Abstract:
Disclosed are methods and systems for dynamically determining data-transfer paths. The data-transfer pats are determined in response to an instruction that facilitates data transfer among execution lanes in an integrated-circuit processing device operable to execute operations in parallel.

Description:
RELATED APPLICATIONS 
       [0001]    This application is a continuation of U.S. patent application Ser. No. 12/192,813 filed on Aug. 15, 2008 and entitled “Data Exchange and Communication Between Execution Units in a Parallel Processor.” U.S. patent application Ser. No. 12/192,813 is a division of U.S. patent application Ser. No. 11/973,887 filed Oct. 9, 2007 and entitled “Data-Parallel Processing Unit,” which claims priority from U.S. Provisional Application No. 60/849,945 filed Oct. 6, 2006. Each foregoing applications is hereby incorporated by reference in its entirety. 
     
    
     BRIEF DESCRIPTION OF THE DRAWINGS 
       [0002]    Embodiments are described and illustrated by way of example, and not by way of limitation, in the figures of the accompanying drawings and in which like reference numerals refer to similar elements. 
         [0003]      FIG. 1  illustrates an exemplary system including a host CPU and a data-parallel co-processor. 
         [0004]      FIG. 2  shows an embodiment of a stream processor that may be used to implement the data-parallel co-processor of  FIG. 1 . 
         [0005]      FIG. 3  illustrates an embodiment of pipelined instruction execution within the stream processor of  FIG. 2 . 
         [0006]      FIG. 4  illustrates signaling between a microcontroller, execution lanes and an inter-lane switch to effect inter-lane data transfer during execution of a permutation-compute (PERMCOMP) instruction. 
         [0007]      FIG. 5  illustrates operations of the microcontroller during execution of the permutation-compute instruction. 
         [0008]      FIGS. 6A-6H  illustrate respective combined arithmetic operations that correspond to pseudo-code listings herein. 
         [0009]      FIG. 7  illustrates a multiplier architecture that may be used to support a variety of combined-arithmetic operations including, without limitation, dot-product and add, and sum and add operations. 
         [0010]      FIG. 8  illustrates data flow of strips of data during kernel execution within the stream processor of  FIG. 2 . 
         [0011]      FIGS. 9A and 9B  illustrate memory access patterns supported by an embodiment of the stream processor of  FIG. 2 . 
         [0012]      FIG. 10  illustrates another memory access pattern that may be supported by an embodiment of the stream processor of  FIG. 2 , in this case having 2 levels of nesting so that contiguous 2D blocks of pixels from an image stored in row-major order may be fetched. 
         [0013]      FIGS. 11A and 11B  illustrate retrieval of data and distribution of the retrieved data to lanes. 
         [0014]      FIG. 12  illustrates memory burst sequences and the manner in which selected words within each burst sequence may be associated with execution lanes in accordance with one embodiment. 
         [0015]      FIG. 13  shows an embodiment of a memory subsystem capable of accepting memory-load and memory-store stream commands with various strided and indirect access patterns. 
         [0016]      FIG. 14  illustrates an embodiment of the load interface and store interface to the LRF within a given execution lane. 
     
