公开(公告)号：US12210900B2

公开(公告)日：2025-01-28

申请号：US17746201

申请日：2022-05-17

Applicant: Intel Corporation

Inventor： Joydeep Ray ,  Abhishek R. Appu ,  Altug Koker ,  Kamal Sinha ,  Balaji Vembu ,  Rajkishore Barik ,  Eriko Nurvitadhi ,  Nicolas Galoppo Von Borries ,  Tsung-Han Lin ,  Sanjeev Jahagirdar ,  Vasanth Ranganathan

IPC: G06F9/48 ,  G06T1/20

Abstract: A mechanism is described for facilitating intelligent thread scheduling at autonomous machines. A method of embodiments, as described herein, includes detecting dependency information relating to a plurality of threads corresponding to a plurality of workloads associated with tasks relating to a processor including a graphics processor. The method may further include generating a tree of thread groups based on the dependency information, where each thread group includes multiple threads, and scheduling one or more of the thread groups associated a similar dependency to avoid dependency conflicts.

公开(公告)号：US20250004861A1

公开(公告)日：2025-01-02

申请号：US18883755

申请日：2024-09-12

Applicant: Intel Corporation

Inventor： Rajkishore Barik ,  Stephan A. Herhut ,  Jaswanth Sreeram ,  Tatiana Shpeisman ,  Richard L. Hudson

IPC: G06F9/50 ,  G06F13/42

Abstract: Disclosed examples include scheduler circuitry to allocate a first task to a first work queue in memory; and a first processor circuit of a first type, the first processor circuit to cause movement of the first task from the first work queue to a second work queue in the memory, the second work queue accessible by a second processor circuit of a second type, the movement atomically performed via a read operation and a write operation to update the second work queue in a same bus cycle to prevent multiple entities from moving the first task in the same bus cycle.

公开(公告)号：US20240257294A1

公开(公告)日：2024-08-01

申请号：US18436494

申请日：2024-02-08

Applicant: Intel Corporation

Inventor： Prasoonkumar Surti ,  Narayan Srinivasa ,  Feng Chen ,  Joydeep Ray ,  Ben J. Ashbaugh ,  Nicolas C. Galoppo Von Borries ,  Eriko Nurvitadhi ,  Balaji Vembu ,  Tsung-Han Lin ,  Kamal Sinha ,  Rajkishore Barik ,  Sara S. Baghsorkhi ,  Justin E. Gottschlich ,  Altug Koker ,  Nadathur Rajagopalan Satish ,  Farshad Akhbari ,  Dukhwan Kim ,  Wenyin Fu ,  Travis T. Schluessler ,  Josh B. Mastronarde ,  Linda L. Hurd ,  John H. Feit ,  Jeffery S. Boles ,  Adam T. Lake ,  Karthik Vaidyanathan ,  Devan Burke ,  Subramaniam Maiyuran ,  Abhishek R. Appu

IPC: G06T1/20 ,  G06F8/41 ,  G06F9/455 ,  G06F9/50 ,  G06N3/044 ,  G06N3/045 ,  G06N3/063 ,  G06N3/084

CPC classification number: G06T1/20 ,  G06F9/45533 ,  G06F9/5061 ,  G06F9/5094 ,  G06N3/044 ,  G06N3/045 ,  G06N3/063 ,  G06N3/084 ,  G06F8/41 ,  G06F2009/45583

Abstract: Embodiments provide mechanisms to facilitate compute operations for deep neural networks. One embodiment comprises a graphics processing unit comprising one or more multiprocessors, at least one of the one or more multiprocessors including a register file to store a plurality of different types of operands and a plurality of processing cores. The plurality of processing cores includes a first set of processing cores of a first type and a second set of processing cores of a second type. The first set of processing cores are associated with a first memory channel and the second set of processing cores are associated with a second memory channel.

公开(公告)号：US12050984B2

公开(公告)日：2024-07-30

申请号：US17083080

申请日：2020-10-28

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: G06N3/06 ,  G06F9/30 ,  G06F9/38 ,  G06F16/17 ,  G06N3/044 ,  G06N3/045 ,  G06N3/063 ,  G06N3/084 ,  G06T1/20

CPC classification number: G06N3/063 ,  G06F9/3001 ,  G06F9/3017 ,  G06F9/3851 ,  G06F9/3887 ,  G06F9/3895 ,  G06F16/17 ,  G06N3/044 ,  G06N3/045 ,  G06N3/084 ,  G06T1/20

Abstract: One embodiment provides for a general-purpose graphics processing unit including a scheduler to schedule multiple matrix operations for execution by a general-purpose graphics processing unit. The multiple matrix operations are determined based on a single machine learning compute instruction. The single machine learning compute instruction is a convolution instruction and the multiple matrix operations are associated with a convolution operation.

