Virtual register file

Information

  • Patent Grant
  • 10963398
  • Patent Number
    10,963,398
  • Date Filed
    Friday, August 3, 2018
    6 years ago
  • Date Issued
    Tuesday, March 30, 2021
    3 years ago
Abstract
The present disclosure is related to a virtual register file. Source code can be compiled to include references to a virtual register file for data subject to a logical operation. The references can be dereferenced at runtime to obtain physical addresses of memory device elements according to the virtual register file. The logical operation can be performed in the memory device on data stored in the memory device elements.
Description
TECHNICAL FIELD

The present disclosure relates generally to semiconductor memory and methods, and more particularly, to a virtual register file.


BACKGROUND

Memory devices are typically provided as internal, semiconductor, integrated circuits in computing devices or other electronic devices. There are many different types of memory including volatile and non-volatile memory. Volatile memory can require power to maintain its data (e.g., user data, error data, etc.) and includes random-access memory (RAM), dynamic random access memory (DRAM), and synchronous dynamic random access memory (SDRAM), among others. Non-volatile memory can provide persistent data by retaining stored data when not powered and can include NAND flash memory, NOR flash memory, read only memory (ROM), Electrically Erasable Programmable ROM (EEPROM), Erasable Programmable ROM (EPROM), and resistance variable memory such as phase change random access memory (PCRAM), resistive random access memory (RRAM), and magnetoresistive random access memory (MRAM), such as spin torque transfer random access memory (STT RAM), among others.


Computing systems often include a number of processing resources (e.g., one or more processors), which may retrieve and execute instructions and store the results of the executed instructions to a suitable location. A processor can comprise a number of functional units (e.g., herein referred to as functional unit circuitry (FUC)) such as arithmetic logic unit (ALU) circuitry, floating point unit (FPU) circuitry, and/or a combinatorial logic block, for example, which can execute instructions to perform logical operations such as AND, OR, NOT, NAND, NOR, and XOR logical operations on data (e.g., one or more operands).


A number of components in a computing system may be involved in providing instructions to the functional unit circuitry for execution. The instructions may be generated, for instance, by a processing resource such as a controller and/or host processor. Data (e.g., the operands on which the instructions will be executed to perform the logical operations) may be stored in a memory array that is accessible by the FUC. The instructions and/or data may be retrieved from the memory array and sequenced and/or buffered before the FUC begins to execute instructions on the data. Furthermore, as different types of operations may be executed in one or multiple clock cycles through the FUC, intermediate results of the operations and/or data may also be sequenced and/or buffered. In many instances, the processing resources (e.g., processor and/or associated FUC) may be external to the memory array, and data can be accessed (e.g., via a bus between the processing resources and the memory array) to execute instructions. Data can be moved from the memory array to registers external to the memory array via a bus.


A register file is an array of processor registers in a central processing unit (CPU). Integrated circuit-based register files may be implemented, for example, by static random access memory (SRAM). The instruction set architecture of a CPU may define a set of registers used to stage data between memory and the FUC. The register file may be visible to the programmer, as opposed to the cache, which may not be visible to the programmer.





BRIEF DESCRIPTION OF THE DRAWINGS


FIG. 1 is a block diagram of an apparatus in the form of a computing system including at least one memory system in accordance with a number of embodiments of the present disclosure.



FIG. 2 is a schematic diagram of a portion of a memory device in accordance with a number of embodiments of the present disclosure.



FIG. 3 is a block diagram illustrating virtual register file memory translation according to a number of embodiments of the present disclosure.





DETAILED DESCRIPTION

Given the complexity of modern computer architectures, software programmers and software tool chains (e.g., compilers, debuggers, etc.) can have more difficulty extracting efficient performance from a target platform. Adding processing in memory (PIM) devices can further complicate the architecture. Most modern computer architectures use a register-memory technique, where operations are executed in two separate domains. Logical operations (e.g., arithmetic, flow control, and combinatorial operations) are generally executed on a number of register files. Memory operations (e.g., load, store, etc.) are generally executed on memory devices. Instructions in register-memory architectures utilize register indices or memory addresses to indicate how/where to perform an operation.


PIM computing architectures and/or devices can be classified as memory-memory devices in computing architecture taxonomies. This implies that both logical operations and memory operations are performed on the memory devices in-situ. Instructions in memory-memory architectures use physical addresses to indicate how/where to perform an operation.


Modern applications and operating systems use the notions of relocation and virtual addressing, which imply that an application can be loaded or relocated into different physical memory spaces due to the fact that the actual addressing is virtualized. The application and operating system reside in the virtual address space. The hardware and system architecture dereference these virtual addresses to their physical addresses when memory requests are made. However, any system architecture that includes the use of a PIM device that natively relies on physical addressing conflicts with the notion of virtualizing memory.


Some embodiments of the present disclosure can expose low-level memory functionality provided by a PIM device using a register-memory layer. This layer is referred to herein as a virtual register file. The ability to provide register-memory access to a PIM device significantly decreases the level of customization that would otherwise be used in applications for the PIM device via an optimizing compiler. Otherwise, the applications would be customized for each different kind of PIM device or devices included in a system. Providing optimizing compilers and runtime systems with the ability to target what appears to be a register-memory architecture can greatly simplify an implementation that uses a PIM device. Abstracting the physical addressing mechanisms of a PIM device such that virtual addressing may sufficiently exist without collisions can be beneficial for integrating PIM devices with systems that generally operate on a register-memory architecture.


The present disclosure is related to a virtual register file. Source code can be compiled to include references to a virtual register file for data subject to a logical operation. The references can be dereferenced at runtime to obtain physical addresses of memory device elements according to the virtual register file. The logical operation can be performed in the memory device on data stored in the memory device elements.


In the following detailed description of the present disclosure, reference is made to the accompanying drawings that form a part hereof, and in which is shown by way of illustration how a number of embodiments of the disclosure may be practiced. These embodiments are described in sufficient detail to enable those of ordinary skill in the art to practice the embodiments of this disclosure, and it is to be understood that other embodiments may be utilized and that process, electrical, and/or structural changes may be made without departing from the scope of the present disclosure. As used herein, the designators “M” and “N”, particularly with respect to reference numerals in the drawings, indicates that a number of the particular feature so designated can be included. As used herein, “a number of” a particular thing can refer to one or more of such things (e.g., a number of memory devices can refer to one or more memory devices). As used herein, the terms “first” and “second” are used to differentiate between one feature from another and do not necessarily imply an order between the features so designated.


