APPARATUS AND METHOD FOR SELECTING ELEMENTS OF A VECTOR COMPUTATION

BACKGROUND

1. Field of the Invention

Embodiments of the invention relate generally to the field of computer systems. More particularly, the embodiments of the invention relate to an apparatus and method for selecting elements of a vector computation.

2. General Background

An instruction set, or instruction set architecture (ISA), is the part of the computer architecture related to programming, and may include the native data types, instructions, register architecture, addressing modes, memory architecture, interrupt and exception handling, and external input and output (I/O). The term instruction generally refers herein to macro-instructions—that is instructions that are provided to the processor (or instruction converter that translates (e.g., using static binary translation, dynamic binary translation including dynamic compilation), morphs, emulates, or otherwise converts an instruction to one or more other instructions to be processed by the processor) for execution—as opposed to micro-instructions or micro-operations (micro-ops)—that is the result of a processor's decoder decoding macro-instructions.

The ISA is distinguished from the microarchitecture, which is the internal design of the processor implementing the instruction set. Processors with different microarchitectures can share 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. For example, the same register architecture of the ISA may be implemented in different ways in different microarchitectures using 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; the use of multiple maps and a pool of registers), etc. Unless otherwise specified, the phrases register architecture, register file, and register are used herein to refer to that which is visible to the software/programmer and the manner in which instructions specify registers. Where a specificity is desired, the adjective logical, architectural, or software visible will be used to indicate registers/files in the register architecture, while different adjectives will be used to designation registers in a given microarchitecture (e.g., physical register, reorder buffer, retirement register, register pool).

An instruction set includes one or more instruction formats. A given instruction format defines various fields (number of bits, location of bits) to specify, among other things, the operation to be performed (opcode) and the operand(s) on which that operation is to be performed. Some instruction formats are further broken down though the definition of instruction templates (or subformats). For example, the instruction templates of a given instruction format may be defined to have different subsets of the instruction format's fields (the included fields are typically in the same order, but at least some have different bit positions because there are less fields included) and/or defined to have a given field interpreted differently. Thus, each instruction of an ISA is expressed using a given instruction format (and, if defined, in a given one of the instruction templates of that instruction format) and includes fields for specifying the operation and the operands. For example, an exemplary ADD instruction has a specific opcode and an instruction format that includes an opcode field to specify that opcode and operand fields to select operands (source1/destination and source2); and an occurrence of this ADD instruction in an instruction stream will have specific contents in the operand fields that select specific operands.

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) often require the same operation to be performed on a large number of data items (referred to as “data parallelism”). Single Instruction Multiple Data (SIMD) refers to a type of instruction that causes a processor to perform an operation on multiple data items. SIMD technology is especially suited to processors that can logically divide the bits in a register into a number of fixed-sized data elements, each of which represents a separate value. For example, the bits in a 256-bit register may be specified as a source operand to be operated on as four separate 64-bit packed data elements (quad-word (Q) size data elements), eight separate 32-bit packed data elements (double word (D) size data elements), sixteen separate 16-bit packed data elements (word (W) size data elements), or thirty-two separate 8-bit data elements (byte (B) size data elements). This type of data is referred to as packed data type or vector data type, and operands of this data type are referred to as packed data operands or vector operands. In other words, a packed data item or vector refers to a sequence of packed data elements, and a packed data operand or a vector operand is a source or destination operand of a SIMD instruction (also known as a packed data instruction or a vector instruction).

By way of example, one type of SIMD instruction specifies a single vector operation to be performed on two source vector operands in a vertical fashion to generate a destination vector operand (also referred to as a result vector operand) of the same size, with the same number of data elements, and in the same data element order. The data elements in the source vector operands are referred to as source data elements, while the data elements in the destination vector operand are referred to a destination or result data elements. These source vector operands are of the same size and contain data elements of the same width, and thus they contain the same number of data elements. The source data elements in the same bit positions in the two source vector operands form pairs of data elements (also referred to as corresponding data elements; that is, the data element in data element position 0 of each source operand correspond, the data element in data element position 1 of each source operand correspond, and so on). The operation specified by that SIMD instruction is performed separately on each of these pairs of source data elements to generate a matching number of result data elements, and thus each pair of source data elements has a corresponding result data element. Since the operation is vertical and since the result vector operand is the same size, has the same number of data elements, and the result data elements are stored in the same data element order as the source vector operands, the result data elements are in the same bit positions of the result vector operand as their corresponding pair of source data elements in the source vector operands. In addition to this exemplary type of SIMD instruction, there are a variety of other types of SIMD instructions (e.g., that has only one or has more than two source vector operands, that operate in a horizontal fashion, that generates a result vector operand that is of a different size, that has a different size data elements, and/or that has a different data element order). It should be understood that the term destination vector operand (or destination operand) is defined as the direct result of performing the operation specified by an instruction, including the storage of that destination operand at a location (be it a register or at a memory address specified by that instruction) so that it may be accessed as a source operand by another instruction (by specification of that same location by the another instruction).

The 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, has enabled a significant improvement in application performance. An additional set of SIMD extensions, referred to the Advanced Vector Extensions (AVX) (AVX1 and AVX2) and using the Vector Extensions (VEX) coding scheme, has been, has been released and/or published (e.g., see Intel® 64 and IA-32 Architectures Software Developers Manual, October 2011; and see Intel® Advanced Vector Extensions Programming Reference, June 2011).

BACKGROUND RELATED TO THE EMBODIMENTS OF THE INVENTION

A vector may be thought of as a column of data elements or other specified data stored in predetermined locations in a memory or register. Data processing applications which process vectors often require the use of an efficient hardware implementation for performing “vector reduction.” A vector reduction operation may be, for example, the addition or multiplication of the vector elements, yielding a result which is the sum or product of all the data elements of the vector. Vector reduction operations may also include (in addition to addition and multiplication) logical operations and comparisons for determining the largest or smallest element of the vector.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1A is a block diagram illustrating both an exemplary in-order pipeline and an exemplary register renaming, out-of-order issue/execution pipeline according to embodiments of the invention;

FIG. 1B is a block diagram illustrating both an exemplary embodiment of an in-order architecture core and an exemplary register renaming, out-of-order issue/execution architecture core to be included in a processor according to embodiments of the invention;

FIG. 2 is a block diagram of a single core processor and a multicore processor with integrated memory controller and graphics according to embodiments of the invention;

FIG. 3 illustrates a block diagram of a system in accordance with one embodiment of the present invention;

FIG. 4 illustrates a block diagram of a second system in accordance with an embodiment of the present invention;

FIG. 5 illustrates a block diagram of a third system in accordance with an embodiment of the present invention;

FIG. 6 illustrates a block diagram of a system on a chip (SoC) in accordance with an embodiment of the present invention;

FIG. 7 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 according to embodiments of the invention;

FIG. 8 illustrate one embodiment of the invention for performing a vector reduction;

FIG. 9 illustrates another embodiment of an apparatus for performing a vector reduction;

FIGS. 10A and 10B are block diagrams illustrating a generic vector friendly instruction format and instruction templates thereof according to embodiments of the invention;

FIG. 11A-D are block diagrams illustrating an exemplary specific vector friendly instruction format according to embodiments of the invention;

FIG. 12 is a block diagram of a register architecture according to one embodiment of the invention;

FIG. 13A is a block diagram of a single processor core, along with its connection to the on-die interconnect network and with its local subset of the Level 2 (L2) cache, according to embodiments of the invention; and

FIG. 13B is an expanded view of part of the processor core in FIG. 13A according to embodiments of the invention.

DETAILED DESCRIPTION
Exemplary Processor Architectures and Data Types

FIG. 1A is a block diagram illustrating both an exemplary in-order pipeline and an exemplary register renaming, out-of-order issue/execution pipeline according to embodiments of the invention. FIG. 1B is a block diagram illustrating both an exemplary embodiment of an in-order architecture core and an exemplary register renaming, out-of-order issue/execution architecture core to be included in a processor according to embodiments of the invention. The solid lined boxes in FIGS. 1A-B illustrate the in-order pipeline and in-order core, while the optional addition of the dashed lined boxes illustrates the register renaming, out-of-order issue/execution pipeline and core. Given that the in-order aspect is a subset of the out-of-order aspect, the out-of-order aspect will be described.