    
     DETAILED DESCRIPTION OF PREFERRED EMBODIMENTS 
       [0017]    System Context 
         [0018]    Embodiments of data-parallel/instruction-parallel processors disclosed herein may be employed as co-processors that execute compound vector operations as computation kernels compiled from a programming language. As shown in  FIG. 1 , a host CPU  101  executes the main application code in a data processing system. The host CPU  101  sends commands (not shown) to a data-parallel and/or instruction-parallel processor, referred to herein as a stream processor  103 . The commands issued by the host CPU  101  to the stream processor  103 , referred to herein as stream commands, instruct the stream processor  103  when to load and store instructions and data from an external memory into the stream processor&#39;s  103  local memory and when to execute computation kernels (described below) to process this data. 
         [0019]      FIG. 2  shows one embodiment of a stream processor  130  with 16 lanes, each having 5 arithmetic-logic units (ALU 0 -ALU 4 , also referred to as function units), and 1 communication (COMM) unit per lane. A DPU (Data-Parallel Unit) dispatcher  131  receives the stream commands from a host processor via port  111 . The DPU Dispatcher  131  buffers the commands locally until they are ready to be issued to various execution units. Descriptor registers are stored in a descriptor register file  169  and accessed by the DPU dispatcher  131  when commands are issued to the execution units. There are three main units for executing stream commands: an instruction fetch unit  161 , a stream load/store unit  143 , and a kernel execute unit that includes, in this example, a very-long-instruction word (VLIW) sequencer  165 , scalar unit  150 , sixteen execution lanes  141   0 - 141   15  (also referred to singularly and generically as lane  141 , or collectively as lanes  141 ), and inter-lane switch  135 . 
         [0020]    The instruction fetch unit  161  transfers code between an external memory (not shown) and a local instruction memory  163  via instruction memory port  108 . The stream load/store unit  143  transfers data between external memory and the lane register files  145  (LRFs) via data memory port  110 . During kernel-execute stream commands, the VLIW sequencer  165  fetches VLIW instructions from the instruction memory  163  and sends decoded instructions to the lanes  141   0 - 141   15  and the scalar unit  150 . The VLIW sequencer  165  also controls instruction sequencing with branch instructions. Each of the lanes  141  (also referred to as execution lanes) includes a lane register file (LRF)  145  for data memory, some number of function units (ALU 0 -ALU 4 , in this example) for executing arithmetic and data movement instructions, and a number of dedicated operand register files (RF) per function unit. A COMM unit  142  in each lane  141  may access the inter-lane switch  135  to provide a mechanism to exchange data among the lanes  141   0 - 141   15  and between the scalar unit  150  and the lanes  141   0 - 141   15 . 
         [0021]    The lanes  141   0 - 141   15  receive VLIW instructions from the VLIW sequencer  165  and execute the same instruction each clock cycle on each lane in a single-instruction multiple-data (SIMD) fashion. Within each lane  141 , the VLIW instruction controls the configuration of the local switch  149 , the reading and writing of the operand register files (RF), the reading and writing of the lane register file  145 , and the operations being performed on each of the function units (ALUs). 
         [0022]    In order to support high-frequency execution, a multi-stage hardware pipeline can be used. A long pipeline enables the long latency of executing one VLIW instruction on a highly parallel machine to be split up. The steps typically involved in execution of one instruction involve sending the instruction address from the VLIW sequencer  165 , reading a VLIW instruction from the instruction memory  163 , decoding the instruction, distributing it across a long distance to all of the lanes  141   0 - 141   15 , reading from the operand register files (RF), executing function unit operations specified by the VLIW instruction, traversing the local switch  149  for writing back results, and finally writing results back into the operand register file (RF). In a highly-parallel high-frequency processor, this process often uses tens of cycles to fully execute a VLIW instruction. 
         [0023]    In the stream processor  130  of  FIG. 2 , individual instruction execution may be pipelined in order to achieve high-frequency operation. One embodiment of this pipelining is shown in  FIG. 3 . The instruction fetch and decode stages, denoted by F 1 -F 4  and D 1 -D 3  respectively, split the reading of the instruction memory and instruction decode across seven total cycles. Within each lane, the register read (RR) and individual operations in the ALU (X1, X1:X5 depending on operation latency) can be pipelined. Finally, a cross-cluster (i.e, intra-lane) and write-back stage can be used for traversing the local switch  149  and writing back to the operand register files (RFs). Other embodiments can use more or fewer pipeline stages in order to trade off power dissipation for clock frequency. 
         [0024]    Kernel Execution 
         [0025]    Herein, “kernel” refers to a relatively small program that generally uses data in the lane register files  145  as input data, writes output data back to the lane register file  145  and also accepts scalar arguments from the host processor  101  through the DPU dispatcher  131 . Kernels may be prevented from accessing external memory locations. Also, in one embodiment, only addresses in the lane register file  145  associated with each lane  141  are addressable during kernel computation. Communication between lane register files is explicitly handled in the kernel program by using the COMM unit  142 . Since there is a single shared VLIW sequencer  165 , control flow decisions such as branches for supporting loops apply to all lanes  141 . 
         [0026]    The stream processor  130  of  FIG. 2  generally achieves highest performance efficiency when executing compound vector operations in kernel inner loops. Compound vector operations perform a sequence of arithmetic operations on data read from the lane register file  145 , and generate results written back to the lane register file  145 . During compound vector operations, data is read and written from the lane register file  145  sequentially at very high bandwidth. 
         [0027]    Kernel execution in a stream processor is not limited to the compound vector operation model. Random or indexed access to streams in the lane register file  145  may be provided, for example, using register-plus-offset indexed addressing. With indexed streams, data in the lane register file  145  is not treated as sequential streams and is not pre-fetched or buffered separately, but more like a traditional VLIW architecture with a load/store unit, access to the lane register file  145  data memory is done directly using explicit addresses. In this mode of operation the architecture has a disadvantage of longer-latency and lower-bandwidth access but the advantage of providing random access to the lane register file  145  during kernels. 
         [0028]    COMM Unit—PERMCOMP 
         [0029]    The communication unit (COMM) within each lane  141  provides a simple interface to the inter-lane switch  135 , used to exchange data between the lanes  141 . The COMM unit  142  can support arbitrary permutations on 8-bit, 16-bit, or 32-bit data. In normal modes, permutation patterns are specified when each destination lane specifies dynamically from one of its operands which lane to get its source data from. In this way, static permutations can be easily supported. Dynamic inter-lane communication patterns can also be supported if the source lane (for example, lane  141   0 ) is dynamically computed on the destination lane (for example, lane  141   15 ). 
         [0030]    In some applications, it may be desirable for the source lane, rather than the destination lane, to compute the destination dynamically. In contrast to prior-art data-parallel processing devices, the stream processor  130  of  FIG. 2  supports this type of source-lane destination computation. In one embodiment, a special instruction, permutation compute (PERMCOMP), is implemented to manage this type of communication. When the PERMCOMP instruction is encountered by the VLIW sequencer  165 , a microcontroller  137  formed by the VLIW sequencer  165  and scalar unit  150  takes in a request to send data from each of the 16 lanes  141   0 - 141   15 . Each request is comprised of a destination lane and a valid bit. Once the requests are collected by the microcontroller  137  from all the lanes  141 , the requests are then arbitrated. The originating lane (or source lane, not shown due to the many possible permutations) is sent a single bit (success/no success) to inform the originating lane whether or not it can successfully send data. Each destination lane (not shown) to which valid data is directed is sent the source lane number and a valid signal. An unsuccessful send (i.e, bit indicating no-success to source lane) signals the source lane that a collision has occurred (i.e, conflict within the inter-lane switch  135 ). This approach has several advantages:
       1) Supports efficient data communication among lanes even when communication pattern is non deterministic.   2) Fast communication with lower overhead than a pure software approach.   3) Centralized arbitration reduces hardware requirements for this instruction (PERMCOMP).   4) Deterministic instruction latency allows for efficient scheduling in the compiler; pipelined so that it does not become a cycle time limiter.       
 