The figures herein follow a numbering convention in which the first digit or digits correspond to the drawing figure number and the remaining digits identify an element or component in the drawing. Similar elements or components between different figures may be identified by the use of similar digits. For example, 110 may reference element “10” in FIG. 1, and a similar element may be referenced as 210 in FIG. 2. Multiple analogous elements within one figure may be referenced with a reference numeral followed by a hyphen and another numeral or a letter. For example, 240-1 may reference element 20-1 in FIGS. 2 and 240-N may reference element 40-N, which can be analogous to element 240-1. Such analogous elements may be generally referenced without the hyphen and extra numeral or letter. For example, elements 240-1, . . . , 240-N may be generally referenced as 440. As will be appreciated, elements shown in the various embodiments herein can be added, exchanged, and/or eliminated so as to provide a number of additional embodiments of the present disclosure. In addition, as will be appreciated, the proportion and the relative scale of the elements provided in the figures are intended to illustrate certain embodiments of the present invention, and should not be taken in a limiting sense.



FIG. 1 is a block diagram of an apparatus in the form of a computing system 100 including at least one memory system 104 in accordance with a number of embodiments of the present disclosure. As used herein, a host 102, a memory system 104, a memory device 110, a memory array 111, and/or sensing circuitry 124 might also be separately considered an “apparatus.”


The computing system 100 can include a host 102 coupled to memory system 104, which includes a memory device 110 (e.g., including a memory array 111 and/or sensing circuitry 124). The host 102 can be a host system such as a personal laptop computer, a desktop computer, a digital camera, a mobile telephone, or a memory card reader, among various other types of hosts. The host 102 can include a system motherboard and/or backplane and can include a number of processing resources (e.g., one or more processors, microprocessors, or some other type of controlling circuitry), such as central processing unit (CPU) 106. The CPU 106 can be coupled to secondary storage 114 and to main memory 112 via a memory bus 116. The secondary storage 114 can be a storage device or other media not directly accessible by the CPU 106 such as hard disk drives, solid state drives, optical disc drives, and can be non-volatile memory. The main memory 112 is directly accessible by the CPU 106. The main memory 112 can be volatile memory such as DRAM. The memory bus 116 can be analogous to the control bus 136 and the I/O bus 138, but for communication between the CPU 106 and the main memory 112 instead of for communication between the host 102 and the memory system 104. The CPU 106 can include a logic unit 118 coupled to a number of registers 120 and cache 122. The cache 122 can be an intermediate stage between the relatively faster registers 120 and the relatively slower main memory 112. Data to be operated on by the CPU 106 may be copied to cache 122 before being placed in a register 120, where the operations can be effected by the logic unit 118. Although not specifically illustrated, the cache 122 can be a multilevel hierarchical cache.


The computing system 100 can include separate integrated circuits or both the host 102 and the memory system 104 can be on the same integrated circuit. The computing system 100 can be, for instance, a server system and/or a high performance computing system and/or a portion thereof. Although the example shown in FIG. 1 illustrates a system having a Von Neumann architecture, embodiments of the present disclosure can be implemented in non-Von Neumann architectures (e.g., a Turing machine), which may not include one or more components (e.g., CPU, ALU, etc.) often associated with a Von Neumann architecture.


For clarity, the computing system 100 has been simplified to focus on features with particular relevance to the present disclosure. The memory array 111 can be a hybrid memory cube (HMC), processing in memory random access memory (PIMRAM) array, DRAM array, SRAM array, STT RAM array, PCRAM array, TRAM array, RRAM array, NAND flash array, and/or NOR flash array, for instance. The memory array 111 can comprise memory cells arranged in rows coupled by access lines (which may be referred to herein as word lines or select lines) and columns coupled by sense lines (which may be referred to herein as digit lines or data lines). Although a single memory device 110 is shown in FIG. 1, embodiments are not so limited. For instance, memory system 104 may include a number of memory devices 110 (e.g., a number of banks of DRAM cells).


The memory system 104 can include address circuitry 126 to latch address signals provided over an I/O bus 138 (e.g., a data bus) through I/O circuitry 130. Address signals can be received and decoded by a row decoder 128 and a column decoder 134 to access the memory device 110. Data can be read from the memory array 111 by sensing voltage and/or current changes on the sense lines using sensing circuitry 124. The sensing circuitry 124 can read and latch a page (e.g., row) of data from the memory array 111. The I/O circuitry 130 can be used for bi-directional data communication with host 102 over the I/O bus 138. The write circuitry 132 can be used to write data to the memory device 110.


Controller 108 can decode signals provided by control bus 136 from the host 102. These signals can include chip enable signals, write enable signals, and address latch signals that are used to control memory operations performed on the memory device 110, including data read, data write, and data erase operations. The signals can also be used to control logical operations performed on the memory device 110 including arithmetic, flow control, and combinatorial operations, among others. In various embodiments, the controller 108 is responsible for executing instructions from the host 102. The controller 108 can be a state machine, a sequencer, a processor, and/or other control circuitry.


An example of the sensing circuitry 124 is described further below in association with FIG. 2. For instance, in a number of embodiments, the sensing circuitry 124 can comprise a number of sense amplifiers and a number of compute components, which may comprise a latch serving as an accumulator and that can be used to perform logical operations (e.g., on data associated with complementary sense lines). Logical operations can include Boolean operations (e.g., AND, OR, NOR, XOR, etc.), combinations of Boolean operations to perform other mathematical operations, as well as non-Boolean operations. In a number of embodiments, the sensing circuitry 124 can be used to perform logical operations using data stored in the memory array 111 as inputs and store the results of the logical operations back to the memory array 111 without transferring via a sense line address access (e.g., without firing a column decode signal). As such, a logical operation can be performed using sensing circuitry 124 rather than and/or in addition to being performed by processing resources external to the sensing circuitry 124 (e.g., by the host CPU 106 and/or other processing circuitry, such as ALU circuitry, located on the memory system 104, such as on the controller 108, or elsewhere).


