公开(公告)号：US20240354559A1

公开(公告)日：2024-10-24

申请号：US18646021

申请日：2024-04-25

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 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：US11995029B2

公开(公告)日：2024-05-28

申请号：US17428527

申请日：2020-03-14

Applicant: Intel Corporation

Inventor： Lakshminarayanan Striramassarma ,  Prasoonkumar Surti ,  Varghese George ,  Ben Ashbaugh ,  Aravindh Anantaraman ,  Valentin Andrei ,  Abhishek Appu ,  Nicolas Galoppo Von Borries ,  Altug Koker ,  Mike Macpherson ,  Subramaniam Maiyuran ,  Nilay Mistry ,  Elmoustapha Ould-Ahmed-Vall ,  Selvakumar Panneer ,  Vasanth Ranganathan ,  Joydeep Ray ,  Ankur Shah ,  Saurabh Tangri

IPC: G06F12/00 ,  G06F7/544 ,  G06F7/575 ,  G06F7/58 ,  G06F9/30 ,  G06F9/38 ,  G06F9/50 ,  G06F12/02 ,  G06F12/06 ,  G06F12/0802 ,  G06F12/0804 ,  G06F12/0811 ,  G06F12/0862 ,  G06F12/0866 ,  G06F12/0871 ,  G06F12/0875 ,  G06F12/0882 ,  G06F12/0888 ,  G06F12/0891 ,  G06F12/0893 ,  G06F12/0895 ,  G06F12/0897 ,  G06F12/1009 ,  G06F12/128 ,  G06F15/78 ,  G06F15/80 ,  G06F17/16 ,  G06F17/18 ,  G06T1/20 ,  G06T1/60 ,  H03M7/46 ,  G06N3/08 ,  G06T15/06

CPC classification number: G06F15/7839 ,  G06F7/5443 ,  G06F7/575 ,  G06F7/588 ,  G06F9/3001 ,  G06F9/30014 ,  G06F9/30036 ,  G06F9/3004 ,  G06F9/30043 ,  G06F9/30047 ,  G06F9/30065 ,  G06F9/30079 ,  G06F9/3887 ,  G06F9/5011 ,  G06F9/5077 ,  G06F12/0215 ,  G06F12/0238 ,  G06F12/0246 ,  G06F12/0607 ,  G06F12/0802 ,  G06F12/0804 ,  G06F12/0811 ,  G06F12/0862 ,  G06F12/0866 ,  G06F12/0871 ,  G06F12/0875 ,  G06F12/0882 ,  G06F12/0888 ,  G06F12/0891 ,  G06F12/0893 ,  G06F12/0895 ,  G06F12/0897 ,  G06F12/1009 ,  G06F12/128 ,  G06F15/8046 ,  G06F17/16 ,  G06F17/18 ,  G06T1/20 ,  G06T1/60 ,  H03M7/46 ,  G06F9/3802 ,  G06F9/3818 ,  G06F9/3867 ,  G06F2212/1008 ,  G06F2212/1021 ,  G06F2212/1044 ,  G06F2212/302 ,  G06F2212/401 ,  G06F2212/455 ,  G06F2212/60 ,  G06N3/08 ,  G06T15/06

Abstract: Multi-tile Memory Management for Detecting Cross Tile Access, Providing Multi-Tile Inference Scaling with multicasting of data via copy operation, and Providing Page Migration are disclosed herein. In one embodiment, a graphics processor for a multi-tile architecture includes a first graphics processing unit (GPU) having a memory and a memory controller, a second graphics processing unit (GPU) having a memory and a cross-GPU fabric to communicatively couple the first and second GPUs. The memory controller is configured to determine whether frequent cross tile memory accesses occur from the first GPU to the memory of the second GPU in the multi-GPU configuration and to send a message to initiate a data transfer mechanism when frequent cross tile memory accesses occur from the first GPU to the memory of the second GPU.