         [0035]      FIG. 4  illustrates the above-described signaling between the microcontroller  137 , execution lanes  141 , and inter-lane switch  135  during execution of a PERMCOMP instruction. As discussed, at the start of PERMCOMP execution, the microcontroller  137  receives a destination lane identifier (Dest Lane) and corresponding valid signal (Valid) from each lane, the valid signal indicating whether the lane is requesting to transfer data via the inter-lane switch  135  (i.e, whether the lane is a source lane) and the destination lane identifier specifies the lane to which data is directed. Referring to  FIG. 5 , which illustrates operations of the microcontroller  137  during PERMCOMP execution, the microcontroller  137  examines the request from all lanes ( 201 ), and then, as shown at  203 , sends the success/failure flag (Success/Failure) to each lane having valid data (i.e, asserting the valid signal) if the destination lane requested by the source lane was not requested by any other lane (i.e, no conflicts with other lanes). If two or more lanes having valid data specify the same destination lane (decision block  205 ), then a conflict arises and the microcontroller  137  responds as shown at  207  by arbitrating between the conflicting requests ( 209 ), sending a success flag (or signal) to the arbitration winner ( 211 ) and sending a failure flag to each arbitration loser ( 213 ). 
         [0036]    In the embodiment of  FIG. 4 , each of execution lanes  141   0 - 141   1   5  controls the source of any transfer via the inter-lane switch  135 , for example, by providing a source-lane value (Src lane) to a respective one of multiplexers  193   0 - 193   15 . Accordingly, as shown at block  215  in  FIG. 5 , after success/failure flags have been sent to each requesting lane (i.e, as in block  203  for non-conflicting requests, and as in blocks  205 / 207  for conflicting requests), the microcontroller  137  identifies the destination lanes for all successful requests (i.e, requests for which success flags are asserted) and sends source lane information to each destination lane to enable the destination lane to control the source lane selection in the corresponding multiplexer  193 . 
         [0037]    Note that in the embodiment shown, each of multiplexers  193  includes a respective input port coupled to each of sixteen communication lanes ( 194 ) within the inter-lane switch  135 , thus enabling each lane to receive data from any others of the lanes and also permitting a given source lane to transmit data to multiple destination lanes. In alternative embodiments, other switching structures may be used (e.g., programmable cross-bar), including structures that permit less than all possible source lanes to transfer to a give destination lane and/or that limit the number of destination lanes to which a source lane may send data. 
         [0038]    With regard to arbitration between conflicting requests (e.g., as shown in  FIG. 5  at  209 ), any desirable arbitration policy may be applied to identify the arbitration winner. For example, in one embodiment, the microcontroller  137  may arbitrate between conflicting requests based on a fixed priority assigned to individual lanes (e.g., always selecting a lower-numbered lane over a higher-numbered lane, or vice-versa). In other embodiments, a least-recently selected policy or other starvation-avoidance policy may be applied to ensure that no individual lane fails to receive at least some share of the inter-lane transfer bandwidth (i.e, no requesting lane is repeatedly denied access to the inter-lane switch  135  (“starving”) due to sustained higher-priority requests). Moreover, in yet other embodiments, the stream processor  130  may support multiple arbitration policies, with one of the multiple different arbitration policies selected through run-time configuration register setting (or one-time or otherwise non-volatile programming operation during device production) or selected by a bit or bits within or associated with the PERMCOMP instruction. 
         [0039]    Function Unit (ALU) Operations—Instruction Set Architecture 
         [0040]    Each of the ALUs shown within the execution lanes  141  (and/or scalar unit) of  FIG. 2  supports a number of 3-input-operand (or less) and 2-output-operand (or less) operations for doing arithmetic and logical functions. Signal, image, and video processing applications may use the following data-types packed into a 32-bit word: 
         [0041]    Packed unsigned integer 8-bit 
         [0042]    Packed unsigned integer 16-bit 
         [0043]    Unsigned integer 32-bit 
         [0044]    Packed signed integer 8-bit 
         [0045]    Packed signed integer 16-bit 
         [0046]    Signed integer 32-bit 
         [0047]    Packed signed integer complex 16-bit pairs 
         [0048]    Packed unsigned fixed-point 8-bit 
         [0049]    Packed unsigned fixed-point 16-bit 
         [0050]    Unsigned fixed-point 32-bit 
         [0051]    Packed signed fixed-point 8-bit 
         [0052]    Packed signed fixed-point 16-bit 
         [0053]    Signed fixed-point 32-bit 
         [0054]    Packed signed fixed-point complex 16-bit pairs 
         [0055]    Some example operations supported by an ALU to process this packed data are shown below: 
         [0056]    Absolute difference 
         [0057]    Addition and subtraction with saturation 
         [0058]    Format conversion (packing/unpacking) between data-types, including clipping/ 
         [0059]    saturation 
         [0060]    Division (or divide step) and remainder 
         [0061]    Dot Product 
         [0062]    Minimum/maximum 
         [0063]    Logic ops: negate, xor, or, and 
         [0064]    Fractional multiplies with rounding and saturation 
         [0065]    Sums between different sub-words 
         [0066]    Integer multiplies with saturation 
         [0067]    Comparison operations (less than, greater than, equal to, etc. . . . ) 
         [0068]    Arithmetic and Logical Shifts 
         [0069]    Conditionals: Ternary select 
         [0070]    Fixed-point: Find first one, normalize 
         [0071]    There are particular advantages to supporting a three-operand instruction as a basic operation in DSP applications. Since many image, video, and signal processing computation kernels exhibit large amounts of instruction-level parallelism (ILP) and data-level parallelism (DLP) (which can be converted into ILP via software pipelining or loop unrolling), kernel performance is often limited by the available instruction throughput (instructions per cycle) and not by the latency through the critical path of a computation kernel. In these types of applications, if two common arithmetic functions are grouped together into a single operation at a small or negligible area cost (and/or frequency penalty), this tradeoff can result in higher overall performance. 
         [0072]    In contrast to the more limited support for combined arithmetic functions in typical prior-art DSPs multiply-accumulate as described above), each of the ALUs within the stream processor of  FIG. 2  may include a microarchitecture that enables a substantially broader combination of arithmetic functions, including combinations of operations that use the multiplier array where the partial result is added to an accumulator before the final result is computed are supported. More specifically, such combination operations may include, in addition to multiply-accumulate (i.e, multiplications in which the multiplication result is added to an accumulator):
       Dot-products (both real and complex) where the result is added to an accumulator   Multiple simultaneous dot products on packed data with shifted data alignment in one operation   Full and partial sums between sub-words where the result is added to an accumulator       
 
