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1.
公开(公告)号:US12217053B2
公开(公告)日:2025-02-04
申请号:US18528340
申请日:2023-12-04
Applicant: Intel Corporation
Inventor: Himanshu Kaul , Mark A. Anders , Sanu K. Mathew , Anbang Yao , Joydeep Ray , Ping T. Tang , Michael S. Strickland , Xiaoming Chen , Tatiana Shpeisman , Abhishek R. Appu , Altug Koker , Kamal Sinha , Balaji Vembu , Nicolas C. Galoppo Von Borries , Eriko Nurvitadhi , Rajkishore Barik , Tsung-Han Lin , Vasanth Ranganathan , Sanjeev Jahagirdar
IPC: G06F9/30 , G06F7/483 , G06F7/544 , G06F9/38 , G06N3/044 , G06N3/045 , G06N3/063 , G06N3/08 , G09G5/393 , G06F1/16 , G06F17/16 , G06N20/00 , G06T15/00
Abstract: One embodiment provides for a graphics processing unit to accelerate machine-learning operations, the graphics processing unit comprising a multiprocessor having a single instruction, multiple thread (SIMT) architecture, the multiprocessor to execute at least one single instruction; and a first compute unit included within the multiprocessor, the at least one single instruction to cause the first compute unit to perform a two-dimensional matrix multiply and accumulate operation, wherein to perform the two-dimensional matrix multiply and accumulate operation includes to compute an intermediate product of 16-bit operands and to compute a 32-bit sum based on the intermediate product.
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公开(公告)号:US12148063B2
公开(公告)日:2024-11-19
申请号:US17960611
申请日:2022-10-05
Applicant: Intel Corporation
Inventor: Elmoustapha Ould-Ahmed-Vall , Sara S. Baghsorkhi , Anbang Yao , Kevin Nealis , Xiaoming Chen , Altug Koker , Abhishek R. Appu , John C. Weast , Mike B. Macpherson , Dukhwan Kim , Linda L. Hurd , Ben J. Ashbaugh , Barath Lakshmanan , Liwei Ma , Joydeep Ray , Ping T. Tang , Michael S. Strickland
IPC: G06T1/20 , G06F7/483 , G06F9/30 , G06F9/38 , G06F9/50 , G06N3/044 , G06N3/045 , G06N3/063 , G06N3/084 , G06N20/00 , G06T1/60 , G06F3/14 , G06T15/00
Abstract: One embodiment provides a multi-chip module accelerator usable to execute tensor data processing operations a multi-chip module. The multi-chip module may include a memory stack including multiple memory dies and parallel processor circuitry communicatively coupled to the memory stack. The parallel processor circuitry may include multiprocessor cores to execute matrix multiplication and accumulate operations. The matrix multiplication and accumulate operations may include floating-point operations that are configurable to include two-dimensional matrix multiply and accumulate operations involving inputs that have differing floating-point precisions. The floating-point operations may include a first operation at a first precision and a second operation at a second precision. The first operation may include a multiply having at least one 16-bit floating-point input and the second operation may include an accumulate having a 32-bit floating-point input.
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公开(公告)号:US20240256825A1
公开(公告)日:2024-08-01
申请号:US18435528
申请日:2024-02-07
Applicant: Intel Corporation
Inventor: Liwei Ma , Elmoustapha Ould-Ahmed-Vall , Barath Lakshmanan , Ben J. Ashbaugh , Jingyi Jin , Jeremy Bottleson , Mike B. Macpherson , Kevin Nealis , Dhawal Srivastava , Joydeep Ray , Ping T. Tang , Michael S. Strickland , Xiaoming Chen , Anbang Yao , Tatiana Shpeisman , Altug Koker , Abhishek R. Appu
Abstract: A library of machine learning primitives is provided to optimize a machine learning model to improve the efficiency of inference operations. In one embodiment a trained convolutional neural network (CNN) model is processed into a trained CNN model via pruning, convolution window optimization, and quantization.