In FIG. 1A, a processor pipeline 100 includes a fetch stage 102, a length decode stage 104, a decode stage 106, an allocation stage 108, a renaming stage 110, a scheduling (also known as a dispatch or issue) stage 112, a register read/memory read stage 114, an execute stage 116, a write back/memory write stage 118, an exception handling stage 122, and a commit stage 124.

FIG. 1B shows processor core 190 including a front end unit 130 coupled to an execution engine unit 150, and both are coupled to a memory unit 170. The core 190 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. As yet another option, the core 190 may be a special-purpose core, such as, for example, a network or communication core, compression engine, coprocessor core, general purpose computing graphics processing unit (GPGPU) core, graphics core, or the like.

The front end unit 130 includes a branch prediction unit 132 coupled to an instruction cache unit 134, which is coupled to an instruction translation lookaside buffer (TLB) 136, which is coupled to an instruction fetch unit 138, which is coupled to a decode unit 140. The decode unit 140 (or decoder) 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 are decoded from, or which otherwise reflect, or are derived from, the original instructions. The decode unit 140 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, the core 190 includes a microcode ROM or other medium that stores microcode for certain macroinstructions (e.g., in decode unit 140 or otherwise within the front end unit 130). The decode unit 140 is coupled to a rename/allocator unit 152 in the execution engine unit 150.

The execution engine unit 150 includes the rename/allocator unit 152 coupled to a retirement unit 154 and a set of one or more scheduler unit(s) 156. The scheduler unit(s) 156 represents any number of different schedulers, including reservations stations, central instruction window, etc. The scheduler unit(s) 156 is coupled to the physical register file(s) unit(s) 158. Each of the physical register file(s) units 158 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, status (e.g., an instruction pointer that is the address of the next instruction to be executed), etc. In one embodiment, the physical register file(s) unit 158 comprises a vector registers unit, a write mask registers unit, and a scalar registers unit. These register units may provide architectural vector registers, vector mask registers, and general purpose registers. The physical register file(s) unit(s) 158 is overlapped by the retirement unit 154 to illustrate various ways in which register renaming and out-of-order execution may be implemented (e.g., using a reorder buffer(s) and a retirement register file(s); using a future file(s), a history buffer(s), and a retirement register file(s); using a register maps and a pool of registers; etc.). The retirement unit 154 and the physical register file(s) unit(s) 158 are coupled to the execution cluster(s) 160. The execution cluster(s) 160 includes a set of one or more execution units 162 and a set of one or more memory access units 164. The execution units 162 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. The scheduler unit(s) 156, physical register file(s) unit(s) 158, and execution cluster(s) 160 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(s) unit, and/or execution cluster—and in the case of a separate memory access pipeline, certain embodiments are implemented in which only the execution cluster of this pipeline has the memory access unit(s) 164). 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 164 is coupled to the memory unit 170, which includes a data TLB unit 172 coupled to a data cache unit 174 coupled to a level 2 (L2) cache unit 176. In one exemplary embodiment, the memory access units 164 may include a load unit, a store address unit, and a store data unit, each of which is coupled to the data TLB unit 172 in the memory unit 170. The instruction cache unit 134 is further coupled to a level 2 (L2) cache unit 176 in the memory unit 170. The L2 cache unit 176 is 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 the pipeline 100 as follows: 1) the instruction fetch 138 performs the fetch and length decoding stages 102 and 104; 2) the decode unit 140 performs the decode stage 106; 3) the rename/allocator unit 152 performs the allocation stage 108 and renaming stage 110; 4) the scheduler unit(s) 156 performs the schedule stage 112; 5) the physical register file(s) unit(s) 158 and the memory unit 170 perform the register read/memory read stage 114; the execution cluster 160 perform the execute stage 116; 6) the memory unit 170 and the physical register file(s) unit(s) 158 perform the write back/memory write stage 118; 7) various units may be involved in the exception handling stage 122; and 8) the retirement unit 154 and the physical register file(s) unit(s) 158 perform the commit stage 124.

The core 190 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.), including the instruction(s) described herein. In one embodiment, the core 190 includes logic to support a packed data instruction set extension (e.g., AVX1, AVX2, and/or some form of the generic vector friendly instruction format (U=0 and/or U=1), described below), thereby allowing the operations used by many multimedia applications to be performed using packed data.

It should be understood that the core may support multithreading (executing two or more parallel sets of operations or threads), and may do so in a variety of ways 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 (e.g., time sliced fetching and decoding and simultaneous multithreading thereafter such as in the Intel® Hyperthreading technology).

While register renaming is 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 also includes separate instruction and data cache units 134/174 and a shared L2 cache unit 176, alternative 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 is external to the core and/or the processor. Alternatively, all of the cache may be external to the core and/or the processor.

FIG. 2 is a block diagram of a processor 200 that may have more than one core, may have an integrated memory controller, and may have integrated graphics according to embodiments of the invention. The solid lined boxes in FIG. 2 illustrate a processor 200 with a single core 202A, a system agent 210, a set of one or more bus controller units 216, while the optional addition of the dashed lined boxes illustrates an alternative processor 200 with multiple cores 202A-N, a set of one or more integrated memory controller unit(s) 214 in the system agent unit 210, and special purpose logic 208.

Thus, different implementations of the processor 200 may include: 1) a CPU with the special purpose logic 208 being integrated graphics and/or scientific (throughput) logic (which may include one or more cores), and the cores 202A-N being one or more general purpose cores (e.g., general purpose in-order cores, general purpose out-of-order cores, a combination of the two); 2) a coprocessor with the cores 202A-N being a large number of special purpose cores intended primarily for graphics and/or scientific (throughput); and 3) a coprocessor with the cores 202A-N being a large number of general purpose in-order cores. Thus, the processor 200 may be a general-purpose processor, coprocessor or special-purpose processor, such as, for example, a network or communication processor, compression engine, graphics processor, GPGPU (general purpose graphics processing unit), a high-throughput many integrated core (MIC) coprocessor (including 30 or more cores), embedded processor, or the like. The processor may be implemented on one or more chips. The processor 200 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.

The memory hierarchy includes one or more levels of cache within the cores, a set or one or more shared cache units 206, and external memory (not shown) coupled to the set of integrated memory controller units 214. The set of shared cache units 206 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. While in one embodiment a ring based interconnect unit 212 interconnects the integrated graphics logic 208, the set of shared cache units 206, and the system agent unit 210/integrated memory controller unit(s) 214, alternative embodiments may use any number of well-known techniques for interconnecting such units. In one embodiment, coherency is maintained between one or more cache units 206 and cores 202-A-N.

In some embodiments, one or more of the cores 202A-N are capable of multi-threading. The system agent 210 includes those components coordinating and operating cores 202A-N. The system agent unit 210 may include for example a power control unit (PCU) and a display unit. The PCU may be or include logic and components needed for regulating the power state of the cores 202A-N and the integrated graphics logic 208. The display unit is for driving one or more externally connected displays.

The cores 202A-N may be homogenous or heterogeneous in terms of architecture instruction set; that is, two or more of the cores 202A-N may be capable of execution the same instruction set, while others may be capable of executing only a subset of that instruction set or a different instruction set.

FIGS. 3-6 are block diagrams of exemplary computer architectures. Other system designs and configurations 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, are also suitable. In general, a huge variety of systems or electronic devices capable of incorporating a processor and/or other execution logic as disclosed herein are generally suitable.

Referring now to FIG. 3, shown is a block diagram of a system 300 in accordance with one embodiment of the present invention. The system 300 may include one or more processors 310, 315, which are coupled to a controller hub 320. In one embodiment the controller hub 320 includes a graphics memory controller hub (GMCH) 390 and an Input/Output Hub (IOH) 350 (which may be on separate chips); the GMCH 390 includes memory and graphics controllers to which are coupled memory 340 and a coprocessor 345; the IOH 350 is couples input/output (I/O) devices 360 to the GMCH 390. Alternatively, one or both of the memory and graphics controllers are integrated within the processor (as described herein), the memory 340 and the coprocessor 345 are coupled directly to the processor 310, and the controller hub 320 in a single chip with the IOH 350.