         [0076]    Pseudo-code expressions for specific examples of these combined-function operations are provided below (with corresponding graphical representation as shown by example in  FIGS. 6A-6H ), wherein the symbol “*” indicates multiplication, “X” and “Y” are outputs from a given ALU (e.g., X=accumulated sum, Y=carry value), and “A”, “B” and “C” are operands supplied to the ALU (e.g., A and B may be multiplicands, and C an accumulated value to which the A*B product is to be added): 
         [0077]    2-element Dot-product and Add ( FIG. 6A ): 
         [0078]    Y:X=sign_ext(A[1]*B[1]+A[0]*B[0])+C 
         [0079]    2-element Dot-product with Negate and Add: 
         [0080]    Y:X=sign_ext(A[1]*B[1]−A[0]*B[0])+C 
         [0081]    4-element Dot-product and Add ( FIG. 6B ): 
         [0082]    X=A[3]*B[3]+A[2]*B[2]+A[1]*B[1]+A[0]*B[0]+C 
         [0083]    4-way Multiply and add (same output precision) ( FIG. 6C ): 
         [0084]    X[3]=A[3]*B[3]+C[3] 
         [0085]    X[2]=A[2]*B[2]+C[2] 
         [0086]    X[1]=A[1]*B[1]+C[1] 
         [0087]    X[0]=A[0]*B[0]+C[0] 
         [0088]    2-way Multiply and add (same output precision) ( FIG. 6D ): 
         [0089]    X[1]=A[1]*B[1]+C[1] 
         [0090]    X[0]=A[0]*B[0]+C[0] 
         [0091]    4-way Multiply with double-precision output and add ( FIG. 6E ): 
         [0092]    Y[1]=A[3]*B[3]+C[0] 
         [0093]    Y[0]=A[2]*B[2]+C[0] 
         [0094]    X[1]=A[1]*B[1]+C[1] 
         [0095]    X[0]=A[0]*B[0]+C[1] 
         [0096]    2-way Multiply with double-precision output and add ( FIG. 6F ): 
         [0097]    Y=A[1]*B[1]+C 
         [0098]    X=A[0]*B[0]+C 
         [0099]    4-element Sum and Add ( FIG. 6G ): 
         [0100]    X=A[1]+A[0]+B[1]+B[0]+C 
         [0101]    2-way 4-element Sum and Add (8-bit A, 8-bit B, 16-bit C) ( FIG. 6H ): 
         [0102]    X[1]=A[3]+A[2]+B[3]+B[2]+C[1] 
         [0103]    X[0]=A[1]+A[0]+B[1]+B[0]+C[0] 
         [0104]    In all operations, by supplying a zero to the C input operand, each operation can be simplified to a multiply, dot-product, or sum. Furthermore, depending on input and output data-types, these basic operations can be augmented to support saturation and clipping or rounding. 
         [0105]    ALU Micro-Architecture 
         [0106]    An efficient ALU micro-architecture is essential to support the above instruction set containing many variations of multiply, multiply add, dot product, and sum instructions mentioned above. Variations include operand size differences (8-, 16-, 32-bits), and operand types (signed, unsigned). In some embodiments, to support this rich ISA, a unique partitioning of Wallace trees is provided, including four levels of ALU components, as shown in  FIG. 7 . A first level of ALU components includes four instances (A, B, C, D) of 16×8 Booth encoded multipliers constructed of 5:2 Wallace CSA (carry/sum adder) arrays. 
         [0107]    The second level of ALU components includes two instances (AB, CD) of 4:2 Wallace CSA arrays. The first array (AB) adds together the results of A and B. The second array (CD) adds together the results of C and D. At the input of the arrays is a multiplexer allowing one of the results to be shifted left by one byte. This allows the array to add data with equal bit weights (for dot products), or perform partial product accumulation for larger multiplies. 
         [0108]    The third level of ALU components includes two separate 5:2 Wallace array instances (X, Y). These can combine different combinations of the AB and CD results along with a third operand, and create carry/sum results ready for a full propagate adder. 
         [0109]    The fourth level of ALU components includes two full propagate adders, one to combine X&#39;s carry/sum results, and one to add Y&#39;s carry/sum results. This adder can also be used for add instructions. 
         [0110]    Repeating the pseudo code examples of combined-function operations provided above, and lining up references input operands A, B and C (and outputs X and Y) to the operand inputs (and operation results) shown in  FIG. 7 , it can be seen that the foregoing pseudocode examples, and ALU micro-architecture of  FIG. 7  carries out the following sub-operations in support of a given combined-function operation (note that A′, B′, C′, D′, AB′ and CD′ reflect the outputs of like-designated Wallace CSA&#39;s in carry/sum format): 
         [0111]    2-element Dot-product and Add: 
         [0112]    Y:X=sign_ext(A[1]*B[1]+A[0]*B[0])+C
       A′=sign_ext(opa[15:0]*opb[7:0])   B′=sign_ext(opa[15:0]*opb[15:8])   C′=sign_ext(opa[31:16]*opb[23:16])   D′=sign_ext(opa[31:16]*opb[31:24])   AB′=sign_ext(A′+(B′&lt;&lt;8))   CD′=sign_ext(C′+(D′&lt;&lt;8))   X=AB′[31:0]+CD′[31:0])+opc[31:0]   Y=sign_ext(AB′[63:32]+CD′[63:32]+X′carry_out)       
 
