logic to store a first set of key-value pairs in the content-associative memory, a second logic to obtain input to represent a second set of key-value pairs from one or more input locations identified in the instruction, and a third logic to identify key-value pairs in the second set of key-value pairs whose keys match a key in a key-value pair in the first set of key-value pairs. In any of the above embodiments, the second set of key-value pairs may be an ordered set of key-value pairs in which the key-value pairs are sorted dependent on their respective keys. In any of the above embodiments, keys for the second set of key-value pairs may be stored in a first input location identified in the instruction, values for the second set of key-value pairs may be stored in a second input location identified in the instruction. In combination with any of the above embodiments, the system may include a fourth logic to receive the input to represent the second set of key-value pairs as streamed inputs from the first input location and the second input location. In combination with any of the above embodiments, the system may include a fourth logic to store, as a result of the identification, keys of the key-value pairs in the second set of key-value pairs whose keys match a key in a key-value pair in the first set of key-value pairs to a first output location identified in the instruction, and a fifth logic to store, as a result of the identification, values of the key-value pairs in the second set of key-value pairs whose keys match a key in a key-value pair in the first set of key-value pairs to a second output location identified in the instruction. In combination with any of the above embodiments, the system may include a fourth logic to store, as a result of the identification, data to represent a number of key-value pairs in the second set of key-value pairs whose keys match a key in a key-value pair in the first set of key-value pairs to an output location identified in the instruction. In combination with any of the above embodiments, the system may include a fourth logic to receive the instruction to be executed by the system. In combination with any of the above embodiments, the system may include a fifth logic to produce a result of the identification. The result may include a collection of matching keys, a collection of values for key-value pairs in the second set of key-value pairs with matching keys, or an indication of a number of matching keys. In combination with any of the above embodiments, the system may include a fourth logic to apply an arithmetic or aggregate operation specified in the instruction to a value in each key-value pair in the second set of key-value pairs whose key matches a key in a key-value pair in the first set of key-value pairs and a value in the key-value pair in the first set of key-value pairs with the matching key to obtain a result value for each matching key. In combination with any of the above embodiments, the system may include a fifth logic to create third set of key-value pairs that includes a respective key-value pair for each matching key that contains the result value for the matching key and a respective key-value pair for each key-value pair in the first set of key-value pairs and each key-value pair in the second set of key-value pairs that have unique keys, and a sixth logic to store the third set of key-value pairs in the content-associative memory. In combination with any of the above embodiments, the system may include a fourth logic to determine the length of the content-associative memory, where the length may represent the number of key-value pairs stored in the content-associative memory, and a fifth logic to return an indication of the length of the content-associative memory. In combination with any of the above embodiments, the system may include a fourth logic to delete or invalidate the contents of the content-associative memory, and a fifth logic to reset an indicator of length for the content-associative memory to zero, where the length may represent the number of key-value pairs stored in the content-associative memory. In combination with any of the above embodiments, the system may include a fourth logic to move keys of key-value pairs stored in the content-associative memory to a first output location specified in the instruction, and a fifth logic to move values of key-value pairs stored in the content-associative memory to a second output location specified in the instruction. In any of the above embodiments, the system may include a sixth logic to receive instructions to be executed from a particular one of a plurality of processor cores in a processor. In combination with any of the above embodiments, the system may include a sixth logic to receive instructions to be executed from a plurality of hardware threads of a processor.

Some embodiments of the present disclosure include a system for executing instructions. In at least some of these embodiments, the system may include means for receiving a first instruction, decoding the first instruction, executing the first instruction, and retiring the first instruction. The means for executing the first instruction may include means for accessing a first set of key-value pairs stored in a content-associative memory, means for receiving a second set of key-value pairs from one or more input locations identified in the first instruction, means for determining, for each key-value pair in the second set of key-value pairs, whether or not its key matches a key in a key-value pair in the first set of key-value pairs, and means for storing, to an output location identified in the first instruction, a result of the determination. In any of the above embodiments, the result of the determination may include the keys in the key-value pairs in the second set of key-value pairs that are determined to match keys in key-value pairs in the first set of key-value pairs, the values in the key-value pairs in the second set of key-value pairs whose keys are determined to match keys in key-value pairs in the first set of key-value pairs, or the number of keys in the key-value pairs in the second set of key-value pairs that are determined to match keys in key-value pairs in the first set of key-value pairs. In combination with any of the above embodiments, the system may include means for storing, as a result of the identification, keys of the key-value pairs in the second set of key-value pairs whose keys match a key in a key-value pair in the first set of key-value pairs to a first output location identified in the first instruction, and means for storing, as a result of the determination, values of the key-value pairs in the second set of key-value pairs whose keys match a key in a key-value pair in the first set of key-value pairs to a second output location identified in the first instruction. In combination with any of the above embodiments, the system may include means for storing, as a result of the determination, data representing the number of key-value pairs in the second set of key-value pairs whose keys match a key in a key-value pair in the first set of key-value pairs to an output location identified in the first instruction. In any of the above embodiments, the means for executing the first instruction may include means for applying an operation specified in the first instruction to a value in each key-value pair in the second set of key-value pairs whose key matches a key in a key-value pair in the first set of key-value pairs and a value in the key-value pair in the first set of key-value pairs with the matching key to obtain a result value for each matching key, means for creating a third set of key-value pairs that includes a respective key-value pair for each matching key that contains the result value for the matching key and a respective key-value pair for each key-value pair in the first set of key-value pairs and each key-value pair in the second set of key-value pairs that have unique keys, and means for storing the third set of key-value pairs in the content-associative memory. In any of the above embodiments, the second set of key-value pairs may be an ordered set of key-value pairs in which the key-value pairs are sorted dependent on their respective keys. In any of the above embodiments, keys for the second set of key-value pairs may be stored in a first input location identified in the first instruction, values for the second set of key-value pairs may be stored in a second input location identified in the first instruction, and the system may include means for receiving the input representing the second set of key-value pairs as streamed inputs from the first input location and the second input location. In combination with any of the above embodiments, the system may include means for receiving a second instruction, decoding the second instruction, executing the second instruction, and retiring the second instruction. In any of the above embodiments, the means for executing the second instruction may include means for determining the length of the content-associative memory, where the length represents the number of key-value pairs stored in the content-associative memory, and means for returning an indication of the length of the content-associative memory. In any of the above embodiments, the means for executing the second instruction may include means for deleting or invalidating the contents of the content-associative memory, and means for resetting an indicator of length for the content-associative memory to zero, where the length represents the number of key-value pairs stored in the content-associative memory. In any of the above embodiments, the means for executing the second instruction may include means for storing keys of key-value pairs stored in the content-associative memory to a first output location specified in the second instruction, and means for storing values of key-value pairs stored in the content-associative memory to a second output location specified in the second instruction. In any of the above embodiments, the means for executing the first instruction may include means for identifying key-value pairs in the second set of key-value pairs whose keys match a key in a key-value pair in the first set of key-value pairs. In any of the above embodiments, the system may include means for producing a result of the identification. The result of the identification may include a collection of matching keys, a collection of values for key-value pairs in the second set of key-value pairs with matching keys, or an indication of the number of matching keys. In any of the above embodiments, the means for executing the first instruction may include a set operations logic unit. In combination with any of the above embodiments, the system may include means for receiving the first instruction from one of multiple processor cores in a processor. In combination with any of the above embodiments, the system may include means for receiving the first instruction from one of multiple hardware threads of a processor.

Hardware content-associative data structure for acceleration of set operations

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