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公开(公告)号:US11669329B2
公开(公告)日:2023-06-06
申请号:US17723312
申请日:2022-04-18
Applicant: Intel Corporation
Inventor: Supratim Pal , Sasikanth Avancha , Ishwar Bhati , Wei-Yu Chen , Dipankar Das , Ashutosh Garg , Chandra S. Gurram , Junjie Gu , Guei-Yuan Lueh , Subramaniam Maiyuran , Jorge E. Parra , Sudarshan Srinivasan , Varghese George
CPC classification number: G06F9/3802 , G06F9/3001 , G06F9/30018 , G06F9/30145
Abstract: Embodiments described herein provide for an instruction and associated logic to enable a vector multiply add instructions with automatic zero skipping for sparse input. One embodiment provides for a general-purpose graphics processor comprising logic to perform operations comprising fetching a hardware macro instruction having a predicate mask, a repeat count, and a set of initial operands, where the initial operands include a destination operand and multiple source operands. The hardware macro instruction is configured to perform one or more multiply/add operations on input data associated with a set of matrices.
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公开(公告)号:US11275998B2
公开(公告)日:2022-03-15
申请号:US15994930
申请日:2018-05-31
Applicant: Intel Corporation
Inventor: Martin Langhammer , Sudarshan Srinivasan , Gregg William Baeckler , Duncan Moss , Sasikanth Avancha , Dipankar Das
IPC: G06N3/08 , G06N3/04 , G06N3/063 , G06F17/16 , G06F7/501 , G06F5/01 , G06F7/509 , H03M7/40 , H03M7/42 , H03M7/30
Abstract: The present disclosure relates generally to techniques for improving the implementation of certain operations on an integrated circuit. In particular, deep learning techniques, which may use a deep neural network (DNN) topology, may be implemented more efficiently using low-precision weights and activation values by efficiently performing down conversion of data to a lower precision and by preventing data overflow during suitable computations. Further, by more efficiently mapping multipliers to programmable logic on the integrated circuit device, the resources used by the DNN topology to perform, for example, inference tasks may be reduced, resulting in improved integrated circuit operating speeds.
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公开(公告)号:US11314515B2
公开(公告)日:2022-04-26
申请号:US16724831
申请日:2019-12-23
Applicant: Intel Corporation
Inventor: Supratim Pal , Sasikanth Avancha , Ishwar Bhati , Wei-Yu Chen , Dipankar Das , Ashutosh Garg , Chandra S. Gurram , Junjie Gu , Guei-Yuan Lueh , Subramaniam Maiyuran , Jorge E. Parra , Sudarshan Srinivasan , Varghese George
Abstract: Embodiments described herein provide for an instruction and associated logic to enable a vector multiply add instructions with automatic zero skipping for sparse input. One embodiment provides for a general-purpose graphics processor comprising logic to perform operations comprising fetching a hardware macro instruction having a predicate mask, a repeat count, and a set of initial operands, where the initial operands include a destination operand and multiple source operands. The hardware macro instruction is configured to perform one or more multiply/add operations on input data associated with a set of matrices.
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公开(公告)号:US11249910B2
公开(公告)日:2022-02-15
申请号:US16717647
申请日:2019-12-17
Applicant: Intel Corporation
Inventor: Aravindh Anantaraman , Srinivas Sridharan , Ajaya Durg , Mohammad R. Haghighat , Mikhail E. Smorkalov , Sudarshan Srinivasan
IPC: G06F12/08 , G06F3/06 , G06F12/0868 , G06F12/10 , G06F16/2455 , G06N3/08 , G06F12/0877 , G06F12/0871
Abstract: Systems, apparatuses and methods may provide for technology that detects a runtime call to a communication library, wherein the runtime call identifies a memory buffer, determines that a class of service (CLOS) attribute is associated with the memory buffer, and issues a driver instruction to modify the CLOS attribute in response to the runtime call.
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公开(公告)号:US20190042939A1
公开(公告)日:2019-02-07
申请号:US15994930
申请日:2018-05-31
Applicant: Intel Corporation
Inventor: Martin Langhammer , Sudarshan Srinivasan , Gregg William Baeckler , Duncan Moss , Sasikanth Avancha , Dipankar Das
Abstract: The present disclosure relates generally to techniques for improving the implementation of certain operations on an integrated circuit. In particular, deep learning techniques, which may use a deep neural network (DNN) topology, may be implemented more efficiently using low-precision weights and activation values by efficiently performing down conversion of data to a lower precision and by preventing data overflow during suitable computations. Further, by more efficiently mapping multipliers to programmable logic on the integrated circuit device, the resources used by the DNN topology to perform, for example, inference tasks may be reduced, resulting in improved integrated circuit operating speeds.
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公开(公告)号:US20220326953A1
公开(公告)日:2022-10-13
申请号:US17723312
申请日:2022-04-18
Applicant: Intel Corporation
Inventor: Supratim Pal , Sasikanth Avancha , Ishwar Bhati , Wei-Yu Chen , Dipankar Das , Ashutosh Garg , Chandra S. Gurram , Junjie Gu , Guei-Yuan Lueh , Subramaniam Maiyuran , Jorge E. Parra , Sudarshan Srinivasan , Varghese George
Abstract: Embodiments described herein provide for an instruction and associated logic to enable a vector multiply add instructions with automatic zero skipping for sparse input. One embodiment provides for a general-purpose graphics processor comprising logic to perform operations comprising fetching a hardware macro instruction having a predicate mask, a repeat count, and a set of initial operands, where the initial operands include a destination operand and multiple source operands. The hardware macro instruction is configured to perform one or more multiply/add operations on input data associated with a set of matrices.
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公开(公告)号:US20210191724A1
公开(公告)日:2021-06-24
申请号:US16724831
申请日:2019-12-23
Applicant: Intel Corporation
Inventor: Supratim Pal , Sasikanth Avancha , Ishwar Bhati , Wei-Yu Chen , Dipankar Das , Ashutosh Garg , Chandra S. Gurram , Junjie Gu , Guei-Yuan Lueh , Subramaniam Maiyuran , Jorge E. Parra , Sudarshan Srinivasan , Varghese George
Abstract: Embodiments described herein provide for an instruction and associated logic to enable a vector multiply add instructions with automatic zero skipping for sparse input. One embodiment provides for a general-purpose graphics processor comprising logic to perform operations comprising fetching a hardware macro instruction having a predicate mask, a repeat count, and a set of initial operands, where the initial operands include a destination operand and multiple source operands. The hardware macro instruction is configured to perform one or more multiply/add operations on input data associated with a set of matrices.
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