         [0121]    2-element Dot-product with Negate and Add: 
         [0122]    Y:X=sign_ext(A[1]*B[1]−A[0]*B[0])+C
       A′=sign_ext(opa[15:0]*opb[7:0])   B′=sign_ext(opa[15:0]*opb[15:8])   C′=sign_ext(opa[31:16]*opb[23:16])   D′=sign_ext(opa[31:16]*opb[31:24])   AB′=sign_ext(A′+(B′&lt;&lt;8))   CD′=sign_ext(C′+(D′&lt;&lt;8))   X=˜(AB′[31:0])+1+CD′[31:0])+opc[31:0]       
 
         [0130]    Y=sign_ext(˜(AB′[63:32])+CD′[63:32]+X′carry_out) 
         [0131]    4-element Dot-product and Add: 
         [0132]    X=sign_ext(A[3]*B[3]+A[2]*B[2]+A[1]*B[1]+A[0]*B[0])+C
       A′=sign_ext(opa[7:0]*opb[7:0])   B′=sign_ext(opa[15:8]*opb[15:8])   C′=sign_ext(opa[23:16]*opb[23:16])   D′=sign_ext(opa[31:24]*opb[31:24])   AB′=sign_ext(A′+B′)   CD′=sign_ext(C′+D′)   X=sign_ext(AB′[31:0]+CD′[31:0])+opc[31:0]       
 
         [0140]    4-way Multiply and Add (same output precision) 
         [0141]    X[3]=sat(A[3]*B[3]+C[3]) 
         [0142]    X[2]=sat(A[2]*B[2]+C[2]) 
         [0143]    X[1]=sat(A[1]*B[1]+C[1]) 
         [0144]    X[0]=sat(A[0]*B[0]+C[0])
       A′=sign_ext(opa[7:0]*opb[7:0])   B′=sign_ext(opa[15:8]*opb[15:8])   C′=sign_ext(opa[23:16]*opb[23:16])   D′=sign_ext(opa[31:24]*opb[31:24])   AB′=bypass   CD′=bypass   X[0]=sat(A′+opc[7:0]) (note: block carries at byte boundary)   X[1]=sat(B′+opc[15:8])   X[2]=sat(C′+opc[23:16])   X[3]=sat(D′+opc[31:24])       
 
         [0155]    2-way Multiply and Add (same output precision) 
         [0156]    X[1]=sat(A[1]*B[1]+C[1]) 
         [0157]    X[0]=sat(A[0]*B[0]+C[0])
       A′=sign_ext(opa[15:0]*opb[7:0])   B′=sign_ext(opa[15:0]*opb[15:8])   C′=sign_ext(opa[31:16]*opb[23:16])   D′=sign_ext(opa[31:16]*opb[31:24])   AB′=sign_ext(A′+(B′&lt;&lt;8))   CD′=sign_ext(C′+(D′&lt;&lt;8))   X[0]=sat(AB′[31:0]+opc[15:0]) (note: block carries at 16-bit boundary)   X[1]=sat(CD′[31:0]+opc[31:0])       
 