In various previous approaches, data associated with a logical operation, for instance, would be read from memory via sensing circuitry and provided to registers 120 associated with the host CPU 106. A logic unit 118 of the host CPU 106 would perform the logical operations using the data (which may be referred to as operands or inputs) from the memory array 111 in the registers 120 and the result could be transferred back to the memory array 111 via the local I/O lines. In contrast, in a number of embodiments of the present disclosure, sensing circuitry 124 can be configured to perform a logical operation on data stored in memory cells in memory array 111 and store the result back to the array 111 without enabling a local I/O line coupled to the sensing circuitry and without using registers 120 of the host CPU 106.


As such, in a number of embodiments, registers 126 and/or a logic unit 118 of a host CPU 106 external to the memory array 111 and sensing circuitry 124 may not be needed to perform the logical operation as the sensing circuitry 124 can be operated to perform the logical operation using the address space of memory array 111. Additionally, the logical operation can be performed without the use of an external processing resource.


The host 102 can be configured with an operating system. The host 102 can be coupled to the memory device 110 (e.g., via the control bus 136 and/or the I/O bus 138). The operating system is executable instructions (software) that manages hardware resources and provides services other executable instructions (applications) that run on the operating system. The operating system can implement a virtual memory system.


According to the present disclosure, the CPU 106 can execute instructions to define a buffer in the main memory 112 of the host 102 with sufficient space to contain backing storage for a virtual register file (VRF) 117. The instructions can be executed to logically split the buffer into a number of virtual vector registers (VVR) 119, a number virtual scalar registers (VSR) 121, and a number of virtual control registers (VCR) 123, among other virtualized components as described herein, which collectively define the virtual register file 117. The host 102 can create the virtual register file 117 at runtime. These virtual registers 119, 121, 123 can represent a number of the registers 120 of the CPU 106 (e.g., physical vector registers, physical scalar registers, and/or physical control registers) for logical operations to be performed in the memory device 110. The virtual registers can represent physical registers 120 of the CPU 106 with respective indices to the virtual register file 117 at compile time as described in more detail in association with FIG. 3. The virtual register file 117, specifically, the virtual vector registers 119 can store virtual addresses (e.g., base virtual addresses) of elements of the memory device 110 (e.g., the PIM memory device 110 illustrated in FIG. 1). A memory element (also referred to as a computational element) stores an amount of data that is operated on in one logical operation. The memory element can refer to a number of memory cells that store the amount of data. Memory-memory architectures may be prohibitively difficult to expose to high performance software and compiler implementations.


In some embodiments, the host 102 can include a memory management unit (MMU) 115. The MMU 115 is a hardware component that can perform translation between virtual memory addresses and physical memory addresses. That is, the MMU 115 can translate the virtual memory addresses stored in the virtual register file 117 to physical addresses of the elements of the memory device 110. Thus, the virtual register file 117 does not store the physical addresses of the elements of the memory device 110. In this regard, the virtual register file 117 does not need to be updated when data is moved within the memory device 110. Furthermore, unlike physical registers 120 associated with the CPU 106 for operations on data stored in the main memory 112, the virtual registers in the virtual register file 117 do not receive or store data corresponding to the elements of the memory device 110.



FIG. 2 is a schematic diagram of a portion of a memory device 210 in accordance with a number of embodiments of the present disclosure. The memory device 210 is analogous to the memory device 110 illustrated in FIG. 1. The memory device 210 can include a memory array 211 that includes memory cells 240-1, 240-2, 240-3, 240-4, 240-5, 240-6, 240-7, 240-8, . . . , 240-N coupled to rows of access lines 242-1, 242-2, 242-3, 242-4, 242-5, 242-6, 242-7, . . . , 242-M and columns of sense lines 244-1, 244-2, 244-3, 244-4, 244-5, 244-6, 244-7, 244-8, . . . , 244-N. The memory array 211 is not limited to a particular number of access lines and/or sense lines, and use of the terms “rows” and “columns” does not intend a particular physical structure and/or orientation of the access lines and/or sense lines. Although not pictured, each column of memory cells can be associated with a corresponding pair of complementary sense lines.


Each column of memory cells can be coupled to sensing circuitry 224, which can be analogous to sensing circuitry 124 illustrated in FIG. 1. In this example, the sensing circuitry includes a number of sense amplifiers 246-1, 246-2, 246-3, 246-4, 246-5, 246-6, 246-7, 246-8, . . . , 246-N coupled to the respective sense lines 244. The sense amplifiers 246 are coupled to input/output (I/O) line 254 (e.g., a local I/O line) via access devices (e.g., transistors) 250-1, 250-2, 250-3, 250-4, 250-5, 250-6, 250-7, 250-8, . . . , 250-N. In this example, the sensing circuitry also includes a number of compute components 248-1, 248-2, 248-3, 248-4, 248-5, 248-6, 248-7, 248-8, . . . , 248-N coupled to the respective sense lines 244. Column decode lines 252-1, 252-2, 252-3, 252-4, 252-5, 252-6, 252-7, 252-8, . . . , 252-N are coupled to the gates of access devices 250 respectively, and can be selectively activated to transfer data sensed by respective sense amps 246 and/or stored in respective compute components 248 to a secondary sense amplifier 256. In a number of embodiments, the compute components 248 can be formed on pitch with the memory cells of their corresponding columns and/or with the corresponding sense amplifiers 246.


In a number of embodiments, the sensing circuitry (e.g., compute components 248 and sense amplifiers 246) is configured to perform a number of logical operations on elements stored in array 211. As an example, a first plurality of elements can be stored in a first group of memory cells coupled to a particular access line (e.g., access line 242-1) and to a number of sense lines 244, and a second plurality of elements can be stored in a second group of memory cells coupled to a different access line (e.g., access line 242-2) and the respective number of sense lines 244. Each element of the first plurality of elements can have a logical operation performed thereon with a respective one of the second plurality of elements, and the result of the logical operation can be stored (e.g., as a bit-vector) in a third group of memory cells coupled to a particular access line (e.g., access line 242-3) and to the number of sense lines 244.