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公开(公告)号:US11748606B2
公开(公告)日:2023-09-05
申请号:US17317857
申请日:2021-05-11
Applicant: INTEL CORPORATION
Inventor: Kamal Sinha , Balaji Vembu , Eriko Nurvitadhi , Nicolas C. Galoppo Von Borries , Rajkishore Barik , Tsung-Han Lin , Joydeep Ray , Ping T. Tang , Michael S. Strickland , Xiaoming Chen , Anbang Yao , Tatiana Shpeisman , Abhishek R. Appu , Altug Koker , Farshad Akhbari , Narayan Srinivasa , Feng Chen , Dukhwan Kim , Nadathur Rajagopalan Satish , John C. Weast , Mike B. MacPherson , Linda L. Hurd , Vasanth Ranganathan , Sanjeev S. Jahagirdar
IPC: G06F7/50 , G06N3/063 , G06N3/08 , G06N3/04 , G06T1/20 , G06F9/30 , G06T15/00 , G06F15/78 , G06F15/76 , G06F1/3287 , G06F1/3293 , G06N3/084 , G06N3/044 , G06N3/045 , G06T1/60
CPC classification number: G06N3/063 , G06F1/3287 , G06F1/3293 , G06F9/30014 , G06F9/30036 , G06F15/76 , G06F15/78 , G06N3/04 , G06N3/044 , G06N3/045 , G06N3/08 , G06N3/084 , G06T1/20 , G06T15/005 , G06T1/60
Abstract: In an example, an apparatus comprises a compute engine comprising a high precision component and a low precision component; and logic, at least partially including hardware logic, to receive instructions in the compute engine; select at least one of the high precision component or the low precision component to execute the instructions; and apply a gate to at least one of the high precision component or the low precision component to execute the instructions. Other embodiments are also disclosed and claimed.
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5.
公开(公告)号:US20220357945A1
公开(公告)日:2022-11-10
申请号:US17834482
申请日:2022-06-07
Applicant: Intel Corporation
Inventor: Himanshu Kaul , Mark A. Anders , Sanu K. Mathew , Anbang Yao , Joydeep Ray , Ping T. Tang , Michael S. Strickland , Xiaoming Chen , Tatiana Shpeisman , Abhishek R. Appu , Altug Koker , Kamal Sinha , Balaji Vembu , Nicolas C. Galoppo Von Borries , Eriko Nurvitadhi , Rajkishore Barik , Tsung-Han Lin , Vasanth Ranganathan , Sanjeev Jahagirdar
Abstract: One embodiment provides a graphics processor comprising a memory controller and a graphics processing resource coupled with the memory controller. The graphics processing resource includes circuitry configured to execute an instruction to perform a matrix operation on first input including weight data and second input including input activation data, generate intermediate data based on a result of the matrix operation, quantize the intermediate data to a floating-point format determined based on a statistical distribution of first output data, and output, as second output data, quantized intermediate data in a determined floating-point format.
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公开(公告)号:US20220261948A1
公开(公告)日:2022-08-18
申请号:US17684187
申请日:2022-03-01
Applicant: Intel Corporation
Inventor: Abhishek R. Appu , Altug Koker , Linda L. Hurd , Dukhwan Kim , Mike B. Macpherson , John C. Weast , Feng Chen , Farshad Akhbari , Narayan Srinivasa , Nadathur Rajagopalan Satish , Joydeep Ray , Ping T. Tang , Michael S. Strickland , Xiaoming Chen , Anbang Yao , Tatiana Shpeisman
IPC: G06T1/20 , G06F3/14 , G06F9/30 , G06F9/38 , G06N3/04 , G06N3/063 , G06N3/08 , G06T15/00 , G09G5/36
Abstract: An apparatus to facilitate compute optimization is disclosed. The apparatus includes a mixed precision core including mixed-precision execution circuitry to execute one or more of the mixed-precision instructions to perform a mixed-precision dot-product operation comprising to perform a set of multiply and accumulate operations.