公开(公告)号：US12039331B2

公开(公告)日：2024-07-16

申请号：US17967283

申请日：2022-10-17

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 ,  G06N20/00 ,  G06T15/00

CPC classification number: G06F9/3001 ,  G06F7/483 ,  G06F7/5443 ,  G06F9/30014 ,  G06F9/30036 ,  G06F9/3851 ,  G06N3/044 ,  G06N3/045 ,  G06N3/063 ,  G06N3/08 ,  G09G5/393 ,  G06F1/16 ,  G06F9/30025 ,  G06F9/3013 ,  G06F2207/3824 ,  G06N20/00 ,  G06T15/005

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.

公开(公告)号：US12001944B2

公开(公告)日：2024-06-04

申请号：US17874876

申请日：2022-07-27

Applicant: Intel Corporation

Inventor： Rajkishore Barik ,  Brian T. Lewis ,  Murali Sundaresan ,  Jeffrey Jackson ,  Feng Chen ,  Xiaoming Chen ,  Mike Macpherson

IPC: G06N3/063 ,  G06F9/46 ,  G06N3/044 ,  G06N3/045 ,  G06N3/084 ,  G06N5/01

CPC classification number: G06N3/063 ,  G06F9/46 ,  G06N3/044 ,  G06N3/045 ,  G06N3/084 ,  G06N5/01

Abstract: A mechanism is described for facilitating smart distribution of resources for deep learning autonomous machines. A method of embodiments, as described herein, includes detecting one or more sets of data from one or more sources over one or more networks, and introducing a library to a neural network application to determine an optimal point at which to apply frequency scaling without degrading performance of the neural network application at a computing device.

公开(公告)号：US20240078629A1

公开(公告)日：2024-03-07

申请号：US18466991

申请日：2023-09-14

Applicant: Intel Corporation

Inventor： Eriko Nurvitadhi ,  Balaji Vembu ,  Tsung-Han Lin ,  Kamal Sinha ,  Rajkishore Barik ,  Nicolas C. Galoppo Von Borries

IPC: G06T1/20 ,  G06F9/30 ,  G06F9/38 ,  G06F9/48 ,  G06F12/02 ,  G06F12/0811 ,  G06F12/0815 ,  G06F12/0831 ,  G06F12/0888 ,  G06F17/16 ,  G06F18/2136 ,  G06N3/04 ,  G06N3/08 ,  G06N20/00 ,  G06T1/60 ,  G06T15/00 ,  H03M7/30

CPC classification number: G06T1/20 ,  G06F9/3001 ,  G06F9/3885 ,  G06F9/4881 ,  G06F12/0207 ,  G06F12/0811 ,  G06F12/0815 ,  G06F12/0831 ,  G06F12/0888 ,  G06F17/16 ,  G06F18/2136 ,  G06N3/04 ,  G06N3/08 ,  G06N20/00 ,  G06T1/60 ,  G06T15/005 ,  H03M7/30 ,  G06F2212/1024 ,  G06F2212/302 ,  G06F2212/401 ,  G06F2212/621 ,  G06T2200/28

Abstract: Techniques to improve performance of matrix multiply operations are described in which a compute kernel can specify one or more element-wise operations to perform on output of the compute kernel before the output is transferred to higher levels of a processor memory hierarchy.

公开(公告)号：US11922535B2

公开(公告)日：2024-03-05

申请号：US18168207

申请日：2023-02-13

Applicant: Intel Corporation

Inventor： Prasoonkumar Surti ,  Narayan Srinivasa ,  Feng Chen ,  Joydeep Ray ,  Ben J. Ashbaugh ,  Nicolas C. Galoppo Von Borries ,  Eriko Nurvitadhi ,  Balaji Vembu ,  Tsung-Han Lin ,  Kamal Sinha ,  Rajkishore Barik ,  Sara S. Baghsorkhi ,  Justin E. Gottschlich ,  Altug Koker ,  Nadathur Rajagopalan Satish ,  Farshad Akhbari ,  Dukhwan Kim ,  Wenyin Fu ,  Travis T. Schluessler ,  Josh B. Mastronarde ,  Linda L. Hurd ,  John H. Feit ,  Jeffery S. Boles ,  Adam T. Lake ,  Karthik Vaidyanathan ,  Devan Burke ,  Subramaniam Maiyuran ,  Abhishek R. Appu