FIG. 3 is a block diagram illustrating virtual register file memory translation according to a number of embodiments of the present disclosure. The host (e.g., host 102 illustrated in FIG. 1) can compile source code 360, such as C, C++, etc., with a compiler 362. The source code 360 can be compiled to include references to a virtual register file 317 for data subject to a logical operation. The compiler 362 can be configured to emit compiled code 364 (e.g., machine code, object code, etc.) with references to the virtual register file 317 in terms of indices to virtual vector registers in the virtual register file 317. The source code 360 can be compiled to target the virtual register file 317 for logical operations to be performed in the memory device 310 as though the logical operations were to be performed in the virtual register file 317 on the host (e.g., host 102 illustrated in FIG. 1). That is, the virtual register file 317 can be targeted as though it was a physical register (e.g., physical register 120 illustrated in FIG. 1) for the host device even though the actual logical operation is to be performed in the memory device 310 on the memory system (e.g., memory system 104 illustrated in FIG. 1).


In order to provide functionality for programmers and compilers to generate code for the memory device 310, the virtual register file 317 is defined as the basis for the mapping between virtualized memory devices and the actual processing and memory hardware. Some previous source code compiler technology was made aware of or targeted a fixed set of mutable (changeable) hardware elements for the purpose of safe code generation. This hardware would generally include computational elements (e.g., logic unit 118 illustrated in FIG. 1) and register files (e.g., registers 120 illustrated in FIG. 1). However, the memory device 310 does not have mutable register files. Operations are to be performed at or near the physical row and column intersection of the memory array (e.g., memory array 111 illustrated in FIG. 1) or in the in-situ storage in the memory device (e.g., memory device 110 illustrated in FIG. 1). If the memory device 310 were to function according to some previous compiler approaches, each memory cell in the memory device 310 would become a mutable and allocable hardware element, which could prevent applications from executing alongside one another in virtual memory.


The virtual register file 317 can virtualize access to the memory cells of the memory device 310. The virtual register file 317 can be stored in a buffer in memory (e.g., main memory 112 of a host 102 illustrated in FIG. 1) and can function similar to a register file, except that the actual data to be operated on is not transferred to the virtual register file 317, or even to the host, because the operation is to be performed in the memory device 310 at runtime, rather than performing the logical operation with the host. The virtual register file 317 can be configured to store addresses of respective target elements rather than the actual data. There is no motivation to virtualize a physical register used according to some previous approaches because the physical register receives the data to be operated on by a logic unit of the host.


The entries in the virtual register file 317 can be translated at runtime from virtual address contents to respective physical addresses such that steps can be taken to initiate a logical operation using the memory device 310. Each element of the buffer that provides the backing storage for the virtual register file can be of a particular size (e.g., 64 bits) such that the buffer may be indexed analogously to a register file according to some previous approaches. The compiler 362 can be configured to target the virtual register file 317 as opposed to physical hardware entities (e.g., registers 120 illustrated in FIG. 1) for operations to be performed in the memory device 310.


The compiled code 364 can include logical operations 368 and references 366 to the virtual register file 317, however the compiled code will not include a physical address corresponding to the virtual address associated with the virtual vector register. Some examples of the logical operations include add, subtract, multiply, etc. A particular reference 366 can be an index (e.g., % v0, % v1, . . . , etc.) to the virtual register file 317. A particular index can point to a virtual register in the virtual register file 317, such as a virtual vector register, a virtual scalar register, and/or a virtual control register, among others.


A respective index to the virtual register file 317 can represent a vector register or a scalar register with a fixed amount of backing storage of the virtual register file 317. A respective index to the virtual register file 317 can represent a control register with a variable amount of the backing storage. Virtual addresses for elements of the memory device 310 can be stored in virtual vector registers of the virtual register file 317.


At runtime, the references to the virtual register file can be dereferenced (e.g., by virtual to physical translation 374) to obtain physical address of memory device elements. The dereferencing (e.g., virtual to physical translation 374) can include use of the runtime environment of the memory device 310 and/or use of a memory management unit of the host (e.g., the MMU 115 of the host 102 illustrated in FIG. 1). The logical operation can then be performed in the memory device 310 on data that was stored in the memory device elements.


In some embodiments, the virtual register file 317 can also be used for memory operations (in addition to logical operations). For example, the source code 360 can be compiled to include a reference to the virtual register file 317 for data subject to a memory operation. The reference to the virtual register file can be dereferenced at runtime to obtain a physical address of a memory device element according to the virtual register file 317.


The following table illustrates an example of a virtual register file structure including indices, mnemonics, and descriptions of a number of components of the virtual register file:











TABLE 1





Index
Mnemonic
Description







0x00-0x0F
T0-T15
Temporary Row Registers


0x14-0x17
B0-B3
Bank Registers


0x1A
CB
Bank Control Register


0x1B
ACC0
Accumulator


0x20-0x3F
V0-V31
Vector Registers


0x40-0x5F
S0-S31
Scalar Registers


0x60
VL
Vector Length (in elements)


0x61
VS
Vector Stride (in bits)


0x62
VF
Vector First


0x63
AB
Arbitrary Bit Integer Width (in bits)


0x64
FRAC
Arbitrary Float/Fixed Fractional Width (in bits)


0x65
EXP
Arbitrary Float/Fixed Exponent Width (in bits)


0x66
SP
Stack Pointer


0x67
FP
Frame Pointer


0x68
RP
Return Pointer


0x69
AP
Argument Pointer


0x6A
EMASK
Exception Mask


0x6B
DMASK
Device Mask


0x6C
BMASK
Bank Mask


0x70
MAXROW
Number of rows in subarray


0x71
MAXCOL
Number of columns in subarray


0x72
MAXSA
Number of subarrays in bank


0x73
MAXBANK
Number of banks in device


0x74
MAXDEV
Number of devices in system


0x75
MAXTMP
Number of temporary rows in subarray


0x76
VLMAX.H
Maximum horizontal vector length (in bits)


0x77
VMLAX.V
Maximum vertical vector length (in bits)


0x78
CONFIG
Config register









Although not specifically illustrated in the table above, the virtual register file 317 can store virtual addresses corresponding to physical addresses of elements of the memory device 310. In some embodiments, the virtual memory address can be a base virtual memory address, which in combination with a stored stride of memory device elements and a length of memory device elements together with the translated base virtual address, define which memory device elements correspond to the virtual vector register that stores the virtual memory address. However, the virtual register file 317 does not store physical addresses of the elements of the memory device 310.