The optional nature of additional processors 315 is denoted in FIG. 3 with broken lines. Each processor 310, 315 may include one or more of the processing cores described herein and may be some version of the processor 200.

The memory 340 may be, for example, dynamic random access memory (DRAM), phase change memory (PCM), or a combination of the two. For at least one embodiment, the controller hub 320 communicates with the processor(s) 310, 315 via a multi-drop bus, such as a frontside bus (FSB), point-to-point interface such as QuickPath Interconnect (QPI), or similar connection 395.

In one embodiment, the coprocessor 345 is a special-purpose processor, such as, for example, a high-throughput MIC processor, a network or communication processor, compression engine, graphics processor, GPGPU, embedded processor, or the like. In one embodiment, controller hub 320 may include an integrated graphics accelerator.

There can be a variety of differences between the physical resources 310, 315 in terms of a spectrum of metrics of merit including architectural, microarchitectural, thermal, power consumption characteristics, and the like.

In one embodiment, the processor 310 executes instructions that control data processing operations of a general type. Embedded within the instructions may be coprocessor instructions. The processor 310 recognizes these coprocessor instructions as being of a type that should be executed by the attached coprocessor 345. Accordingly, the processor 310 issues these coprocessor instructions (or control signals representing coprocessor instructions) on a coprocessor bus or other interconnect, to coprocessor 345. Coprocessor(s) 345 accept and execute the received coprocessor instructions.

Referring now to FIG. 4, shown is a block diagram of a first more specific exemplary system 400 in accordance with an embodiment of the present invention. As shown in FIG. 4, multiprocessor system 400 is a point-to-point interconnect system, and includes a first processor 470 and a second processor 480 coupled via a point-to-point interconnect 450. Each of processors 470 and 480 may be some version of the processor 200. In one embodiment of the invention, processors 470 and 480 are respectively processors 310 and 315, while coprocessor 438 is coprocessor 345. In another embodiment, processors 470 and 480 are respectively processor 310 coprocessor 345.

Processors 470 and 480 are shown including integrated memory controller (IMC) units 472 and 482, respectively. Processor 470 also includes as part of its bus controller units point-to-point (P-P) interfaces 476 and 478; similarly, second processor 480 includes P-P interfaces 486 and 488. Processors 470, 480 may exchange information via a point-to-point (P-P) interface 450 using P-P interface circuits 478, 488. As shown in FIG. 4, IMCs 472 and 482 couple the processors to respective memories, namely a memory 432 and a memory 434, which may be portions of main memory locally attached to the respective processors.

Processors 470, 480 may each exchange information with a chipset 490 via individual P-P interfaces 452, 454 using point to point interface circuits 476, 494, 486, 498. Chipset 490 may optionally exchange information with the coprocessor 438 via a high-performance interface 439. In one embodiment, the coprocessor 438 is a special-purpose processor, such as, for example, a high-throughput MIC processor, a network or communication processor, compression engine, graphics processor, GPGPU, embedded processor, or the like.

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 490 may be coupled to a first bus 416 via an interface 496. In one embodiment, first bus 416 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 invention is not so limited.

As shown in FIG. 4, various I/O devices 414 may be coupled to first bus 416, along with a bus bridge 418 which couples first bus 416 to a second bus 420. In one embodiment, one or more additional processor(s) 415, such as coprocessors, high-throughput MIC processors, GPGPU's, accelerators (such as, e.g., graphics accelerators or digital signal processing (DSP) units), field programmable gate arrays, or any other processor, are coupled to first bus 416. In one embodiment, second bus 420 may be a low pin count (LPC) bus. Various devices may be coupled to a second bus 420 including, for example, a keyboard and/or mouse 422, communication devices 427 and a storage unit 428 such as a disk drive or other mass storage device which may include instructions/code and data 430, in one embodiment. Further, an audio I/O 424 may be coupled to the second bus 420. Note that other architectures are possible. For example, instead of the point-to-point architecture of FIG. 4, a system may implement a multi-drop bus or other such architecture.

Referring now to FIG. 5, shown is a block diagram of a second more specific exemplary system 500 in accordance with an embodiment of the present invention. Like elements in FIGS. 4 and 5 bear like reference numerals, and certain aspects of FIG. 4 have been omitted from FIG. 5 in order to avoid obscuring other aspects of FIG. 5.

FIG. 5 illustrates that the processors 470, 480 may include integrated memory and I/O control logic (“CL”) 472 and 482, respectively. Thus, the CL 472, 482 include integrated memory controller units and include I/O control logic. FIG. 5 illustrates that not only are the memories 432, 434 coupled to the CL 472, 482, but also that I/O devices 514 are also coupled to the control logic 472, 482. Legacy I/O devices 515 are coupled to the chipset 490.

Referring now to FIG. 6, shown is a block diagram of a SoC 600 in accordance with an embodiment of the present invention. Similar elements in FIG. 2 bear like reference numerals. Also, dashed lined boxes are optional features on more advanced SoCs. In FIG. 6, an interconnect unit(s) 602 is coupled to: an application processor 610 which includes a set of one or more cores 202A-N and shared cache unit(s) 206; a system agent unit 210; a bus controller unit(s) 216; an integrated memory controller unit(s) 214; a set or one or more coprocessors 620 which may include integrated graphics logic, an image processor, an audio processor, and a video processor; an static random access memory (SRAM) unit 630; a direct memory access (DMA) unit 632; and a display unit 640 for coupling to one or more external displays. In one embodiment, the coprocessor(s) 620 include a special-purpose processor, such as, for example, a network or communication processor, compression engine, GPGPU, a high-throughput MIC processor, embedded processor, or the like.

Embodiments of the mechanisms disclosed herein may be implemented in hardware, software, firmware, or a combination of such implementation approaches. Embodiments of the invention 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, such as code 430 illustrated in FIG. 4, 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 includes 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 rewritable's (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), phase change memory (PCM), magnetic or optical cards, or any other type of media suitable for storing electronic instructions.

Accordingly, embodiments of the invention 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.

FIG. 7 is 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 according to embodiments of the invention. In the illustrated embodiment, the instruction converter is a software instruction converter, although alternatively the instruction converter may be implemented in software, firmware, hardware, or various combinations thereof. FIG. 7 shows a program in a high level language 702 may be compiled using an x86 compiler 704 to generate x86 binary code 706 that may be natively executed by a processor with at least one x86 instruction set core 716. The processor with at least one x86 instruction set core 716 represents any processor that can 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. The x86 compiler 704 represents a compiler that is operable to generate x86 binary code 706 (e.g., object code) that can, with or without additional linkage processing, be executed on the processor with at least one x86 instruction set core 716. Similarly, FIG. 7 shows the program in the high level language 702 may be compiled using an alternative instruction set compiler 708 to generate alternative instruction set binary code 710 that may be natively executed by a processor without at least one x86 instruction set core 714 (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.). The instruction converter 712 is used to convert the x86 binary code 706 into code that may be natively executed by the processor without an x86 instruction set core 714. This converted code is not likely to be the same as the alternative instruction set binary code 710 because an instruction converter capable of this is difficult to make; however, the converted code will accomplish the general operation and be made up of instructions from the alternative instruction set. Thus, the instruction converter 712 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 the x86 binary code 706.

Embodiments of the Invention for Performing a Vector Reduction

Embodiments of the invention comprise a class of instructions that perform various forms of vector reduction within vector registers. By way of example and not limitations, the vector reductions may include logical operations such as bitwise AND and bitwise OR and mathematical operations such as multiplication and addition (summing).

In one embodiment, the new class of instructions take as an input a predicate-mask read from a mask register which controls the behavior of the reduction operation. Two forms of instructions are provided, referred to generally as “pre” and “post” to facilitate compiler code generation. The two forms differ in their outputs. The “pre” form of the instructions outputs the “pre” reduction value; whereas the “post” form of the instructions outputs the “post” reduction value (as described in greater detail below).

Two specific versions of the “pre” and “post” instructions are described below, referred to as vRunningPreAdd and vRunningPostAdd. It should be noted, however, that the underlying principles of the invention are not limited to these specific versions.