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公开(公告)号:US20220245753A1
公开(公告)日:2022-08-04
申请号:US17720804
申请日:2022-04-14
Applicant: Intel Corporation
Inventor: Elmoustapha Ould-Ahmed-Vall , Sara S. Baghsorkhi , Anbang Yao , Kevin Nealis , Xiaoming Chen , Altug Koker , Abhishek R. Appu , John C. Weast , Mike B. Macpherson , Dukhwan Kim , Linda L. Hurd , Ben J. Ashbaugh , Barath Lakshmanan , Liwei Ma , Joydeep Ray , Ping T. Tang , Michael S. Strickland
IPC: G06T1/20 , G06F7/483 , G06N3/08 , G06F9/30 , G06N3/04 , G06N3/063 , G06F9/50 , G06F9/38 , G06N20/00
Abstract: Embodiments described herein provide a graphics processor that can perform a variety of mixed and multiple precision instructions and operations. One embodiment provides a streaming multiprocessor that can concurrently execute multiple thread groups, wherein the streaming multiprocessor includes a single instruction, multiple thread (SIMT) architecture and the streaming multiprocessor is to execute multiple threads for each of multiple instructions. The streaming multiprocessor can perform concurrent integer and floating-point operations and includes a mixed precision core to perform operations at multiple or mixed precisions and dynamic ranges.
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公开(公告)号:US11308574B2
公开(公告)日:2022-04-19
申请号:US16983080
申请日:2020-08-03
Applicant: Intel Corporation
Inventor: Elmoustapha Ould-Ahmed-Vall , Sara S. Baghsorkhi , Anbang Yao , Kevin Nealis , Xiaoming Chen , Altug Koker , Abhishek R. Appu , John C. Weast , Mike B. Macpherson , Dukhwan Kim , Linda L. Hurd , Ben J. Ashbaugh , Barath Lakshmanan , Liwei Ma , Joydeep Ray , Ping T. Tang , Michael S. Strickland
IPC: G06T1/20 , G06F7/483 , G06N3/08 , G06F9/30 , G06N3/04 , G06N3/063 , G06F9/50 , G06F9/38 , G06N20/00 , G06F3/14 , G06T1/60 , G06T15/00
Abstract: Embodiments described herein provide a graphics processor that can perform a variety of mixed and multiple precision instructions and operations. One embodiment provides a streaming multiprocessor that can concurrently execute multiple thread groups, wherein the streaming multiprocessor includes a single instruction, multiple thread (SIMT) architecture and the streaming multiprocessor is to execute multiple threads for each of multiple instructions. The streaming multiprocessor can perform concurrent integer and floating-point operations and includes a mixed precision core to perform operations at multiple precisions.
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公开(公告)号:US20190146800A1
公开(公告)日:2019-05-16
申请号:US16227645
申请日:2018-12-20
Applicant: Intel Corporation
Inventor: ELMOUSTAPHA OULD-AHMED-VALL , BARATH LAKSHMANAN , TATIANA SHPEISMAN , Joydeep Ray , Ping T. Tang , Michael Strickland , Xiaoming Chen , Anbang Yao , Ben J. Ashbaugh , Linda L. Hurd , Liwei Ma
IPC: G06F9/38 , G06N20/00 , G06F15/80 , G06F13/42 , G06F9/30 , G06F13/40 , G06T1/20 , G06N3/00 , G06F9/50
Abstract: One embodiment provides for a general-purpose graphics processing unit comprising a streaming multiprocessor having a single instruction, multiple thread (SIMT) architecture including hardware multithreading. The streaming multiprocessor comprises multiple processing blocks including multiple processing cores. The processing cores include independent integer and floating-point data paths that are configurable to concurrently execute multiple independent instructions. A memory is coupled with the multiple processing blocks.
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公开(公告)号:US20180315157A1
公开(公告)日:2018-11-01
申请号:US15581167
申请日:2017-04-28
Applicant: Intel Corporation
Inventor: Elmoustapha Ould-Ahmed-Vall , Sara S. Baghsorkhi , Anbang Yao , Kevin Nealis , Xiaoming Chen , Altug Koker , Abhishek R. Appu , John C. Weast , Mike B. Macpherson , Dukhwan Kim , Linda L. Hurd , Ben . Ashbaugh , Barath Lakshmanan , Liwei Ma , Joydeep Ray , Ping T. Tang , Michael S. Strickland
Abstract: One embodiment provides a general-purpose graphics processing unit comprising a dynamic precision floating-point unit including a control unit having precision tracking hardware logic to track an available number of bits of precision for computed data relative to a target precision, wherein the dynamic precision floating-point unit includes computational logic to output data at multiple precisions.
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