Virtual to physical translation 374 can occur at runtime according to the runtime library 372, which can be part of the runtime environment of the host and/or the memory device 310. The translation can occur in response to a command calling for a logical operation to be performed in the memory device 310. For example, the compiled source code 364 can be executed to cause the logical operation to be performed in the memory device. The logical operation can be initialized according to a portion of the compiled source code 364 that addresses a particular virtual address. The logical operation can be performed in the memory device 310 on data stored in a particular physical address corresponding to the particular virtual address.


The runtime library 372 can be loaded by an application running on the host. For example, the runtime library 372 and the virtual register file 317 can be loaded into main memory of the host. Although not specifically illustrated as such, the runtime library 372 can create and/or contain the virtual register file 317 including virtual memory addresses of memory device elements. In some embodiments, each running thread can be associated with one virtual register file 317. The virtual register file 317 can be mapped to a particular memory bank of the memory device 310 at runtime, but can later be mapped to a different bank. For example, the memory device 310 can include multiple banks, each including a number of subarrays. The application that is running on the host can be relocated in the main memory of the host without editing the virtual register file 317, while maintaining the functionality provided by the virtual register file 317.


Although not specifically illustrated as such, a non-transitory computing device readable medium for storing executable instructions can include all forms of volatile and non-volatile memory, including, by way of example, semiconductor memory devices, DRAM, PIM, HMC, EPROM, EEPROM, flash memory devices, magnetic disks such as fixed, floppy, and removable disks, other magnetic media including tape, optical media such as compact discs (CDs), digital versatile discs (DVDs), and Blu-Ray discs (BD). The instructions may be supplemented by, or incorporated in, ASICs. For example, any one or more of the secondary storage 114, the registers 120, the cache 122, the main memory 112, and/or the memory array 111 illustrated in FIG. 1, can be a non-transitory computing device readable medium.


Although specific embodiments have been illustrated and described herein, those of ordinary skill in the art will appreciate that an arrangement calculated to achieve the same results can be substituted for the specific embodiments shown. This disclosure is intended to cover adaptations or variations of one or more embodiments of the present disclosure. It is to be understood that the above description has been made in an illustrative fashion, and not a restrictive one. Combination of the above embodiments, and other embodiments not specifically described herein will be apparent to those of skill in the art upon reviewing the above description. The scope of the one or more embodiments of the present disclosure includes other applications in which the above structures and methods are used. Therefore, the scope of one or more embodiments of the present disclosure should be determined with reference to the appended claims, along with the full range of equivalents to which such claims are entitled.


In the foregoing Detailed Description, some features are grouped together in a single embodiment for the purpose of streamlining the disclosure. This method of disclosure is not to be interpreted as reflecting an intention that the disclosed embodiments of the present disclosure have to use more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive subject matter lies in less than all features of a single disclosed embodiment. Thus, the following claims are hereby incorporated into the Detailed Description, with each claim standing on its own as a separate embodiment.

Claims
  • 1. A non-transitory computer readable medium storing instructions executable by a processor to: define a buffer in host memory with sufficient space to contain backing storage for a virtual register file;logically split the buffer into virtual vector registers, virtual scalar registers, and virtual control registers, collectively comprising the virtual register file; andrepresent a vector register, a scalar register, and a control register with a respective index to the virtual register file at compile time.
  • 2. The medium of claim 1, including instructions to reference the vector register and the virtual scalar register with a respective index to the virtual register file for a fixed amount of the backing storage.
  • 3. The medium of claim 1, including instructions to reference the control register with a respective index to the virtual register file for a variable amount of the backing storage.
  • 4. The medium of claim 1, including instructions to store a base virtual address of a memory device element in the virtual vector register.
  • 5. A method, comprising: defining a buffer in host memory with sufficient space to contain backing storage for a virtual register file;logically splitting the buffer into virtual vector registers, virtual scalar registers, and virtual control registers, collectively comprising the virtual register file; andrepresenting a vector register, a scalar register, and a control register with a respective index to the virtual register file at compile time.
  • 6. The method of claim 5, further comprising referencing the vector register and the virtual scalar register with a respective index to the virtual register file for a fixed amount of the backing storage.
  • 7. The method of claim 5, further comprising referencing the control register with a respective index to the virtual register file for a variable amount of the backing storage.
  • 8. The method of claim 5, further comprising storing a base virtual address of a memory device element in the virtual vector register.
  • 9. An apparatus, comprising: a processor; andmemory coupled to the processor;wherein the processor is configured to: define a buffer in the memory with sufficient space to contain backing storage for a virtual register file;logically split the buffer into virtual vector registers, virtual scalar registers, and virtual control registers, collectively comprising the virtual register file; andrepresent a vector register, a scalar register, and a control register with a respective index to the virtual register file at compile time.
  • 10. The apparatus of claim 9, wherein the processor is further configured to reference the vector register and the virtual scalar register with a respective index to the virtual register file for a fixed amount of the backing storage.
  • 11. The apparatus of claim 9, wherein the processor is further configured to reference the control register with a respective index to the virtual register file for a variable amount of the backing storage.
  • 12. The apparatus of claim 9, wherein the processor is further configured to store a base virtual address of an external memory device element in the virtual vector register.
PRIORITY INFORMATION

This application is a Continuation of U.S. application Ser. No. 15/085,631, filed Mar. 30, 2016, which issues as U.S. Pat. No. 10,049,054 on Aug. 14, 2018, which claims the benefit of U.S. Provisional Application No. 62/141,601, filed Apr. 1, 2015, the contents of which are included herein by reference.