The following pseudo code describes the general form of the class of proposed instructions. The specific code sequence below performs reduction integer sum across the vector elements within a vector register. Other reduction functionalities contemplated within the scope of the invention include floating point addition, integer or floating point products (multiplication), bit-wise AND, bit-wise OR, bit-wise XOR and other logical and mathematical operations.

A. vRunningPreAdd (v1 , k1 , v2, v3) (

// VLEN is 8 for Q , 16 for D , 32 for W, and 64 for B

int j,

int sum;

for (j=0, j<VLEN, j++) {

v1[j] = v2[j];

if(k1[j]) {

sum = v2[j] + v3[j];

break;

}

}

for (j++; j<VLEN; j++) {

v1[j] = sum;

if (k1[j]) {

sum = sum + v3[j];

}

}

}

As indicated in the first line, the vector length (VLEN) may be set to 8, 16, 32, or 64. The variables j and sum are integer values. In the first for loop, the value of element j from the vector stored in register v1 is set to the value of element j from the vector stored in register v2. Then, if the value in the mask register k1 at the corresponding position j is true, the value of sum is set to the sum of the elements at position j from register v2 and v3 and the loop is exited. In the next for loop, the value of v1 at element position j is set equal to the value of sum at that element position and, if the value in the mask register k1 at bit position j is true, then the value of sum is set equal to sum+the element in position j in register v3.

B. vRunningPostAdd (v1, k1, v2, v3) {

// VLEN is 8 for Q , 16 for D , 32 for W, and 64 for B

int j,

int sum;

for(j=0; j<VLEN; j++) {

if(k1[j]) {

sum =v2[j] + v3[j],

v1[j] = sum;

break;

}

v1[j]=v2[j];

}

for (j++; j<VLEN; j++) {

if (k1[j]) {

sum = sum + v3[j];

}

v1[j] = sum;

}

}

As indicated in the first line, the vector length (VLEN) may be set to 8, 16, 32, or 64. The variables j and sum are integer values. In the first for loop if the value in the mask register k1 at the corresponding position j is true, the value of sum is set equal to the sum of the elements at position j from register v2 and v3, this sum is also stored in element j of vector v1, and the loop is exited. Otherwise the value of element j from the vector stored in register v1 is set equal to the value of element j in the vector stored in register v2. In the next for loop if the value in the mask register k1 at bit position j is true, then the value of sum is set equal to sum+the element in position j in register v3. Finally, in the last line, the element at position j in register v1 is set equal to the value from sum at the same element position.

To understand more clearly how the vRunningPreAdd and vRunningPostAdd operations are used, consider the following loop:

sum = 0;

for (i=0; i<N; i++) {

B[i] = sum;

if (A[i] > 0) {

sum = sum + A[i];

}

C[i] = sum;

}

In the above loop, the variable sum aggregates the positive values in array A. In each iteration of the loop the partial aggregate computed so far is stored in arrays B and C, the difference being that in B[i] the sum of positive entries in array A is entered from index 0 through i−1, whereas in C[i] the sum of positive entries in array A is entered from index 0 through i.

In one embodiment of the invention, vectorization of this loop uses hardware and instruction set architecture support provided by the embodiments of the invention described herein. This loop can be vectorized as shown below for a SIMD width of 8:

vSum =vBroadcast(0);
// Set vsum = {0,0,0,0,0,0,0,0}

for (i=0; i<N; i+=8) {
// Process 8 elements at a time

vA = Load(A[i:i+7])
// Load 8 elements from A

k = (vA > 0);
// Vector compare to generate mask

of positive entries in vA

vSum = vRunningPreAdd(vSum, vA, k);

B[i] = vSum;

vSum = vRunningPostAdd(vSum, vA, k);

C[i] = vSum;

vSum = vSelectLast(vSum, k)
// Select and broadcast the last

element as determined by k

}

To illustrate how this code would work assume the first 16 entries in A11 are:

A[ ]={0,−1,1,2, 1,−1,4,0, 1,0,1,0, 1,0,1,0}.

The scalar code would compute into sum the following successive values:

sum={0,0,1,3, 4,4,8,8, 9,9,10,10, 11,11,12,12}

Hence after the loop executes B[ ] and C[ ] would contain the following values (shown with the corresponding values of sum in FIG. 8):

B[ ]={0,0,0,1, 3,4,4,8, 8,9,9,10, 10,11,11,12}

C[ ]={0,0,1,3, 4,4,8,8, 9,9,10,10, 11,11,12,12}

Tracing the vector code, the vector vSum is initialized to all zeroes as shown. In the first iteration of the vector loop the following values are computed:

vA={0,−1,1,2, 1,−1,4,0}

k={0,0,1,1, 1,0,1,0} indicating that the 3^rd, 4^th, 5^th, and 7^thelements of vA are positive

vSum={0,0,0,1, 3,4,4,8} as computed by the vRunning PreAdd operation

The first 8 elements of B[ ] are then set to {0,0,0,1, 3,4,4,8}

The vRunningPostAdd operation will then compute vSum as:

vSum={0,0,1,3, 4,4,8,8}

The first 8 elements of C[ ] are then set to {0,0,1,3, 4,4,8,8}.

In one embodiment, since the last element of mask k that has a value of 1 is the 7^thelement, the operation vSelectLast described in co-pending application entitled Apparatus and Method for Selecting Elements of a Vector Computation, serial no. PCT/US11/67093, filed Dec. 23, 2011; assigned the assignee of the present application would select the 7^thelement of vSum, namely the value 8, and broadcast it. Hence, at the end of the loop vSum={8,8,8,8, 8,8,8,8}.

In the second vector iteration the following values are computed:

vA={1,0,1,0, 1,0,1,0},

k={1,0,1,0, 1,0,1,0} indicating that the 1^st, 3^rd, 5^th, and 7^thelements of vA are positive.

The vector vSum={8,9,9,10, 10,11,11,12} as computed by the vRunningPreAdd operation. The next 8 elements of B[ ] are then set to {8,9,9,10, 10,11,11,12}. The vRunningPostAdd operation will then compute vSum as follows:

vSum={9,9,10,10, 11,11,12,12}

The next 8 elements of C[ ] are then set to {9,9,10,10, 11,11,12,12}, and so on.

One embodiment of the invention includes micro-code for the above pseudo code. This embodiment allows flexibility of changing the implementation but provides little performance improvement. One advantage to a micro-coded implementation, however, is to reduce the register pressure in the generated code sequence as the micro-code can utilize internal registers that are not architecturally visible.

Departing from a software implementation of the proposed reduction instruction, various amounts of hardware logic can be used to improve the performance of such reduction operation. FIG. 9 illustrates one such embodiment which includes a reduction logic unit 920 used to perform reduction in a single operation cycle for N vector elements. FIG. 9 assumes a sequential implementation (i.e., for N elements, it will take N cycles to complete). The reduction logic unit 920 of this embodiment operates on one element per cycle. It should be noted, however, that other embodiments may employ a single cycle operation.

In one embodiment, the reduction logic unit 920 can perform sum, product, bit-wise or, bit-wise and, bit wise xor, etc., communicative operations. Vector elements are read from each of two input vector registers 901-902 based on signal provide by sequencer 950 (which, in one embodiment, sequences from 0 to N−1).

The output of one of the input registers (V3) 902 is coupled directly to the reduction logic 920. The output of the other input register (V2) 901 is sent to two different muxes 907-908, which are controlled by the output from the set/reset flip flop (SR FF) unit 951, which outputs a 1 after the first 1 detected in the mask register (k1) 903. The SR/FF unit 951 will set to 1 when the input from the mask register 903 is initially 1. It will not reset its output to 0 until the next time the logic is reset. Thus, prior to the first 1, mux 908 provides an input register 901 value to the reduction logic; after the first one, it provides a value from a temporary register 911. Similarly, prior to the first 1 from the mask register, mux 907 outputs the value from the input register (v2) 901 to the output register (v1) 910. After the first 1, mux 907 outputs the values generated by the reduction logic unit 920. The output register is thus populated according to the details set forth above.

Exemplary Instruction Formats

Embodiments of the instruction(s) described herein may be embodied in different formats. Additionally, exemplary systems, architectures, and pipelines are detailed below. Embodiments of the instruction(s) may be executed on such systems, architectures, and pipelines, but are not limited to those detailed.