IPC: G06T1/20 ,  G06F9/455 ,  G06F9/50 ,  G06N3/044 ,  G06N3/045 ,  G06N3/063 ,  G06N3/084 ,  G06F8/41

CPC classification number: G06T1/20 ,  G06F9/45533 ,  G06F9/5061 ,  G06F9/5094 ,  G06N3/044 ,  G06N3/045 ,  G06N3/063 ,  G06N3/084 ,  G06F8/41 ,  G06F2009/45583

Abstract: Embodiments provide mechanisms to facilitate compute operations for deep neural networks. One embodiment comprises a graphics processing unit comprising one or more multiprocessors, at least one of the one or more multiprocessors including a register file to store a plurality of different types of operands and a plurality of processing cores. The plurality of processing cores includes a first set of processing cores of a first type and a second set of processing cores of a second type. The first set of processing cores are associated with a first memory channel and the second set of processing cores are associated with a second memory channel.

公开(公告)号：US11803935B2

公开(公告)日：2023-10-31

申请号：US17881720

申请日：2022-08-05

Applicant: Intel Corporation

Inventor： Eriko Nurvitadhi ,  Balaji Vembu ,  Tsung-Han Lin ,  Kamal Sinha ,  Rajkishore Barik ,  Nicolas C. Galoppo Von Borries

IPC: G06F17/16 ,  G06T1/20 ,  G06F9/30 ,  G06F9/38 ,  G06F12/0811 ,  G06F12/0815 ,  G06F12/0831 ,  G06F12/0888 ,  H03M7/30 ,  G06N20/00 ,  G06F12/02 ,  G06F18/2136 ,  G06F9/48 ,  G06N3/04 ,  G06N3/08 ,  G06T1/60 ,  G06T15/00

CPC classification number: G06T1/20 ,  G06F9/3001 ,  G06F9/3885 ,  G06F9/4881 ,  G06F12/0207 ,  G06F12/0811 ,  G06F12/0815 ,  G06F12/0831 ,  G06F12/0888 ,  G06F17/16 ,  G06F18/2136 ,  G06N3/04 ,  G06N3/08 ,  G06N20/00 ,  G06T1/60 ,  G06T15/005 ,  H03M7/30 ,  G06F2212/1024 ,  G06F2212/302 ,  G06F2212/401 ,  G06F2212/621 ,  G06T2200/28

Abstract: Techniques to improve performance of matrix multiply operations are described in which a compute kernel can specify one or more element-wise operations to perform on output of the compute kernel before the output is transferred to higher levels of a processor memory hierarchy.

公开(公告)号：US20230260072A1

公开(公告)日：2023-08-17

申请号：US18168207

申请日：2023-02-13

Applicant: Intel Corporation

Inventor： Prasoonkumar Surti ,  Narayan Srinivasa ,  Feng Chen ,  Joydeep Ray ,  Ben J. Ashbaugh ,  Nicolas C. Galoppo Von Borries ,  Eriko Nurvitadhi ,  Balaji Vembu ,  Tsung-Han Lin ,  Kamal Sinha ,  Rajkishore Barik ,  Sara S. Baghsorkhi ,  Justin E. Gottschlich ,  Altug Koker ,  Nadathur Rajagopalan Satish ,  Farshad Akhbari ,  Dukhwan Kim ,  Wenyin Fu ,  Travis T. Schluessler ,  Josh B. Mastronarde ,  Linda L. Hurd ,  John H. Feit ,  Jeffery S. Boles ,  Adam T. Lake ,  Karthik Vaidyanathan ,  Devan Burke ,  Subramaniam Maiyuran ,  Abhishek R. Appu

IPC: G06T1/20 ,  G06F9/455 ,  G06F9/50 ,  G06N3/063 ,  G06N3/084 ,  G06N3/044 ,  G06N3/045

CPC classification number: G06T1/20 ,  G06F9/45533 ,  G06F9/5061 ,  G06F9/5094 ,  G06N3/063 ,  G06N3/084 ,  G06N3/044 ,  G06N3/045 ,  G06F8/41

Abstract: Embodiments provide mechanisms to facilitate compute operations for deep neural networks. One embodiment comprises a graphics processing unit comprising one or more multiprocessors, at least one of the one or more multiprocessors including a register file to store a plurality of different types of operands and a plurality of processing cores. The plurality of processing cores includes a first set of processing cores of a first type and a second set of processing cores of a second type. The first set of processing cores are associated with a first memory channel and the second set of processing cores are associated with a second memory channel.