US Referenced Citations (279)
Number Name Date Kind
4380046 Fung Apr 1983 A
4435792 Bechtolsheim Mar 1984 A
4435793 Ochii Mar 1984 A
4727474 Batcher Feb 1988 A
4843264 Galbraith Jun 1989 A
4958378 Bell Sep 1990 A
4977542 Matsuda et al. Dec 1990 A
5023838 Herbert Jun 1991 A
5034636 Reis et al. Jul 1991 A
5201039 Sakamura Apr 1993 A
5210850 Kelly et al. May 1993 A
5253308 Johnson Oct 1993 A
5276643 Hoffmann et al. Jan 1994 A
5325519 Long et al. Jun 1994 A
5367488 An Nov 1994 A
5379257 Matsumura et al. Jan 1995 A
5386379 Ali-Yahia et al. Jan 1995 A
5398213 Yeon et al. Mar 1995 A
5440482 Davis Aug 1995 A
5446690 Tanaka et al. Aug 1995 A
5473576 Matsui Dec 1995 A
5481500 Reohr et al. Jan 1996 A
5485373 Davis et al. Jan 1996 A
5506811 McLaury Apr 1996 A
5615404 Knoll et al. Mar 1997 A
5638128 Hoogenboom Jun 1997 A
5638317 Tran Jun 1997 A
5654936 Cho Aug 1997 A
5678021 Pawate et al. Oct 1997 A
5724291 Matano Mar 1998 A
5724366 Furutani Mar 1998 A
5751987 Mahant-Shetti et al. May 1998 A
5787458 Miwa Jul 1998 A
5854636 Watanabe et al. Dec 1998 A
5867429 Chen et al. Feb 1999 A
5870504 Nemoto et al. Feb 1999 A
5915084 Wendell Jun 1999 A
5920881 Porterfield Jul 1999 A
5935263 Keeth et al. Aug 1999 A
5986942 Sugibayashi Nov 1999 A
5991209 Chow Nov 1999 A
5991785 Alidina et al. Nov 1999 A
6005799 Rao Dec 1999 A
6009020 Nagata Dec 1999 A
6092186 Betker et al. Jul 2000 A
6122211 Morgan et al. Sep 2000 A
6125071 Kohno et al. Sep 2000 A
6134164 Lattimore et al. Oct 2000 A
6147514 Shiratake Nov 2000 A
6151244 Fujino et al. Nov 2000 A
6157578 Brady Dec 2000 A
6163862 Adams et al. Dec 2000 A
6166942 Vo et al. Dec 2000 A
6172918 Hidaka Jan 2001 B1
6175514 Henderson Jan 2001 B1
6178482 Sollars et al. Jan 2001 B1
6181698 Hariguchi Jan 2001 B1
6208544 Beadle et al. Mar 2001 B1
6226215 Yoon May 2001 B1
6301153 Takeuchi et al. Oct 2001 B1
6301164 Manning et al. Oct 2001 B1
6304477 Naji Oct 2001 B1
6389507 Sherman May 2002 B1
6418498 Martwick Jul 2002 B1
6466499 Blodgett Oct 2002 B1
6510098 Taylor Jan 2003 B1
6563754 Lien et al. May 2003 B1
6578058 Nygaard Jun 2003 B1
6731542 Le et al. May 2004 B1
6754746 Leung et al. Jun 2004 B1
6768679 Le et al. Jul 2004 B1
6807614 Chung Oct 2004 B2
6816422 Hamade et al. Nov 2004 B2
6819612 Achter Nov 2004 B1
6894549 Eliason May 2005 B2
6943579 Hazanchuk et al. Sep 2005 B1
6948056 Roth et al. Sep 2005 B1
6950771 Fan et al. Sep 2005 B1
6950898 Merritt et al. Sep 2005 B2
6956770 Khalid et al. Oct 2005 B2
6961272 Schreck Nov 2005 B2
6965648 Smith et al. Nov 2005 B1
6985394 Kim Jan 2006 B2
6987693 Cernea et al. Jan 2006 B2
7020017 Chen et al. Mar 2006 B2
7028170 Saulsbury Apr 2006 B2
7045834 Tran et al. May 2006 B2
7054178 Shiah et al. May 2006 B1
7061817 Raad et al. Jun 2006 B2
7079407 Dimitrelis Jul 2006 B1
7173857 Kato et al. Feb 2007 B2
7187585 Li et al. Mar 2007 B2
7196928 Chen Mar 2007 B2
7260565 Lee et al. Aug 2007 B2
7260672 Garney Aug 2007 B2
7372715 Han May 2008 B2
7400532 Aritome Jul 2008 B2
7406494 Magee Jul 2008 B2
7447720 Beaumont Nov 2008 B2
7454451 Beaumont Nov 2008 B2
7457181 Lee et al. Nov 2008 B2
7535769 Cernea May 2009 B2
7546438 Chung Jun 2009 B2
7562198 Noda et al. Jul 2009 B2
7574466 Beaumont Aug 2009 B2
7602647 Li et al. Oct 2009 B2
7663928 Tsai et al. Feb 2010 B2
7685365 Rajwar et al. Mar 2010 B2
7692466 Ahmadi Apr 2010 B2
7752417 Manczak et al. Jul 2010 B2
7791962 Noda et al. Sep 2010 B2
7796453 Riho et al. Sep 2010 B2
7805587 Van Dyke et al. Sep 2010 B1
7808854 Takase Oct 2010 B2
7827372 Bink et al. Nov 2010 B2
7869273 Lee et al. Jan 2011 B2
7898864 Dong Mar 2011 B2
7924628 Danon et al. Apr 2011 B2
7937535 Ozer et al. May 2011 B2
7957206 Bauser Jun 2011 B2
7979667 Allen et al. Jul 2011 B2
7996749 Ding et al. Aug 2011 B2
8042082 Solomon Oct 2011 B2
8045391 Mohklesi Oct 2011 B2
8059438 Chang et al. Nov 2011 B2
8095825 Hirotsu et al. Jan 2012 B2
8117462 Snapp et al. Feb 2012 B2
8164942 Gebara et al. Apr 2012 B2
8208328 Hong Jun 2012 B2
8213248 Moon et al. Jul 2012 B2
8223568 Seo Jul 2012 B2
8238173 Akerib et al. Aug 2012 B2
8274841 Shimano et al. Sep 2012 B2
8279683 Klein Oct 2012 B2
8310884 Iwai et al. Nov 2012 B2
8332367 Bhattacherjee et al. Dec 2012 B2
8339824 Cooke Dec 2012 B2
8339883 Yu et al. Dec 2012 B2
8347154 Bahali et al. Jan 2013 B2