A vector friendly instruction format is an instruction format that is suited for vector instructions (e.g., there are certain fields specific to vector operations). While embodiments are described in which both vector and scalar operations are supported through the vector friendly instruction format, alternative embodiments use only vector operations the vector friendly instruction format.

FIGS. 10A-10B are block diagrams illustrating a generic vector friendly instruction format and instruction templates thereof according to embodiments of the invention. FIG. 10A is a block diagram illustrating a generic vector friendly instruction format and class A instruction templates thereof according to embodiments of the invention; while FIG. 10B is a block diagram illustrating the generic vector friendly instruction format and class B instruction templates thereof according to embodiments of the invention. Specifically, a generic vector friendly instruction format 1000 for which are defined class A and class B instruction templates, both of which include no memory access 1005 instruction templates and memory access 1020 instruction templates. The term generic in the context of the vector friendly instruction format refers to the instruction format not being tied to any specific instruction set.

While embodiments of the invention will be described in which the vector friendly instruction format supports the following: a 64 byte vector operand length (or size) with 32 bit (4 byte) or 64 bit (8 byte) data element widths (or sizes) (and thus, a 64 byte vector consists of either 16 doubleword-size elements or alternatively, 8 quadword-size elements); a 64 byte vector operand length (or size) with 16 bit (2 byte) or 8 bit (1 byte) data element widths (or sizes); a 32 byte vector operand length (or size) with 32 bit (4 byte), 64 bit (8 byte), 16 bit (2 byte), or 8 bit (1 byte) data element widths (or sizes); and a 16 byte vector operand length (or size) with 32 bit (4 byte), 64 bit (8 byte), 16 bit (2 byte), or 8 bit (1 byte) data element widths (or sizes); alternative embodiments may support more, less and/or different vector operand sizes (e.g., 256 byte vector operands) with more, less, or different data element widths (e.g., 128 bit (16 byte) data element widths).

The class A instruction templates in FIG. 10A include: 1) within the no memory access 1005 instruction templates there is shown a no memory access, full round control type operation 1010 instruction template and a no memory access, data transform type operation 1015 instruction template; and 2) within the memory access 1020 instruction templates there is shown a memory access, temporal 1025 instruction template and a memory access, non-temporal 1030 instruction template. The class B instruction templates in FIG. 10B include: 1) within the no memory access 1005 instruction templates there is shown a no memory access, write mask control, partial round control type operation 1012 instruction template and a no memory access, write mask control, vsize type operation 1017 instruction template; and 2) within the memory access 1020 instruction templates there is shown a memory access, write mask control 1027 instruction template.

The generic vector friendly instruction format 1000 includes the following fields listed below in the order illustrated in FIGS. 10A-10B.

Format field 1040—a specific value (an instruction format identifier value) in this field uniquely identifies the vector friendly instruction format, and thus occurrences of instructions in the vector friendly instruction format in instruction streams. As such, this field is optional in the sense that it is not needed for an instruction set that has only the generic vector friendly instruction format.

Base operation field 1042—its content distinguishes different base operations.

Register index field 1044—its content, directly or through address generation, specifies the locations of the source and destination operands, be they in registers or in memory. These include a sufficient number of bits to select N registers from a P×Q (e.g. 32×512, 16×128, 32×1024, 64×1024) register file. While in one embodiment N may be up to three sources and one destination register, alternative embodiments may support more or less sources and destination registers (e.g., may support up to two sources where one of these sources also acts as the destination, may support up to three sources where one of these sources also acts as the destination, may support up to two sources and one destination).

Modifier field 1046—its content distinguishes occurrences of instructions in the generic vector instruction format that specify memory access from those that do not; that is, between no memory access 1005 instruction templates and memory access 1020 instruction templates. Memory access operations read and/or write to the memory hierarchy (in some cases specifying the source and/or destination addresses using values in registers), while non-memory access operations do not (e.g., the source and destinations are registers). While in one embodiment this field also selects between three different ways to perform memory address calculations, alternative embodiments may support more, less, or different ways to perform memory address calculations.

Augmentation operation field 1050—its content distinguishes which one of a variety of different operations to be performed in addition to the base operation. This field is context specific. In one embodiment of the invention, this field is divided into a class field 1068, an alpha field 1052, and a beta field 1054. The augmentation operation field 1050 allows common groups of operations to be performed in a single instruction rather than 2, 3, or 4 instructions.

Scale field 1060—its content allows for the scaling of the index field's content for memory address generation (e.g., for address generation that uses 2^scale*index+base).

Displacement Field 1062A—its content is used as part of memory address generation (e.g., for address generation that uses 2^scale*index+base+displacement).

Displacement Factor Field 1062B (note that the juxtaposition of displacement field 1062A directly over displacement factor field 1062B indicates one or the other is used)—its content is used as part of address generation; it specifies a displacement factor that is to be scaled by the size of a memory access (N)—where N is the number of bytes in the memory access (e.g., for address generation that uses 2^scale*index+base+scaled displacement). Redundant low-order bits are ignored and hence, the displacement factor field's content is multiplied by the memory operands total size (N) in order to generate the final displacement to be used in calculating an effective address. The value of N is determined by the processor hardware at runtime based on the full opcode field 1074 (described herein) and the data manipulation field 1054C. The displacement field 1062A and the displacement factor field 1062B are optional in the sense that they are not used for the no memory access 1005 instruction templates and/or different embodiments may implement only one or none of the two.

Data element width field 1064—its content distinguishes which one of a number of data element widths is to be used (in some embodiments for all instructions; in other embodiments for only some of the instructions). This field is optional in the sense that it is not needed if only one data element width is supported and/or data element widths are supported using some aspect of the opcodes.

Write mask field 1070—its content controls, on a per data element position basis, whether that data element position in the destination vector operand reflects the result of the base operation and augmentation operation. Class A instruction templates support merging-writemasking, while class B instruction templates support both merging- and zeroing-writemasking. When merging, vector masks allow any set of elements in the destination to be protected from updates during the execution of any operation (specified by the base operation and the augmentation operation); in other one embodiment, preserving the old value of each element of the destination where the corresponding mask bit has a 0. In contrast, when zeroing vector masks allow any set of elements in the destination to be zeroed during the execution of any operation (specified by the base operation and the augmentation operation); in one embodiment, an element of the destination is set to 0 when the corresponding mask bit has a 0 value. A subset of this functionality is the ability to control the vector length of the operation being performed (that is, the span of elements being modified, from the first to the last one); however, it is not necessary that the elements that are modified be consecutive. Thus, the write mask field 1070 allows for partial vector operations, including loads, stores, arithmetic, logical, etc. While embodiments of the invention are described in which the write mask field's 1070 content selects one of a number of write mask registers that contains the write mask to be used (and thus the write mask field's 1070 content indirectly identifies that masking to be performed), alternative embodiments instead or additional allow the mask write field's 1070 content to directly specify the masking to be performed.

Immediate field 1072—its content allows for the specification of an immediate. This field is optional in the sense that is it not present in an implementation of the generic vector friendly format that does not support immediate and it is not present in instructions that do not use an immediate.

Class field 1068—its content distinguishes between different classes of instructions. With reference to FIGS. 10A-B, the contents of this field select between class A and class B instructions. In FIGS. 10A-B, rounded corner squares are used to indicate a specific value is present in a field (e.g., class A 1068A and class B 1068B for the class field 1068 respectively in FIGS. 10A-B).

Instruction Templates of Class A

In the case of the non-memory access 1005 instruction templates of class A, the alpha field 1052 is interpreted as an RS field 1052A, whose content distinguishes which one of the different augmentation operation types are to be performed (e.g., round 1052A.1 and data transform 1052A.2 are respectively specified for the no memory access, round type operation 1010 and the no memory access, data transform type operation 1015 instruction templates), while the beta field 1054 distinguishes which of the operations of the specified type is to be performed. In the no memory access 1005 instruction templates, the scale field 1060, the displacement field 1062A, and the displacement scale filed 1062B are not present.

No-Memory Access Instruction Templates—Full Round Control Type Operation

In the no memory access full round control type operation 1010 instruction template, the beta field 1054 is interpreted as a round control field 1054A, whose content(s) provide static rounding. While in the described embodiments of the invention the round control field 1054A includes a suppress all floating point exceptions (SAE) field 1056 and a round operation control field 1058, alternative embodiments may support may encode both these concepts into the same field or only have one or the other of these concepts/fields (e.g., may have only the round operation control field 1058).