         [0166]    4-way Multiply and Add (double precision output) 
         [0167]    Y[1]=sign_ext(A[3]*B[3]+C[3]) 
         [0168]    Y[0]=sign_ext(A[2]*B[2]+C[2]) 
         [0169]    X[1]=sign_ext(A[1]*B[1]+C[1]) 
         [0170]    X[0]=sign_ext(A[0]*B[0]+C[0])
       A′=sign_ext(opa[7:0]*opb[7:0])   B′=sign_ext(opa[15:8]*opb[15:8])   C′=sign_ext(opa[23:16]*opb[23:16])   D′=sign_ext(opa[31:24]*opb[31:24])   AB′=bypass   CD′=bypass   X[0]=sign_ext(A′+opc[7:0]) (note: block carries at 16-bit boundary)   X[1]=sign_ext(B′+opc[15:8])   Y[0]=sign_ext(C′+opc[23:16])   Y[2]=sign_ext(D′+opc[31:24])       
 
         [0181]    2-way Multiply and Add (double precision output) 
         [0182]    Y=sign_ext(A[1]*B[1]+C[1]) 
         [0183]    X=sign_ext(A[0]*B[0]+C[0])
       A′=sign_ext(opa[15:0]*opb[7:0])   B′=sign_ext(opa[15:0]*opb[15:8])   C′=sign_ext(opa[31:16]*opb[23:16])   D′=sign_ext(opa[31:16]*opb[31:24])   AB′=sign_ext(A′+(B′&lt;&lt;8))   CD′=sign_ext(C′+(D′&lt;&lt;8))   X=sign_ext(AB′[31:0]+opc[15:0])   Y=sign_ext(CD′[31:0]+opc[31:0])       
 
         [0192]    4-element Sum and Add: 
         [0193]    X=sign_ext(A[1]+A[0]+B[1]+B[0]+C)
       A′=sign_ext(opa[15:0]*1)   B′=sign_ext(opa[31:16]*1)   C′=sign_ext(opb[15:0*1)   D′=sign_ext(opb[31:16]*1)   AB′=bypass   CD′=bypass   X=sign_ext(A′+B′+C′+D′+opc[31:0])       
 
         [0201]    2-way 4-element Sum and Add (8-bit A, 8-bit B, 16-bit C): 
         [0202]    X[1]=sign_ext(A[3]+A[2]+B[3]+B[2]+C[1]) 
         [0203]    X[0]=sign_ext(A[1]+A[0]+B[1]+B[0]+C[0])
       A′=sign_ext(opa[15:0]*1)   B′=sign_ext(opa[31:16]*1)   C′=sign_ext(opb[15:0*1)   D′=sign_ext(opb[31:16]*1)   AB′=sign_ext(A′+B′) (note: block carries at 16-bit boundary)   CD′=sign_ext(C′+D′)   X[1]=sign_ext(AB′[1]+CD′[1]+opc[31:16]) (note: block carries at 16-bit boundary)   X[0]=sign_ext(AB′[0]+CD′[0]+opc[15:0])       
 
         [0212]    Within the foregoing sub-operations, the function “sign ext( )” effects a sign extension from m-bits to n-bits (16 bits to 32 bits in this example). The function, “sat( )” returns a minimum or maximum m-bit 2&#39;s complement number if the function argument (i.e, the input to the function) exceeds the minimum or maximum of the m-bit 2&#39;s complement number, and otherwise returns the least significant m bits of the function argument. Also, the terms, “x2”, “s”, and “a” are Booth encoded control signals. Using radix-4 Booth encoding, for example, allows the number of partial product terms summed in the Wallace tree to be reduced by roughly half. Three consecutive bits of the multiplier are encoded to produce an x2,a,s control value that is used, in turn, to choose a single partial product term. The next 3 bit window of multiplier bits overlaps the first window by one bit. The encoding is as follows: 
         [0000]    
       
         
               
               
             
           
               
                   
                   
               
             
             
               
                   
                 // {booth_a,booth_s} = = 00: Invalid 
               
               
                   
                 // {booth_a,booth_s} = = 01: do not invert partial product 
               
               
                   
                 // {booth_a,booth_s} = = 10: invert partial product 
               
               
                   
                 // {booth_a,booth_s} = = 11: 0 for partial product 
               
               
                   
                 // booth_x2 = = 1 :partial product = 2*multiplicand 
               
               
                   
                 // booth_x2 = = 0 :partial product = multiplicand 
               
               
                   
                   
               
             
          
         
       
     
         [0213]    Stream Load/Store Unit 
         [0214]    One programming model for a system that includes the stream processor of  FIG. 2  consists of a main instruction stream running on a host CPU and separate computation kernels that run on the stream processor. The host CPU dispatches stream commands for respective strips of data and loops over the data strips in order to sustain real-time operation. This dataflow is shown graphically in  FIG. 8 . 
         [0215]    Referring again to  FIG. 2 , the stream load/store unit  143  executes MEMLD (memory load) or MEMST (memory store) stream commands that transfer data between external memory and the LRFs. In many cases, stream commands process between tens and thousands of bytes of data at a time using memory access patterns provided with the command. More specifically, memory access patterns may be used to specify the address sequence for the data transferred during MEMLDs and MEMSTs. These access patterns are defined by an external memory base address, an external memory address sequence, and an LRF address sequence. Base addresses are arbitrary byte addresses in external memory. The address sequence can be specified as a stride between subsequent records all at address offsets from the base address or as a sequent of indirect record offsets from a common base address.  FIG. 9A  provides an example of a stride of 7 with a record size of 3, whereas  FIG. 9B  shows indirect offsets with a record size of 3. More complicated addressing patterns are supported with nested strided patterns or a combination of strided and indirect patterns. For example, with 2 levels of nesting, contiguous 2D blocks of pixels from an image stored in row-major order could be fetched where an inner stride would correspond to the image width while the outer stride would correspond to the block width. An example of such multiple-level nesting is shown in  FIG. 10 . 
         [0216]    The external memory access patterns may be described using command arguments that specify record sizes and strides (non-nested or nested) in external memory. Once data records are fetched from external memory and arranged into a linear sequence of records belonging to the stream to be loaded, the data in the stream needs to be divided up among the lanes. A simple example with a 4-lane stream processor where each 3-word record is sent to each lane is shown in Table 1 below. 
         [0000]    
       