8351292 Matano Jan 2013 B2
8356144 Hessel et al. Jan 2013 B2
8417921 Gonion et al. Apr 2013 B2
8462532 Argyres Jun 2013 B1
8484276 Carlson et al. Jul 2013 B2
8495438 Roine Jul 2013 B2
8503250 Demone Aug 2013 B2
8526239 Kim Sep 2013 B2
8533245 Cheung Sep 2013 B1
8555037 Gonion Oct 2013 B2
8599613 Abiko et al. Dec 2013 B2
8605015 Guttag et al. Dec 2013 B2
8625376 Jung et al. Jan 2014 B2
8644101 Jun et al. Feb 2014 B2
8650232 Stortz et al. Feb 2014 B2
8873272 Lee Oct 2014 B2
8964496 Manning Feb 2015 B2
8971124 Manning Mar 2015 B1
9015390 Klein Apr 2015 B2
9047193 Lin et al. Jun 2015 B2
9104436 Michaud Aug 2015 B1
9165023 Moskovich et al. Oct 2015 B2
20010007112 Porterfield Jul 2001 A1
20010008492 Higashiho Jul 2001 A1
20010010057 Yamada Jul 2001 A1
20010028584 Nakayama et al. Oct 2001 A1
20010043089 Forbes et al. Nov 2001 A1
20020059355 Peleg et al. May 2002 A1
20030167426 Slobodnik Sep 2003 A1
20030222879 Lin et al. Dec 2003 A1
20040073592 Kim et al. Apr 2004 A1
20040073773 Demjanenko Apr 2004 A1
20040085840 Vali et al. May 2004 A1
20040095826 Perner May 2004 A1
20040154002 Ball et al. Aug 2004 A1
20040205289 Srinivasan Oct 2004 A1
20040240251 Nozawa et al. Dec 2004 A1
20050015557 Wang et al. Jan 2005 A1
20050021925 Clark et al. Jan 2005 A1
20050078514 Scheuerlein et al. Apr 2005 A1
20050097417 Agrawal et al. May 2005 A1
20050226337 Dorojevets et al. Oct 2005 A1
20060047937 Selvaggi et al. Mar 2006 A1
20060069849 Rudelic Mar 2006 A1
20060146623 Mizuno et al. Jul 2006 A1
20060149804 Luick et al. Jul 2006 A1
20060181917 Kang et al. Aug 2006 A1
20060215432 Wickeraad et al. Sep 2006 A1
20060225072 Lari et al. Oct 2006 A1
20060265575 Damron Nov 2006 A1
20060291282 Liu et al. Dec 2006 A1
20070094484 Rychlik Apr 2007 A1
20070103986 Chen May 2007 A1
20070171747 Hunter et al. Jul 2007 A1
20070180006 Gyoten et al. Aug 2007 A1
20070180184 Sakashita et al. Aug 2007 A1
20070195602 Fong et al. Aug 2007 A1
20070285131 Sohn Dec 2007 A1
20070285979 Turner Dec 2007 A1
20070291532 Tsuji Dec 2007 A1
20080025073 Arsovski Jan 2008 A1
20080037333 Kim et al. Feb 2008 A1
20080052711 Forin et al. Feb 2008 A1
20080137388 Krishnan et al. Jun 2008 A1
20080165601 Matick et al. Jul 2008 A1
20080178053 Gorman et al. Jul 2008 A1
20080215937 Dreibelbis et al. Sep 2008 A1
20090067218 Graber Mar 2009 A1
20090106478 Okin et al. Apr 2009 A1
20090154238 Lee Jun 2009 A1
20090154273 Borot et al. Jun 2009 A1
20090254697 Akerib Oct 2009 A1
20100067296 Li Mar 2010 A1
20100091582 Vali et al. Apr 2010 A1
20100172190 Lavi et al. Jul 2010 A1
20100210076 Gruber et al. Aug 2010 A1
20100226183 Kim Sep 2010 A1
20100308858 Noda et al. Dec 2010 A1
20100332895 Billing et al. Dec 2010 A1
20110051523 Manabe et al. Mar 2011 A1
20110063919 Chandrasekhar et al. Mar 2011 A1
20110093662 Walker et al. Apr 2011 A1
20110103151 Kim et al. May 2011 A1
20110119467 Cadambi et al. May 2011 A1
20110122695 Li et al. May 2011 A1
20110140741 Zerbe et al. Jun 2011 A1
20110219260 Nobunaga et al. Sep 2011 A1
20110267883 Lee et al. Nov 2011 A1
20110317496 Bunce et al. Dec 2011 A1
20120005397 Lim et al. Jan 2012 A1
20120017039 Margetts Jan 2012 A1
20120023281 Kawasaki et al. Jan 2012 A1
20120120705 Mitsubori et al. May 2012 A1
20120134216 Singh May 2012 A1
20120134225 Chow May 2012 A1
20120134226 Chow May 2012 A1
20120140540 Agam et al. Jun 2012 A1
20120159193 Spradlin Jun 2012 A1
20120182798 Hosono et al. Jul 2012 A1
20120195146 Jun et al. Aug 2012 A1
20120198310 Tran et al. Aug 2012 A1
20120246380 Akerib et al. Sep 2012 A1
20120265964 Murata et al. Oct 2012 A1
20120281486 Rao et al. Nov 2012 A1
20120303627 Keeton et al. Nov 2012 A1
20130003467 Klein Jan 2013 A1
20130024647 Gove Jan 2013 A1
20130061006 Hein Mar 2013 A1
20130107623 Kavalipurapu et al. May 2013 A1
20130117541 Choquette et al. May 2013 A1
20130124783 Yoon et al. May 2013 A1
20130132702 Patel et al. May 2013 A1
20130138646 Sirer et al. May 2013 A1
20130163362 Kim Jun 2013 A1
20130173888 Hansen et al. Jul 2013 A1
20130205114 Badam et al. Aug 2013 A1
20130219112 Okin et al. Aug 2013 A1
20130227213 Choi Aug 2013 A1
20130227361 Bowers et al. Aug 2013 A1
20130283122 Anholt et al. Oct 2013 A1
20130286705 Grover et al. Oct 2013 A1
20130326154 Haswell Dec 2013 A1
20130332707 Gueron et al. Dec 2013 A1
20140129799 Fleischer et al. May 2014 A1