公开(公告)号：US11861759B2

公开(公告)日：2024-01-02

申请号：US17580352

申请日：2022-01-20

Applicant: Intel Corporation

Inventor： Joydeep Ray ,  Aravindh Anantaraman ,  Valentin Andrei ,  Abhishek R. Appu ,  Nicolas Galoppo von Borries ,  Varghese George ,  Altug Koker ,  Elmoustapha Ould-Ahmed-Vall ,  Mike Macpherson ,  Subramaniam Maiyuran

IPC: G06T1/20 ,  G06F9/38 ,  G06T1/60 ,  G06T15/00

CPC classification number: G06T1/20 ,  G06F9/3802 ,  G06F9/3877 ,  G06T1/60 ,  G06T15/005

Abstract: Embodiments are generally directed to memory prefetching in multiple GPU environment. An embodiment of an apparatus includes multiple processors including a host processor and multiple graphics processing units (GPUs) to process data, each of the GPUs including a prefetcher and a cache; and a memory for storage of data, the memory including a plurality of memory elements, wherein the prefetcher of each of the GPUs is to prefetch data from the memory to the cache of the GPU; and wherein the prefetcher of a GPU is prohibited from prefetching from a page that is not owned by the GPU or by the host processor.

公开(公告)号：US11620256B2

公开(公告)日：2023-04-04

申请号：US17732308

申请日：2022-04-28

Applicant: Intel Corporation

Inventor： Altug Koker ,  Joydeep Ray ,  Ben Ashbaugh ,  Jonathan Pearce ,  Abhishek Appu ,  Vasanth Ranganathan ,  Lakshminarayanan Striramassarma ,  Elmoustapha Ould-Ahmed-Vall ,  Aravindh Anantaraman ,  Valentin Andrei ,  Nicolas Galoppo Von Borries ,  Varghese George ,  Yoav Harel ,  Arthur Hunter, Jr. ,  Brent Insko ,  Scott Janus ,  Pattabhiraman K ,  Mike Macpherson ,  Subramaniam Maiyuran ,  Marian Alin Petre ,  Murali Ramadoss ,  Shailesh Shah ,  Kamal Sinha ,  Prasoonkumar Surti ,  Vikranth Vemulapalli

IPC: G06F12/08 ,  G06F15/78 ,  G06F9/30 ,  G06F9/38 ,  G06F17/18 ,  G06F12/0802 ,  G06F7/544 ,  G06F7/575 ,  G06F12/02 ,  G06F12/0866 ,  G06F12/0875 ,  G06F12/0895 ,  G06F12/128 ,  G06F12/06 ,  G06F12/1009 ,  G06T1/20 ,  G06T1/60 ,  H03M7/46 ,  G06F12/0811 ,  G06F15/80 ,  G06F17/16 ,  G06F7/58 ,  G06F12/0871 ,  G06F12/0862 ,  G06F12/0897 ,  G06F9/50 ,  G06F12/0804 ,  G06F12/0882 ,  G06F12/0891 ,  G06F12/0893 ,  G06T15/06 ,  G06N3/08

Abstract: Systems and methods for improving cache efficiency and utilization are disclosed. In one embodiment, a graphics processor includes processing resources to perform graphics operations and a cache controller of a cache coupled to the processing resources. The cache controller is configured to control cache priority by determining whether default settings or an instruction will control cache operations for the cache.

公开(公告)号：US20210103550A1

公开(公告)日：2021-04-08

申请号：US17122905

申请日：2020-12-15

Applicant: Intel Corporation

Inventor： Abhishek Appu ,  Subramaniam Maiyuran ,  Mike Macpherson ,  Fangwen Fu ,  Jiasheng Chen ,  Varghese George ,  Vasanth Ranganathan ,  Ashutosh Garg ,  Joydeep Ray

IPC: G06F15/80 ,  G06F7/544 ,  G06F9/50 ,  G06F17/16 ,  G06N3/08 ,  G06N3/04

Abstract: Embodiments described herein include software, firmware, and hardware logic that provides techniques to perform arithmetic on sparse data via a systolic processing unit. One embodiment provides for data aware sparsity via compressed bitstreams. One embodiment provides for block sparse dot product instructions. One embodiment provides for a depth-wise adapter for a systolic array.