SAE field 1056—its content distinguishes whether or not to disable the exception event reporting; when the SAE field's 1056 content indicates suppression is enabled, a given instruction does not report any kind of floating-point exception flag and does not raise any floating point exception handler.

Round operation control field 1058—its content distinguishes which one of a group of rounding operations to perform (e.g., Round-up, Round-down, Round-towards-zero and Round-to-nearest). Thus, the round operation control field 1058 allows for the changing of the rounding mode on a per instruction basis. In one embodiment of the invention where a processor includes a control register for specifying rounding modes, the round operation control field's 1050 content overrides that register value.

No Memory Access Instruction Templates—Data Transform Type Operation

In the no memory access data transform type operation 1015 instruction template, the beta field 1054 is interpreted as a data transform field 1054B, whose content distinguishes which one of a number of data transforms is to be performed (e.g., no data transform, swizzle, broadcast).

In the case of a memory access 1020 instruction template of class A, the alpha field 1052 is interpreted as an eviction hint field 1052B, whose content distinguishes which one of the eviction hints is to be used (in FIG. 10A, temporal 1052B.1 and non-temporal 1052B.2 are respectively specified for the memory access, temporal 1025 instruction template and the memory access, non-temporal 1030 instruction template), while the beta field 1054 is interpreted as a data manipulation field 1054C, whose content distinguishes which one of a number of data manipulation operations (also known as primitives) is to be performed (e.g., no manipulation; broadcast; up conversion of a source; and down conversion of a destination). The memory access 1020 instruction templates include the scale field 1060, and optionally the displacement field 1062A or the displacement scale field 1062B.

Vector memory instructions perform vector loads from and vector stores to memory, with conversion support. As with regular vector instructions, vector memory instructions transfer data from/to memory in a data element-wise fashion, with the elements that are actually transferred is dictated by the contents of the vector mask that is selected as the write mask.

Memory Access Instruction Templates—Temporal

Temporal data is data likely to be reused soon enough to benefit from caching. This is, however, a hint, and different processors may implement it in different ways, including ignoring the hint entirely.

Memory Access Instruction Templates—Non-Temporal

Non-temporal data is data unlikely to be reused soon enough to benefit from caching in the 1st-level cache and should be given priority for eviction. This is, however, a hint, and different processors may implement it in different ways, including ignoring the hint entirely.

Instruction Templates of Class B

In the case of the instruction templates of class B, the alpha field 1052 is interpreted as a write mask control (Z) field 1052C, whose content distinguishes whether the write masking controlled by the write mask field 1070 should be a merging or a zeroing.

In the case of the non-memory access 1005 instruction templates of class B, part of the beta field 1054 is interpreted as an RL field 1057A, whose content distinguishes which one of the different augmentation operation types are to be performed (e.g., round 1057A.1 and vector length (VSIZE) 1057A.2 are respectively specified for the no memory access, write mask control, partial round control type operation 1012 instruction template and the no memory access, write mask control, VSIZE type operation 1017 instruction template), while the rest of the beta field 1054 distinguishes which of the operations of the specified type is to be performed. In the no memory access 1005 instruction templates, the scale field 1060, the displacement field 1062A, and the displacement scale filed 1062B are not present.

In the no memory access, write mask control, partial round control type operation 1010 instruction template, the rest of the beta field 1054 is interpreted as a round operation field 1059A and exception event reporting is disabled (a given instruction does not report any kind of floating-point exception flag and does not raise any floating point exception handler).

Round operation control field 1059A—just as round operation control field 1058, its content distinguishes which one of a group of rounding operations to perform (e.g., Round-up, Round-down, Round-towards-zero and Round-to-nearest). Thus, the round operation control field 1059A allows for the changing of the rounding mode on a per instruction basis. In one embodiment of the invention where a processor includes a control register for specifying rounding modes, the round operation control field's 1050 content overrides that register value.

In the no memory access, write mask control, VSIZE type operation 1017 instruction template, the rest of the beta field 1054 is interpreted as a vector length field 1059B, whose content distinguishes which one of a number of data vector lengths is to be performed on (e.g., 128, 256, or 512 byte).

In the case of a memory access 1020 instruction template of class B, part of the beta field 1054 is interpreted as a broadcast field 1057B, whose content distinguishes whether or not the broadcast type data manipulation operation is to be performed, while the rest of the beta field 1054 is interpreted the vector length field 1059B. The memory access 1020 instruction templates include the scale field 1060, and optionally the displacement field 1062A or the displacement scale field 1062B.

With regard to the generic vector friendly instruction format 1000, a full opcode field 1074 is shown including the format field 1040, the base operation field 1042, and the data element width field 1064. While one embodiment is shown where the full opcode field 1074 includes all of these fields, the full opcode field 1074 includes less than all of these fields in embodiments that do not support all of them. The full opcode field 1074 provides the operation code (opcode).

The augmentation operation field 1050, the data element width field 1064, and the write mask field 1070 allow these features to be specified on a per instruction basis in the generic vector friendly instruction format.

The combination of write mask field and data element width field create typed instructions in that they allow the mask to be applied based on different data element widths.

The various instruction templates found within class A and class B are beneficial in different situations. In some embodiments of the invention, different processors or different cores within a processor may support only class A, only class B, or both classes. For instance, a high performance general purpose out-of-order core intended for general-purpose computing may support only class B, a core intended primarily for graphics and/or scientific (throughput) computing may support only class A, and a core intended for both may support both (of course, a core that has some mix of templates and instructions from both classes but not all templates and instructions from both classes is within the purview of the invention). Also, a single processor may include multiple cores, all of which support the same class or in which different cores support different class. For instance, in a processor with separate graphics and general purpose cores, one of the graphics cores intended primarily for graphics and/or scientific computing may support only class A, while one or more of the general purpose cores may be high performance general purpose cores with out of order execution and register renaming intended for general-purpose computing that support only class B. Another processor that does not have a separate graphics core, may include one more general purpose in-order or out-of-order cores that support both class A and class B. Of course, features from one class may also be implement in the other class in different embodiments of the invention. Programs written in a high level language would be put (e.g., just in time compiled or statically compiled) into an variety of different executable forms, including: 1) a form having only instructions of the class(es) supported by the target processor for execution; or 2) a form having alternative routines written using different combinations of the instructions of all classes and having control flow code that selects the routines to execute based on the instructions supported by the processor which is currently executing the code.

FIG. 11A-D are block diagrams illustrating an exemplary specific vector friendly instruction format according to embodiments of the invention. FIG. 11 shows a specific vector friendly instruction format 1100 that is specific in the sense that it specifies the location, size, interpretation, and order of the fields, as well as values for some of those fields. The specific vector friendly instruction format 1100 may be used to extend the x86 instruction set, and thus some of the fields are similar or the same as those used in the existing x86 instruction set and extension thereof (e.g., AVX). This format remains consistent with the prefix encoding field, real opcode byte field, MOD R/M field, SIB field, displacement field, and immediate fields of the existing x86 instruction set with extensions. The fields from FIG. 10 into which the fields from FIG. 11 map are illustrated.

It should be understood that, although embodiments of the invention are described with reference to the specific vector friendly instruction format 1100 in the context of the generic vector friendly instruction format 1000 for illustrative purposes, the invention is not limited to the specific vector friendly instruction format 1100 except where claimed. For example, the generic vector friendly instruction format 1000 contemplates a variety of possible sizes for the various fields, while the specific vector friendly instruction format 1100 is shown as having fields of specific sizes. By way of specific example, while the data element width field 1064 is illustrated as a one bit field in the specific vector friendly instruction format 1100, the invention is not so limited (that is, the generic vector friendly instruction format 1000 contemplates other sizes of the data element width field 1064).

The generic vector friendly instruction format 1000 includes the following fields listed below in the order illustrated in FIG. 11A.

EVEX Prefix (Bytes 0-3) 1102—is encoded in a four-byte form.