20140185395 Seo Jul 2014 A1
20140215185 Danielsen Jul 2014 A1
20140250279 Manning Sep 2014 A1
20140281366 Felch Sep 2014 A1
20140344934 Jorgensen Nov 2014 A1
20150029798 Manning Jan 2015 A1
20150042380 Manning Feb 2015 A1
20150063052 Manning Mar 2015 A1
20150078108 Cowles et al. Mar 2015 A1
20150086012 Chhabra Mar 2015 A1
20150134713 Wheeler May 2015 A1
20150279466 Manning Oct 2015 A1
20150324290 Leidel Nov 2015 A1
20150325272 Murphy Nov 2015 A1
20160092675 Vidrine Mar 2016 A1
20160179700 Venkatasubramanian Jun 2016 A1
Foreign Referenced Citations (13)
Number Date Country
102141905 Aug 2011 CN
0214718 Mar 1987 EP
2026209 Feb 2009 EP
H0831168 Feb 1996 JP
2009259193 Mar 2015 JP
10-0211482 Aug 1998 KR
10-2010-0134235 Dec 2010 KR
10-2013-0049421 May 2013 KR
2001065359 Sep 2001 WO
2010079451 Jul 2010 WO
2013062596 May 2013 WO
2013081588 Jun 2013 WO
2013095592 Jun 2013 WO
Non-Patent Literature Citations (20)
Entry
Boyd et al., “On the General Applicability of Instruction-Set Randomization”, Jul.-Sep. 2010, (14 pgs.), vol. 7, Issue 3, IEEE Transactions on Dependable and Secure Computing.
Stojmenovic, “Multiplicative Circulant Networks Topological Properties and Communication Algorithms”, (25 pgs.), Discrete Applied Mathematics 77 (1997) 281-305.
“4.9.3 MINLOC and MAXLOC”, Jun. 12, 1995, (5pgs.), Message Passing Interface Forum 1.1, retrieved from http://www.mpi-forum.org/docs/mpi-1.1/mpi-11-html/node79.html.
Derby, et al., “A High-Performance Embedded DSP Core with Novel SIMD Features”, Apr. 6-10, 2003, (4 pgs), vol. 2, pp. 301-304, 2003 IEEE International Conference on Accoustics, Speech, and Signal Processing.
Debnath, Biplob, Bloomflash: Bloom Filter on Flash-Based Storage, 2011 31st Annual Conference on Distributed Computing Systems, Jun. 20-24, 2011, 10 pgs.
Pagiamtzis, Kostas, “Content-Addressable Memory Introduction”, Jun. 25, 2007, (6 pgs.), retrieved from: http://www.pagiamtzis.com/cam/camintro.
Pagiamtzis, et al., “Content-Addressable Memory (CAM) Circuits and Architectures: A Tutorial and Survey”, Mar. 2006, (16 pgs.), vol. 41, No. 3, IEEE Journal of Solid-State Circuits.
International Search Report and Written Opinion for PCT Application No. PCT/US2013/043702, dated Sep. 26, 2013, (11 pgs.).
Elliot, et al., “Computational RAM: Implementing Processors in Memory”, Jan.-Mar. 1999, (10 pgs.), vol. 16, Issue 1, IEEE Design and Test of Computers Magazine.
Dybdahl, et al., “Destructive-Read in Embedded DRAM, Impact on Power Consumption,” Apr. 2006, (10 pgs.), vol. 2, Issue 2, Journal of Embedded Computing—Issues in embedded single-chip multicore architectures.
Kogge, et al., “Processing In Memory: Chips to Petaflops,” May 23, 1997, (8 pgs.), retrieved from: http://www.cs.ucf.edu/courses/cda5106/summer02/papers/kogge97PIM.pdf.
Draper, et al., “The Architecture of the DIVA Processing-In-Memory Chip,” Jun. 22-26, 2002, (12 pgs.), ICS '02, retrieved from: http://www.isi.edu/˜draper/papers/ics02.pdf.
Adibi, et al., “Processing-In-Memory Technology for Knowledge Discovery Algorithms,” Jun. 25, 2006, (10 pgs.), Proceeding of the Second International Workshop on Data Management on New Hardware, retrieved from: http://www.cs.cmu.edu/˜damon2006/pdf/adibi06inmemory.pdf.
U.S. Appl. No. 13/449,082, entitled, “Methods and Apparatus for Pattern Matching,” filed Apr. 17, 2012, (37 pgs.).
U.S. Appl. No. 13/743,686, entitled, “Weighted Search and Compare in a Memory Device,” filed Jan. 17, 2013, (25 pgs.).
U.S. Appl. No. 13/774,636, entitled, “Memory as a Programmable Logic Device,” filed Feb. 22, 2013, (30 pgs.).
U.S. Appl. No. 13/774,553, entitled, “Neural Network in a Memory Device,” filed Feb. 22, 2013, (63 pgs.).
U.S. Appl. No. 13/796,189, entitled, “Performing Complex Arithmetic Functions in a Memory Device,” filed Mar. 12, 2013, (23 pgs.).
Search Report and Written Opinion for related PCT Application No. PCT/US2016/025499, dated Jul. 20, 2016, 11 pages.
Extended European Search Report for related EP Application No. 16774290.7, dated Dec. 3, 2018, 10 pages.
Related Publications (1)
Number Date Country
20180341597 A1 Nov 2018 US
Provisional Applications (1)
Number Date Country
62141601 Apr 2015 US
Continuations (1)
Number Date Country
Parent 15085631 Mar 2016 US
Child 16054702 US