公开(公告)号：US12210477B2

公开(公告)日：2025-01-28

申请号：US17428530

申请日：2020-03-14

Applicant: Intel Corporation

Inventor： Altug Koker ,  Joydeep Ray ,  Ben Ashbaugh ,  Jonathan Pearce ,  Abhishek Appu ,  Vasanth Ranganathan ,  Lakshminarayanan Striramassarma ,  Elmoustapha Ould-Ahmed-Vall ,  Aravindh Anantaraman ,  Valentin Andrei ,  Nicolas Galoppo Von Borries ,  Varghese George ,  Yoav Harel ,  Arthur Hunter, Jr. ,  Brent Insko ,  Scott Janus ,  Pattabhiraman K ,  Mike Macpherson ,  Subramaniam Maiyuran ,  Marian Alin Petre ,  Murali Ramadoss ,  Shailesh Shah ,  Kamal Sinha ,  Prasoonkumar Surti ,  Vikranth Vemulapalli

IPC: G06F15/78 ,  G06F7/544 ,  G06F7/575 ,  G06F7/58 ,  G06F9/30 ,  G06F9/38 ,  G06F9/50 ,  G06F12/02 ,  G06F12/06 ,  G06F12/0802 ,  G06F12/0804 ,  G06F12/0811 ,  G06F12/0862 ,  G06F12/0866 ,  G06F12/0871 ,  G06F12/0875 ,  G06F12/0882 ,  G06F12/0888 ,  G06F12/0891 ,  G06F12/0893 ,  G06F12/0895 ,  G06F12/0897 ,  G06F12/1009 ,  G06F12/128 ,  G06F15/80 ,  G06F17/16 ,  G06F17/18 ,  G06T1/20 ,  G06T1/60 ,  H03M7/46 ,  G06N3/08 ,  G06T15/06

Abstract: Systems and methods for improving cache efficiency and utilization are disclosed. In one embodiment, a graphics processor includes processing resources to perform graphics operations and a cache controller of a cache coupled to the processing resources. The cache controller is configured to control cache priority by determining whether default settings or an instruction will control cache operations for the cache.

公开(公告)号：US20240086357A1

公开(公告)日：2024-03-14

申请号：US18516716

申请日：2023-11-21

Applicant: Intel Corporation

Inventor： Altug Koker ,  Joydeep Ray ,  Aravindh Anantaraman ,  Valentin Andrei ,  Abhishek Appu ,  Sean Coleman ,  Nicolas Galoppo Von Borries ,  Varghese George ,  Pattabhiraman K ,  SungYe Kim ,  Mike Macpherson ,  Subramaniam Maiyuran ,  Elmoustapha Ould-Ahmed-Vall ,  Vasanth Ranganathan ,  James Valerio

IPC: G06F15/78 ,  G06F7/544 ,  G06F7/575 ,  G06F7/58 ,  G06F9/30 ,  G06F9/38 ,  G06F9/50 ,  G06F12/02 ,  G06F12/06 ,  G06F12/0802 ,  G06F12/0804 ,  G06F12/0811 ,  G06F12/0862 ,  G06F12/0866 ,  G06F12/0871 ,  G06F12/0875 ,  G06F12/0882 ,  G06F12/0888 ,  G06F12/0891 ,  G06F12/0893 ,  G06F12/0895 ,  G06F12/0897 ,  G06F12/1009 ,  G06F12/128 ,  G06F15/80 ,  G06F17/16 ,  G06F17/18 ,  G06T1/20 ,  G06T1/60 ,  H03M7/46

CPC classification number: G06F15/7839 ,  G06F7/5443 ,  G06F7/575 ,  G06F7/588 ,  G06F9/3001 ,  G06F9/30014 ,  G06F9/30036 ,  G06F9/3004 ,  G06F9/30043 ,  G06F9/30047 ,  G06F9/30065 ,  G06F9/30079 ,  G06F9/3887 ,  G06F9/5011 ,  G06F9/5077 ,  G06F12/0215 ,  G06F12/0238 ,  G06F12/0246 ,  G06F12/0607 ,  G06F12/0802 ,  G06F12/0804 ,  G06F12/0811 ,  G06F12/0862 ,  G06F12/0866 ,  G06F12/0871 ,  G06F12/0875 ,  G06F12/0882 ,  G06F12/0888 ,  G06F12/0891 ,  G06F12/0893 ,  G06F12/0895 ,  G06F12/0897 ,  G06F12/1009 ,  G06F12/128 ,  G06F15/8046 ,  G06F17/16 ,  G06F17/18 ,  G06T1/20 ,  G06T1/60 ,  H03M7/46 ,  G06T15/06