Format Field 1040 (EVEX Byte 0, bits [7:0])—the first byte (EVEX Byte 0) is the format field 1040 and it contains 0×62 (the unique value used for distinguishing the vector friendly instruction format in one embodiment of the invention).

The second-fourth bytes (EVEX Bytes 1-3) include a number of bit fields providing specific capability.

REX field 1105 (EVEX Byte 1, bits [7-5])—consists of a EVEX.R bit field (EVEX Byte 1, bit [7] —R), EVEX.X bit field (EVEX byte 1, bit [6] —X), and 1057BEX byte 1, bit[5] —B). The EVEX.R, EVEX.X, and EVEX.B bit fields provide the same functionality as the corresponding VEX bit fields, and are encoded using is complement form, i.e. ZMM0 is encoded as 1011B, ZMM15 is encoded as 0000B. Other fields of the instructions encode the lower three bits of the register indexes as is known in the art (rrr, xxx, and bbb), so that Rrrr, Xxxx, and Bbbb may be formed by adding EVEX.R, EVEX.X, and EVEX.B.

REX′ field 1010—this is the first part of the REX′ field 1010 and is the EVEX.R′ bit field (EVEX Byte 1, bit [4]-R′) that is used to encode either the upper 16 or lower 16 of the extended 32 register set. In one embodiment of the invention, this bit, along with others as indicated below, is stored in bit inverted format to distinguish (in the well-known x86 32-bit mode) from the BOUND instruction, whose real opcode byte is 62, but does not accept in the MOD R/M field (described below) the value of 11 in the MOD field; alternative embodiments of the invention do not store this and the other indicated bits below in the inverted format. A value of 1 is used to encode the lower 16 registers. In other words, R′Rrrr is formed by combining EVEX.R′, EVEX.R, and the other RRR from other fields.

Opcode map field 1115 (EVEX byte 1, bits [3:0] —mmmm)—its content encodes an implied leading opcode byte (0F, 0F 38, or 0F 3).

Data element width field 1164 (EVEX byte 2, bit [7] —W)—is represented by the notation EVEX.W. EVEX.W is used to define the granularity (size) of the datatype (either 32-bit data elements or 64-bit data elements).

EVEX.vvvv 1120 (EVEX Byte 2, bits [6:3]-vvvv)—the role of EVEX.vvvv may include the following: 1) EVEX.vvvv encodes the first source register operand, specified in inverted (1 s complement) form and is valid for instructions with 2 or more source operands; 2) EVEX.vvvv encodes the destination register operand, specified in 1 s complement form for certain vector shifts; or 3) EVEX.vvvv does not encode any operand, the field is reserved and should contain 1111b. Thus, EVEX.vvvv field 1120 encodes the 4 low-order bits of the first source register specifier stored in inverted (1 s complement) form. Depending on the instruction, an extra different EVEX bit field is used to extend the specifier size to 32 registers.

EVEX.U 1168 Class field (EVEX byte 2, bit [2]-U)—If EVEX.U=0, it indicates class A or EVEX.U0; if EVEX.U=1, it indicates class B or EVEX.U1.

Prefix encoding field 1125 (EVEX byte 2, bits [1:0]-pp)—provides additional bits for the base operation field. In addition to providing support for the legacy SSE instructions in the EVEX prefix format, this also has the benefit of compacting the SIMD prefix (rather than requiring a byte to express the SIMD prefix, the EVEX prefix requires only 2 bits). In one embodiment, to support legacy SSE instructions that use a SIMD prefix (66H, F2H, F3H) in both the legacy format and in the EVEX prefix format, these legacy SIMD prefixes are encoded into the SIMD prefix encoding field; and at runtime are expanded into the legacy SIMD prefix prior to being provided to the decoder's PLA (so the PLA can execute both the legacy and EVEX format of these legacy instructions without modification). Although newer instructions could use the EVEX prefix encoding field's content directly as an opcode extension, certain embodiments expand in a similar fashion for consistency but allow for different meanings to be specified by these legacy SIMD prefixes. An alternative embodiment may redesign the PLA to support the 2 bit SIMD prefix encodings, and thus not require the expansion.

Alpha field 1152 (EVEX byte 3, bit [7] —EH; also known as EVEX.EH, EVEX.rs, EVEX.RL, EVEX.write mask control, and EVEX.N; also illustrated with α)—as previously described, this field is context specific.

Beta field 1154 (EVEX byte 3, bits [6:4]-SSS, also known as EVEX.s_2-0, EVEX.r_2-0, EVEX.rr1, EVEX.LL0, EVEX.LLB; also illustrated with βββ)—as previously described, this field is context specific.

REX′ field 1010—this is the remainder of the REX′ field and is the EVEX.V′ bit field (EVEX Byte 3, bit [3]-V′) that may be used to encode either the upper 16 or lower 16 of the extended 32 register set. This bit is stored in bit inverted format. A value of 1 is used to encode the lower 16 registers. In other words, V′VVVV is formed by combining EVEX.V′, EVEX.vvvv.

Write mask field 1070 (EVEX byte 3, bits [2:0]-kkk)—its content specifies the index of a register in the write mask registers as previously described. In one embodiment of the invention, the specific value EVEX.kkk=000 has a special behavior implying no write mask is used for the particular instruction (this may be implemented in a variety of ways including the use of a write mask hardwired to all ones or hardware that bypasses the masking hardware).

Real Opcode Field 1130 (Byte 4) is also known as the opcode byte. Part of the opcode is specified in this field.

MOD R/M Field 1140 (Byte 5) includes MOD field 1142, Reg field 1144, and R/M field 1146. As previously described, the MOD field's 1142 content distinguishes between memory access and non-memory access operations. The role of Reg field 1144 can be summarized to two situations: encoding either the destination register operand or a source register operand, or be treated as an opcode extension and not used to encode any instruction operand. The role of R/M field 1146 may include the following: encoding the instruction operand that references a memory address, or encoding either the destination register operand or a source register operand.

Scale, Index, Base (SIB) Byte (Byte 6)—As previously described, the scale field's 1050 content is used for memory address generation. SIB.xxx 1154 and SIB.bbb 1156—the contents of these fields have been previously referred to with regard to the register indexes Xxxx and Bbbb.

Displacement field 1062A (Bytes 7-10)—when MOD field 1142 contains 10, bytes 7-10 are the displacement field 1062A, and it works the same as the legacy 32-bit displacement (disp32) and works at byte granularity.

Displacement factor field 1062B (Byte 7)—when MOD field 1142 contains 01, byte 7 is the displacement factor field 1062B. The location of this field is that same as that of the legacy x86 instruction set 8-bit displacement (disp8), which works at byte granularity. Since disp8 is sign extended, it can only address between −128 and 127 bytes offsets; in terms of 64 byte cache lines, disp8 uses 8 bits that can be set to only four really useful values −128, −64, 0, and 64; since a greater range is often needed, disp32 is used; however, disp32 requires 4 bytes. In contrast to disp8 and disp32, the displacement factor field 1062B is a reinterpretation of disp8; when using displacement factor field 1062B, the actual displacement is determined by the content of the displacement factor field multiplied by the size of the memory operand access (N). This type of displacement is referred to as disp8*N. This reduces the average instruction length (a single byte of used for the displacement but with a much greater range). Such compressed displacement is based on the assumption that the effective displacement is multiple of the granularity of the memory access, and hence, the redundant low-order bits of the address offset do not need to be encoded. In other words, the displacement factor field 1062B substitutes the legacy x86 instruction set 8-bit displacement. Thus, the displacement factor field 1062B is encoded the same way as an x86 instruction set 8-bit displacement (so no changes in the ModRM/SIB encoding rules) with the only exception that disp8 is overloaded to disp8*N. In other words, there are no changes in the encoding rules or encoding lengths but only in the interpretation of the displacement value by hardware (which needs to scale the displacement by the size of the memory operand to obtain a byte-wise address offset).

Immediate field 1072 operates as previously described.

Full Opcode Field

FIG. 11B is a block diagram illustrating the fields of the specific vector friendly instruction format 1100 that make up the full opcode field 1074 according to one embodiment of the invention. Specifically, the full opcode field 1074 includes the format field 1040, the base operation field 1042, and the data element width (W) field 1064. The base operation field 1042 includes the prefix encoding field 1125, the opcode map field 1115, and the real opcode field 1130.

