Advanced Micro Devices Corporation

Advanced Micro Devices (shanghai) Co., Ltd.

Ati Technologies Ulc

Bin He

Michael Mantor

Jiasheng Chen

YunXiao Zou

Brian D Emberling

Jian Huang

Mark M Leather

Qingcheng Wang

Angel E Socarras

Wei Yuan

Shubh Shah

Timour T Paltashev

Radhakrishna Giduthuri

Chao Liu

Syed Zohaib M Gilani

Eric J Finger

Mohammad Reza Hakami

Liang Huang

Timothy Lottes

Justin David Smith

Derek Carson

A processing system executes wavefronts at multiple arithmetic logic unit (ALU) pipelines of a single instruction multiple data (SIMD) unit in a single execution cycle. The ALU pipelines each include a number of ALUs that execute instructions on wavefront operands that are collected from vector general process register (VGPR) banks at a cache and output results of the instructions executed on the wavefronts at a buffer. By storing wavefronts supplied by the VGPR banks at the cache, a greater number of wavefronts can be made available to the SIMD unit without increasing the VGPR bandwidth, enabling multiple ALU pipelines to execute instructions during a single execution cycle.

Dual vector arithmetic logic unit

Block data load with transpose techniques are described. In one example, an input is received, at a control unit, specifying an instruction to load a block of data to at least one memory module using a transpose operation. Responsive to the receiving the input by the control unit, the block of data is caused to be loaded to the at least one memory module by transposing the block of data to form a transposed block of data and storing the transposed block of data in the at least one memory.

Block data load with transpose into memory

A parallel processing unit employs an arithmetic logic unit (ALU) having a relatively small footprint, thereby reducing the overall power consumption and circuit area of the processing unit. To support the smaller footprint, the ALU includes multiple stages to execute operations corresponding to a received instruction. The ALU executes at least one operation at a precision indicated by the received instruction, and then reduces the resulting data of the at least one operation to a smaller size before providing the results to another stage of the ALU to continue execution of the instruction.

Processing unit with small footprint arithmetic logic unit

Systems, apparatuses, and methods for efficiently processing arithmetic operations are disclosed. A computing system includes a processor capable of executing single precision mathematical instructions on data sizes of M bits and half precision mathematical instructions on data sizes of N bits, which is less than M bits. At least two source operands with M bits indicated by a received instruction are read from a register file. If the instruction is a packed math instruction, at least a first source operand with a size of N bits less than M bits is selected from either a high portion or a low portion of one of the at least two source operands read from the register file. The instruction includes fields storing bits, each bit indicating the high portion or the low portion of a given source operand associated with a register identifier specified elsewhere in the instruction.

Packed 16 bits instruction pipeline

A graphics processing unit (GPU) sequences provision of operands to a set of operand registers, thereby allowing the GPU to share at least one of the operand registers between processing. The GPU includes a plurality of arithmetic logic units (ALUs) with at least one of the ALUs configured to perform double precision operations. The GPU further includes a set of operand registers configured to store single precision operands. For a plurality of executing threads that request double precision operations, the GPU stores the corresponding operands at the operand registers. Over a plurality of execution cycles, the GPU sequences transfer of operands from the set of operand registers to a designated double precision operand register. During each execution cycle, the double-precision ALU executes a double precision operation using the operand stored at the double precision operand register.

Arithmetic logic unit register sequencing

A graphics processing unit (GPU) implements operations, with associated op codes, to perform mixed precision mathematical operations. The GPU includes an arithmetic logic unit (ALU) with different execution paths, wherein each execution path executes a different mixed precision operation. By implementing mixed precision operations at the ALU in response to designate op codes that delineate the operations, the GPU efficiently increases the precision of specified mathematical operations while reducing execution overhead.

Processing unit with mixed precision operations

A processing unit such as a graphics processing unit (GPU) includes a plurality of vector signal processors (VSPs) that include multiply/accumulate elements. The processing unit also includes a plurality of registers associated with the plurality of VSPs. First portions of first and second matrices are fetched into the plurality of registers prior to a first round that includes a plurality of iterations. The multiply/accumulate elements perform matrix multiplication and accumulation on different combinations of subsets of the first portions of the first and second matrices in the plurality of iterations prior to fetching second portions of the first and second matrices into the plurality of registers for a second round. The accumulated results of multiplying the first portions of the first and second matrices are written into an output buffer in response to completing the plurality of iterations.

Matrix multiplication unit with flexible precision operations

A processor includes a plurality of vector sub-processors (VSPs) and a plurality of memory banks dedicated to respective VSPs. A first memory bank corresponding to a first VSP includes a first plurality of high vector general purpose register (VGPR) banks and a first plurality of low VGPR banks corresponding to the first plurality of high VGPR banks. The first memory bank further includes a plurality of operand gathering components that store operands from respective high VGPR banks and low VGPR banks. The operand gathering components are assigned to individual threads while the threads are executed by the first VSP.

Dedicated vector sub-processor system

A processing element is implemented in a stage of a pipeline and configured to execute an instruction. A first array of multiplexers is to provide information associated with the instruction to the processing element in response to the instruction being in a first set of instructions. A second array of multiplexers is to provide information associated with the instruction to the first processing element in response to the instruction being in a second set of instructions. A control unit is to gate at least one of power or a clock signal provided to the first array of multiplexers in response to the instruction being in the second set.

Pipeline including separate hardware data paths for different instruction types

A method and apparatus for performing a multi-precision computation in a plurality of arithmetic logic units (ALUs) includes pairing a first Single Instruction/Multiple Data (SIMD) block channel device with a second SIMD block channel device to create a first block pair having one-level staggering between the first and second channel devices. A third SIMD block channel device is paired with a fourth SIMD block channel device to create a second block pair having one-level staggering between the third and fourth channel devices. A plurality of source inputs are received at the first block pair and the second block pair. The first block pair computes a first result, and the second block pair computes a second result.

Pairing SIMD lanes to perform double precision operations

Arithemetic logic unit register sequencing

Systems, apparatuses, and methods for implementing a decoupled crossbar for a stream processor are disclosed. In one embodiment, a system includes at least a multi-lane execution pipeline, a vector register file, and a crossbar. The system is configured to determine if a given instruction in an instruction stream requires a permutation on data operands retrieved from the vector register file. The system conveys the data operands to the multi-lane execution pipeline on a first path which includes the crossbar responsive to determining the given instruction requires a permutation on the data operands. The crossbar then performs the necessary permutation to route the data operands to the proper processing lanes. Otherwise, the system conveys the data operands to the multi-lane execution pipeline on a second path which bypasses the crossbar responsive to determining the given instruction does not require a permutation on the input operands.

Stream processor with decoupled crossbar for cross lane operations

Systems, apparatuses, and methods for implementing a high bandwidth, low power vector register file for use by a parallel processor are disclosed. In one embodiment, a system includes at least a parallel processing unit with a plurality of processing pipeline. The parallel processing unit includes a vector arithmetic logic unit and a high bandwidth, low power, vector register file. The vector register file includes multi-bank high density random-access memories (RAMs) to satisfy register bandwidth requirements. The parallel processing unit also includes an instruction request queue and an instruction operand buffer to provide enough local bandwidth for VALU instructions and vector I/O instructions. Also, the parallel processing unit is configured to leverage the RAM's output flops as a last level cache to reduce duplicate operand requests between multiple instructions. The parallel processing unit includes a vector destination cache to provide additional R/W bandwidth for the vector register file.

Growing community of inventors

Orlando, FL, United States of America

Bin He