公开(公告)号：US20180315399A1

公开(公告)日：2018-11-01

申请号：US15819152

申请日：2017-11-21

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: G09G5/36 ,  G06T1/20 ,  G09G5/393 ,  G06N99/00 ,  G06T15/00

CPC classification number: G06F9/3001 ,  G06F7/483 ,  G06F7/5443 ,  G06F9/30014 ,  G06F9/30036 ,  G06F9/3851 ,  G06F2207/3824 ,  G06N3/0445 ,  G06N3/0454 ,  G06N3/063 ,  G06N3/08 ,  G06N20/00 ,  G06T15/005 ,  G09G5/393

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 a 32-bit intermediate product of 16-bit operands and to compute a 32-bit sum based on the 32-bit intermediate product.

公开(公告)号：US20180315398A1

公开(公告)日：2018-11-01

申请号：US15787129

申请日：2017-10-18

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: G09G5/36 ,  G06T1/20 ,  G09G5/393

CPC classification number: G06F9/3001 ,  G06F7/483 ,  G06F7/5443 ,  G06F9/30014 ,  G06F9/30036 ,  G06F9/3851 ,  G06F2207/3824 ,  G06N3/0445 ,  G06N3/0454 ,  G06N3/063 ,  G06N3/08 ,  G06N20/00 ,  G06T15/005 ,  G09G5/393

Abstract: One embodiment provides for a machine-learning hardware accelerator comprising a compute unit having an adder and a multiplier that are shared between integer data path and a floating-point datapath, the upper bits of input operands to the multiplier to be gated during floating-point operation.

公开(公告)号：US20180308207A1

公开(公告)日：2018-10-25

申请号：US15798574

申请日：2017-10-31

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

CPC classification number: G06T1/20 ,  G06F9/3001 ,  G06F9/3017 ,  G06F9/3851 ,  G06F9/3887 ,  G06F9/3895 ,  G06F9/46 ,  G06N3/063 ,  G06T15/005 ,  G06T15/04 ,  G09G5/363

Abstract: An apparatus to facilitate compute optimization is disclosed. The apparatus includes sorting logic to sort processing threads into thread groups based on bit depth of floating point thread operations.

公开(公告)号：US20180307984A1

公开(公告)日：2018-10-25

申请号：US15494971

申请日：2017-04-24

Applicant: Intel Corporation

Inventor： Altug Koker ,  Abhishek R. Appu ,  Kamal Sinha ,  Joydeep Ray ,  Balaji Vembu ,  Elmoustapha Ould-Ahmed-Vall ,  Sara S. Baghsorkhi ,  Anbang Yao ,  Kevin Nealis ,  Xiaoming Chen ,  John C. Weast ,  Justin E. Gottschlich ,  Prasoonkumar Surti ,  Chandrasekaran Sakthivel ,  Farshad Akhbari ,  Nadathur Rajagopalan Satish ,  Liwei Ma ,  Jeremy Bottleson ,  Eriko Nurvitadhi ,  Travis T. Schluessler ,  Ankur N. Shah ,  Jonathan Kennedy ,  Vasanth Ranganathan ,  Sanjeev Jahagirdar

IPC: G06N3/08 ,  G06N99/00

CPC classification number: G06N3/08 ,  G06F9/28 ,  G06F9/505 ,  G06N3/0445 ,  G06N3/0454 ,  G06N3/0481 ,  G06N3/063 ,  G06N99/005

Abstract: In an example, an apparatus comprises a plurality of execution units comprising at least a first type of execution unit and a second type of execution unit and logic, at least partially including hardware logic, to analyze a workload and assign the workload to one of the first type of execution unit or the second type of execution unit. Other embodiments are also disclosed and claimed.

公开(公告)号：US20180307980A1

公开(公告)日：2018-10-25

申请号：US15494723

申请日：2017-04-24

Applicant: Intel Corporation

Inventor： Rajkishore Barik ,  Elmoustapha Ould-Ahmed-Vall ,  Xiaoming Chen ,  Dhawal Srivastava ,  Anbang Yao ,  Kevin Nealis ,  Eriko Nurvitadhi ,  Sara S. Baghsorkhi ,  Balaji Vembu ,  Tatiana Shpeisman ,  Ping T. Tang

IPC: G06N3/08 ,  G06N3/04 ,  G06N3/063

CPC classification number: G06N3/063 ,  G06F9/3001 ,  G06F9/3017 ,  G06F9/3851 ,  G06F9/3887 ,  G06F9/3895 ,  G06N3/0445 ,  G06N3/0454 ,  G06N3/084 ,  G06T1/20

Abstract: One embodiment provides for a compute apparatus to perform machine learning operations, the apparatus comprising a decode unit to decode a single instruction into a decoded instruction, the decoded instruction to perform one or more machine learning operations, wherein the decode unit, based on parameters of the one or more machine learning operations, is to request a scheduler to schedule the one or more machine learning operations to one of an array of programmable compute units and a fixed function compute unit.

公开(公告)号：US20180300600A1

公开(公告)日：2018-10-18

申请号：US15488551

申请日：2017-04-17

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

IPC: G06N3/04 ,  G06N3/08 ,  G06N3/063

Abstract: An apparatus to facilitate optimization of a convolutional neural network (CNN) is disclosed. The apparatus includes optimization logic to receive a CNN model having a list of instructions and including pruning logic to optimize the list of instructions by eliminating branches in the list of instructions that comprise a weight value of 0.

公开(公告)号：US20250094170A1

公开(公告)日：2025-03-20

申请号：US18901027

申请日：2024-09-30

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 ,  G06F1/16 ,  G06F7/483 ,  G06F7/544 ,  G06F9/38 ,  G06F17/16 ,  G06N3/044 ,  G06N3/045 ,  G06N3/063 ,  G06N3/08 ,  G06N20/00 ,  G06T15/00 ,  G09G5/393

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 a 32-bit intermediate product of 16-bit operands and to compute a 32-bit sum based on the 32-bit intermediate product.

公开(公告)号：US12175252B2

公开(公告)日：2024-12-24

申请号：US17839856

申请日：2022-06-14

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 ,  G06F9/30 ,  G06F9/50 ,  G06F13/40 ,  G06F13/42 ,  G06F15/80 ,  G06N3/00 ,  G06N3/044 ,  G06N3/045 ,  G06N3/063 ,  G06N3/084 ,  G06N20/00 ,  G06N20/10 ,  G06T1/20

Abstract: One embodiment provides for a graphics processing unit (GPU) to accelerate machine learning operations, the GPU comprising an instruction cache to store a first instruction and a second instruction, the first instruction to cause the GPU to perform a floating-point operation, including a multi-dimensional floating-point operation, and the second instruction to cause the GPU to perform an integer operation; and a general-purpose graphics compute unit having a single instruction, multiple thread architecture, the general-purpose graphics compute unit to concurrently execute the first instruction and the second instruction.

公开(公告)号：US12141578B2

公开(公告)日：2024-11-12

申请号：US17115989

申请日：2020-12-09

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 ,  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 a 32-bit intermediate product of 16-bit operands and to compute a 32-bit sum based on the 32-bit intermediate product.

公开(公告)号：US12020135B2

公开(公告)日：2024-06-25

申请号：US17446101

申请日：2021-08-26

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

IPC: G06N3/04 ,  G06N3/063 ,  G06N3/082 ,  G06T1/20 ,  G06N3/044 ,  G06N3/045

CPC classification number: G06N3/04 ,  G06N3/063 ,  G06N3/082 ,  G06T1/20 ,  G06N3/044 ,  G06N3/045

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.