         
               
             
               
               
               
               
               
             
           
               
                 TABLE 1 
               
             
             
               
                   
               
               
                 Example of LRF partitioning 
               
             
          
           
               
                   
                 Lane 0 
                 Lane 1 
                 Lane 2 
                 Lane 3 
               
               
                   
                   
               
               
                   
                 Base + 0 
                 Base + 7 
                 Base + 14 
                 Base + 21 
               
               
                   
                 Base + 1 
                 Base + 8 
                 Base + 15 
                 Base + 22 
               
               
                   
                 Base + 2 
                 Base + 9 
                 Base + 16 
                 Base + 23 
               
               
                   
                 Base + 28 
                 Base + 35 
                 Base + 42 
                 Base + 49 
               
               
                   
                 Base + 29 
                 Base + 36 
                 Base + 43 
                 Base + 50 
               
               
                   
                 . . . 
                 . . . 
                 . . . 
                 . . . 
               
               
                   
                   
               
             
          
         
       
     
         [0217]    With a more complex example, multiple words from a single record (i.e, having record_size number of words) could be spread out over multiple lanes (i.e, lanes_per_record).  FIGS. 11A and 11B  illustrate retrieval of data and distribution of the retrieved data to lanes in accordance with the example of Table 1 (record_size=3, lanes_per_record=1, stride=7) and in an example having multiple words from a single record spread out over multiple lanes (e.g., record_size=4, lanes_per_record=2, stride=7), respectively. 
         [0218]    The partitioning of records among the lanes can be described with command arguments that indicate the number of words from the sequentially assembled stream to write to each lane before filling up words in the next lane (e.g., record_size and lanes_per_record). For implementation simplicity, it is beneficial to hold the number of words per lane constant during the MEMLD or MEMST command execution. 
         [0219]    Further complicating the loading or storing of this data from external memory, modern DRAM memory systems have relatively long data burst lengths in order to operate at high bandwidth. DRAM bursts are multi-word reads or writes from external memory that can be as high as 8 or 16 words per access in a modern memory system. Memory addresses sent to the DRAM access these 8-word or 16-word bursts, not individual bytes or words within the burst. Consequently, in a DRAM memory system that issues bursts of 8 words (for example), reading the first four records (12 words) of the stream in the example above (i.e, described in reference to  FIG. 9A ) actually may result in reading three DRAM bursts, as shown in  FIG. 12 . 
         [0220]    The stream load/store unit is capable of taking these external memory access patterns, record partitioning across the LRFs, and converting these into sequences of burst addresses and transferring individual words from those bursts to/from the LRFs. 
         [0221]    It should be noted that the above description of access patterns can be extended to arbitrary record lengths, strides, nested strides, and partitioning of records across LRFs. In addition, although the example above was given for a MEMLD, it also applies to MEMST 
         [0222]    Memory Subsystem Architecture 
         [0223]    The stream load/store unit subsystem handles all aspects of executing MEMLDs and MEMSTs. It assembles address sequences into bursts based on flexible memory access patterns, thereby eliminating redundant fetches of bursts from external memory. It also manages partitioning of streams across the lanes  310   0 - 310   15 . 
         [0224]      FIG. 13  shows an embodiment of a memory subsystem capable of accepting MEMLD or MEMST stream commands with various strided and indirect access patterns. The memory system subdivides stream commands into external memory bursts to one or more DRAM channels  302  and  303 , and writes the loaded data back into the LRFs. In the particular embodiment shown, the memory subsystem is composed of several key components:
       Address generators accept stream commands and access patterns from the DPU dispatcher and compute sequences of burst address requests.   Each lane  310  contains a load and store interface for buffering data between the LRFs and the memory switch  305 .   A memory switch  305  handles routing burst address requests and burst data between DRAM channels and the lanes  310   0 - 310   15 .   An optional cache  304  eliminates redundant read requests to the same burst in external memory.       
 