Abstract: Systems and methods for updating remote memory side caches in a multi-GPU configuration are disclosed herein. In one embodiment, a graphics processor for a multi-tile architecture includes a first graphics processing unit (GPU) having a first memory, a first memory side cache memory, a first communication fabric, and a first memory management unit (MMU). The graphics processor includes a second graphics processing unit (GPU) having a second memory, a second memory side cache memory, a second memory management unit (MMU), and a second communication fabric that is communicatively coupled to the first communication fabric. The first MMU is configured to control memory requests for the first memory, to update content in the first memory, to update content in the first memory side cache memory, and to determine whether to update the content in the second memory side cache memory.

公开(公告)号：US11676322B2

公开(公告)日：2023-06-13

申请号：US17500631

申请日：2021-10-13

Applicant: Intel Corporation

Inventor： Hugues Labbe ,  Darrel Palke ,  Sherine Abdelhak ,  Jill Boyce ,  Varghese George ,  Scott Janus ,  Adam Lake ,  Zhijun Lei ,  Zhengmin Li ,  Mike Macpherson ,  Carl Marshall ,  Selvakumar Panneer ,  Prasoonkumar Surti ,  Karthik Veeramani ,  Deepak Vembar ,  Vallabhajosyula Srinivasa Somayazulu

IPC: G06T17/20 ,  G06N3/08 ,  G06T1/60 ,  G06T15/40 ,  G06T1/20 ,  G06T15/00

CPC classification number: G06T15/005 ,  G06N3/08 ,  G06T1/20 ,  G06T1/60 ,  G06T15/40 ,  G06T17/20

Abstract: One embodiment provides for a graphics processor comprising a block of graphics compute units, a graphics processor pipeline coupled to the block of graphics compute units, and a programmable neural network unit including one or more neural network hardware blocks. The programmable neural network unit is coupled with the block of graphics compute units and the graphics processor pipeline. The one or more neural network hardware blocks include hardware to perform neural network operations and activation operations for a layer of a neural network. The programmable neural network unit can configure settings of one or more hardware blocks within the graphics processor pipeline based on a machine learning model trained to optimize performance of a set of workloads.

公开(公告)号：US20220413851A1

公开(公告)日：2022-12-29

申请号：US17304794

申请日：2021-06-25

Applicant: Intel Corporation

Inventor： Chandra Gurram ,  Wei-yu Chen ,  Fangwen Fu ,  Sabareesh Ganapathy ,  Varghese George ,  Guei-Yuan Lueh ,  Subramaniam Maiyuran ,  Mike Macpherson ,  Supratim Pal ,  Jorge Parra

IPC: G06F9/30 ,  G06F17/16 ,  G06F7/483

Abstract: A processing apparatus includes a general-purpose parallel processing engine including a set of multiple processing elements including a single precision floating-point unit, a double precision floating point unit, and an integer unit; a matrix accelerator including one or more systolic arrays; a first register file coupled with a first read control circuit, wherein the first read control circuit couples with the set of multiple processing elements and the matrix accelerator to arbitrate read requests to the first register file from the set of multiple processing elements and the matrix accelerator; and a second register file coupled with a second read control circuit, wherein the second read control circuit couples with the matrix accelerator to arbitrate read requests to the second register file from the matrix accelerator and limit access to the second register file by the set of multiple processing elements.

公开(公告)号：US11410024B2

公开(公告)日：2022-08-09

申请号：US15581152

申请日：2017-04-28

Applicant: Intel Corporation

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

IPC: G06N3/063 ,  G06N3/04 ,  G06N3/08 ,  G06N5/00 ,  G06F9/46

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 optimal point at which to apply frequency scaling without degrading performance of the neural network application at a computing device.