FIG. 11C is a block diagram illustrating the fields of the specific vector friendly instruction format 1100 that make up the register index field 1044 according to one embodiment of the invention. Specifically, the register index field 1044 includes the REX field 1105, the REX′ field 1110, the MODR/M.reg field 1144, the MODR/M.r/m field 1146, the VVVV field 1120, xxx field 1154, and the bbb field 1156.

Augmentation Operation Field

FIG. 11D is a block diagram illustrating the fields of the specific vector friendly instruction format 1100 that make up the augmentation operation field 1050 according to one embodiment of the invention. When the class (U) field 1068 contains 0, it signifies EVEX.U0 (class A 1068A); when it contains 1, it signifies EVEX.U1 (class B 1068B). When U=0 and the MOD field 1142 contains 11 (signifying a no memory access operation), the alpha field 1052 (EVEX byte 3, bit [7] —EH) is interpreted as the rs field 1052A. When the rs field 1052A contains a 1 (round 1052A.1), the beta field 1054 (EVEX byte 3, bits [6:4]-SSS) is interpreted as the round control field 1054A. The round control field 1054A includes a one bit SAE field 1056 and a two bit round operation field 1058. When the rs field 1052A contains a 0 (data transform 1052A.2), the beta field 1054 (EVEX byte 3, bits [6:4]-SSS) is interpreted as a three bit data transform field 1054B. When U=0 and the MOD field 1142 contains 00, 01, or 10 (signifying a memory access operation), the alpha field 1052 (EVEX byte 3, bit [7] —EH) is interpreted as the eviction hint (EH) field 1052B and the beta field 1054 (EVEX byte 3, bits [6:4]-SSS) is interpreted as a three bit data manipulation field 1054C.

When U=1, the alpha field 1052 (EVEX byte 3, bit [7] —EH) is interpreted as the write mask control (Z) field 1052C. When U=1 and the MOD field 1142 contains 11 (signifying a no memory access operation), part of the beta field 1054 (EVEX byte 3, bit [4]-S₀) is interpreted as the RL field 1057A; when it contains a 1 (round 1057A.1) the rest of the beta field 1054 (EVEX byte 3, bit [6-5]-S_2-1) is interpreted as the round operation field 1059A, while when the RL field 1057A contains a 0 (VSIZE 1057.A2) the rest of the beta field 1054 (EVEX byte 3, bit [6-5]-S_2-1) is interpreted as the vector length field 1059B (EVEX byte 3, bit [6-5]-L_1-0). When U=1 and the MOD field 1142 contains 00, 01, or 10 (signifying a memory access operation), the beta field 1054 (EVEX byte 3, bits [6:4]-SSS) is interpreted as the vector length field 1059B (EVEX byte 3, bit [6-5]-L_1-0) and the broadcast field 1057B (EVEX byte 3, bit [4]-B).

FIG. 12 is a block diagram of a register architecture 1200 according to one embodiment of the invention. In the embodiment illustrated, there are 32 vector registers 1210 that are 512 bits wide; these registers are referenced as zmm0 through zmm31. The lower order 256 bits of the lower 16 zmm registers are overlaid on registers ymm0-16. The lower order 128 bits of the lower 16 zmm registers (the lower order 128 bits of the ymm registers) are overlaid on registers xmm0-15. The specific vector friendly instruction format 1200 operates on these overlaid register file as illustrated in the table below.

Adjustable

Vector Length
Class
Operations
Registers

Instruction
A (FIG. 10A;
1010, 1015,
zmm registers

Templates that
U = 0)
1025, 1030
(the vector

do not include

length is 64 byte)

the vector length
B (FIG. 10B;
1012
zmm registers

field 1059B
U = 1)

(the vector

length is 64 byte)

Instruction
B (FIG. 10B;
1017, 1027
zmm, ymm, or

Templates that
U = 1)

xmm registers

do include the

(the vector

vector length

length is 64 byte,

field 1059B

32 byte, or 16

byte) depending

on the vector

length field

1059B

In other words, the vector length field 1059B selects between a maximum length and one or more other shorter lengths, where each such shorter length is half the length of the preceding length; and instructions templates without the vector length field 1059B operate on the maximum vector length. Further, in one embodiment, the class B instruction templates of the specific vector friendly instruction format 1200 operate on packed or scalar single/double-precision floating point data and packed or scalar integer data. Scalar operations are operations performed on the lowest order data element position in an zmm/ymm/xmm register; the higher order data element positions are either left the same as they were prior to the instruction or zeroed depending on the embodiment.

Write mask registers 1215—in the embodiment illustrated, there are 8 write mask registers (k0 through k7), each 64 bits in size. In an alternate embodiment, the write mask registers 1215 are 16 bits in size. As previously described, in one embodiment of the invention, the vector mask register k0 cannot be used as a write mask; when the encoding that would normally indicate k0 is used for a write mask, it selects a hardwired write mask of 0xFFFF, effectively disabling write masking for that instruction.

General-purpose registers 1225—in the embodiment illustrated, there are sixteen 64-bit general-purpose registers that are used along with the existing x86 addressing modes to address memory operands. These registers are referenced by the names RAX, RBX, RCX, RDX, RBP, RSI, RDI, RSP, and R8 through R15.

Scalar floating point stack register file (x87 stack) 1245, on which is aliased the MMX packed integer flat register file 1250—in the embodiment illustrated, the x87 stack is an eight-element stack used to perform scalar floating-point operations on 32/64/80-bit floating point data using the x87 instruction set extension; while the MMX registers are used to perform operations on 64-bit packed integer data, as well as to hold operands for some operations performed between the MMX and XMM registers.

Alternative embodiments of the invention may use wider or narrower registers. Additionally, alternative embodiments of the invention may use more, less, or different register files and registers.

FIGS. 13A-B illustrate a block diagram of a more specific exemplary in-order core architecture, which core would be one of several logic blocks (including other cores of the same type and/or different types) in a chip. The logic blocks communicate through a high-bandwidth interconnect network (e.g., a ring network) with some fixed function logic, memory I/O interfaces, and other necessary I/O logic, depending on the application.

FIG. 13A is a block diagram of a single processor core, along with its connection to the on-die interconnect network 1302 and with its local subset of the Level 2 (L2) cache 1304, according to embodiments of the invention. In one embodiment, an instruction decoder 1300 supports the x86 instruction set with a packed data instruction set extension. An L1 cache 1306 allows low-latency accesses to cache memory into the scalar and vector units. While in one embodiment (to simplify the design), a scalar unit 1308 and a vector unit 1310 use separate register sets (respectively, scalar registers 1312 and vector registers 1314) and data transferred between them is written to memory and then read back in from a level 1 (L1) cache 1306, alternative embodiments of the invention may use a different approach (e.g., use a single register set or include a communication path that allow data to be transferred between the two register files without being written and read back).

The local subset of the L2 cache 1304 is part of a global L2 cache that is divided into separate local subsets, one per processor core. Each processor core has a direct access path to its own local subset of the L2 cache 1304. Data read by a processor core is stored in its L2 cache subset 1304 and can be accessed quickly, in parallel with other processor cores accessing their own local L2 cache subsets. Data written by a processor core is stored in its own L2 cache subset 1304 and is flushed from other subsets, if necessary. The ring network ensures coherency for shared data. The ring network is bi-directional to allow agents such as processor cores, L2 caches and other logic blocks to communicate with each other within the chip. Each ring data-path is 1012-bits wide per direction.

FIG. 13B is an expanded view of part of the processor core in FIG. 13A according to embodiments of the invention. FIG. 13B includes an L1 data cache 1306A part of the L1 cache 1304, as well as more detail regarding the vector unit 1310 and the vector registers 1314. Specifically, the vector unit 1310 is a 16-wide vector processing unit (VPU) (see the 16-wide ALU 1328), which executes one or more of integer, single-precision float, and double-precision float instructions. The VPU supports swizzling the register inputs with swizzle unit 1320, numeric conversion with numeric convert units 1322A-B, and replication with replication unit 1324 on the memory input. Write mask registers 1326 allow predicating resulting vector writes.

APPARATUS AND METHOD FOR SELECTING ELEMENTS OF A VECTOR COMPUTATION

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