         [0229]    During execution of a specific stream command, stream commands are sent from the DPU dispatcher to address generator  301 . The address generator parses the stream command to figure out a burst address sequence based on the memory access pattern. As individual address requests are sent to DRAM, the load or store interface in each lane  310  analyzes the current burst address request to determine if it has any data that belongs to its LRF partition corresponding to the current burst. During stores, if a lane  310  has data corresponding to that burst, the lane  310  sends its data out with the current burst. During loads, a recording of the corresponding burst is stored locally in each lane  310  so that when the return data is sent back from DRAM, the return data gets stored into the appropriate LRF (i.e, as indicated by the record of the burst stored in each lane  310 ). 
         [0230]    Still referring to  FIG. 13 , the memory switch  305  handles routing of address requests and data values between the address generator and LRFs with the cache  304  and external DRAM channels. In a system without a cache  304 , if the address requests are restricted to native request sizes supported by each DRAM channel, it eases implementation complexity. For example, if each DRAM channel supports up to 8-word bursts, the address requests sent out by the address generators could directly correspond to 8-word bursts and memory requests could be supplied directly to the DRAM channel. This approach has the disadvantage of potentially incurring redundant accesses of data, particularly with indirect modes. With indirect modes, if multiple offsets within a stream command access the same burst, then the address generator would end up sending redundant address requests to external memory. 
         [0231]    In a system with a cache  304 , the address requests made by the address generators are not limited to native DRAM requests and redundant accesses can be supported. For example, consider a situation where each DRAM channel supports 32-byte bursts and the cache  304  contains a 32-byte line size. If one indirect-mode access requests the lower 16 bytes from that burst for a data record, then that burst will be loaded into the cache  304 . If an access later in the stream accesses the upper 16 bytes to the same burst, instead of accessing external memory to re-fetch the data, the data can be read out of the cache  304 . A system with a cache  304  can also support address requests from the address generator to non-burst-aligned addresses. Individual address requests to bursts of data can be converted by the cache  304  into multiple external DRAM requests. 
         [0232]    Although the above embodiment of a stream load/store unit contains one load unit, one store unit, sixteen lanes and two DRAM channels, multiple load units, multiple store units, a different number of lanes, and more or fewer DRAM channels may be provided in alternative embodiments. 
         [0233]      FIG. 14  illustrates an embodiment of the load interface  351  and store interface  353  to the LRF  145  within a given execution lane. The store interface  353  contains a tag generator  355 , a tag matching circuit  357 , and a data FIFO  359  (first-in-first-out storage circuit). The load interface  351  contains a tag generator  365 , a tag FIFO  367 , a tag matching circuit  369  for return data, and a return data FIFO  371 . 
         [0234]    During both loads and stores, the tag generator ( 355 ,  365 ) also parses the stream command to determine the word address sequence of all of the data elements in this lane during a memory load or store data transfer. Note that this is different than the address generator burst address sequence since it also indicates the location of a word within a burst. For example, in a memory system with an 8-word burst, the tag generator ( 355 ,  365 ) indicates that a certain data element has a burst address and is in offset 3 of 8 within that burst. Tags may be formed by a combination of a subset of the addresses and the lane number and just need to be large enough to avoid aliasing between data elements across the lanes. 
         [0235]    During stores, as each address is computed, a word is transferred from the LRF SB into the data FIFO  359 . Once enough words have been transferred into the data FIFO to form the first address request, the address generator will send out an address request and a corresponding write tag. The tag matching circuit  357  analyzes the write tag. If any data elements from the current burst are in this lane&#39;s data FIFO  359 , the match circuit  357  will indicate that, and write data will be driven onto the bus to correspond to this address request. 
         [0236]    During loads, as each address is computed, an entry in the tag FIFO  367  indicating that this lane register file needs a word from a specific burst is updated. Once read requests return from either the cache or external DRAM, a read tag corresponding to the request is compared against the next tag in the tag FIFO  367 . If any of the elements from the current burst correspond to words that belong in this lane&#39;s LRF, then those data elements are written into the data FIFO  371 . Once enough data elements have been accumulated in the data FIFOs  371  across all of the lanes, then words can be transferred into the LRFs through the SBs. 
         [0237]    It should be noted that the various circuits disclosed herein may be described using computer aided design tools and expressed (or represented), as data and/or instructions embodied in various computer-readable media, in terms of their behavioral, register transfer, logic component, transistor, layout geometries, and/or other characteristics. Formats of files and other objects in which such circuit expressions may be implemented include, but are not limited to, formats supporting behavioral languages such as C, Verilog, and VHDL, formats supporting register level description languages like RTL, and formats supporting geometry description languages such as GDSII, GDSIII, GDSIV, CIF, MEBES and any other suitable formats and languages. Computer-readable media in which such formatted data and/or instructions may be embodied include, but are not limited to, non-volatile storage media in various forms (e.g., optical, magnetic or semiconductor storage media) and carrier waves that may be used to transfer such formatted data and/or instructions through wireless, optical, or wired signaling media or any combination thereof. Examples of transfers of such formatted data and/or instructions by carrier waves include, but are not limited to, transfers (uploads, downloads, email, etc.) over the Internet and/or other computer networks via one or more data transfer protocols (e.g., HTTP, FTP, SMTP, etc.). 
         [0238]    When received within a computer system via one or more computer-readable media, such data and/or instruction-based expressions of the above described circuits may be processed by a processing entity (e.g., one or more processors) within the computer system in conjunction with execution of one or more other computer programs including, without limitation, net-list generation programs, place and route programs and the like, to generate a representation or image of a physical manifestation of such circuits. Such representation or image may thereafter be used in device fabrication, for example, by enabling generation of one or more masks that are used to form various components of the circuits in a device fabrication process. 
         [0239]    The section headings in the preceding detailed description are provided for convenience of reference only, and in no way define, limit, construe or describe the scope or extent of such sections. Also, while the invention has been described with reference to specific embodiments thereof, it will be evident that various modifications and changes may be made thereto without departing from the broader spirit and scope of the invention. For example, features or aspects of any of the embodiments may be applied, at least where practicable, in combination with any other of the embodiments or in place of counterpart features or aspects thereof. Accordingly, the specification and drawings are to be regarded in an illustrative rather than a restrictive sense.