公开(公告)号：US11232533B2

公开(公告)日：2022-01-25

申请号：US16355274

申请日：2019-03-15

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

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：US20220019431A1

公开(公告)日：2022-01-20

申请号：US17305355

申请日：2021-07-06

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 ,  G06N3/04 ,  G06F9/38 ,  G06F7/544 ,  G06N3/08 ,  G06N3/063 ,  G06F7/483 ,  G09G5/393 ,  G06T15/00 ,  G06F17/16 ,  G06N20/00

Abstract: A processing apparatus is provided comprising a multiprocessor having a multithreaded architecture. The multiprocessor can execute at least one single instruction to perform parallel mixed precision matrix operations. In one embodiment the apparatus includes a memory interface and an array of multiprocessors coupled to the memory interface. At least one multiprocessor in the array of multiprocessors is configured to execute a fused multiply-add instruction in parallel across multiple threads.

公开(公告)号：US11210760B2

公开(公告)日：2021-12-28

申请号：US16928353

申请日：2020-07-14

Applicant: Intel Corporation

Inventor： Eriko Nurvitadhi ,  Balaji Vembu ,  Nicolas C. Galoppo Von Borries ,  Rajkishore Barik ,  Tsung-Han Lin ,  Kamal Sinha ,  Nadathur Rajagopalan Satish ,  Jeremy Bottleson ,  Farshad Akhbari ,  Altug Koker ,  Narayan Srinivasa ,  Dukhwan Kim ,  Sara S. Baghsorkhi ,  Justin E. Gottschlich ,  Feng Chen ,  Elmoustapha Ould-Ahmed-Vall ,  Kevin Nealis ,  Xiaoming Chen ,  Anbang Yao

IPC: G06T1/20 ,  G06N3/04 ,  G06N3/063 ,  G06F9/38 ,  G06F9/30 ,  G06N3/08

Abstract: One embodiment provides for a compute apparatus to perform machine learning operations, the compute apparatus comprising a decode unit to decode a single instruction into a decoded instruction, the decoded instruction to cause the compute apparatus to perform a complex machine learning compute operation.

公开(公告)号：US20210397925A1

公开(公告)日：2021-12-23

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 ,  G06N3/08 ,  G06N3/063 ,  G06T1/20

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.

公开(公告)号：US20210374062A1

公开(公告)日：2021-12-02

申请号：US17400415

申请日：2021-08-12

Applicant: Intel Corporation

Inventor： Abhishek R. Appu ,  Altug Koker ,  Joydeep Ray ,  David Puffer ,  Prasoonkumar Surti ,  Lakshminarayanan Striramassarma ,  Vasanth Ranganathan ,  Kiran C. Veernapu ,  Balaji Vembu ,  Pattabhiraman K

IPC: G06F12/0877 ,  G06F12/0802 ,  G06F12/0855 ,  G06F12/0806 ,  G06F12/0846 ,  G06F12/0868 ,  G06T1/60 ,  G06F12/126

Abstract: In an example, an apparatus comprises a plurality of execution units, and a cache memory communicatively coupled to the plurality of execution units, wherein the cache memory is structured into a plurality of sectors, wherein each sector in the plurality of sectors comprises at least two cache lines. Other embodiments are also disclosed and claimed.

公开(公告)号：US20210373899A1

公开(公告)日：2021-12-02

申请号：US17173923

申请日：2021-02-11

Applicant: Intel Corporation

Inventor： Balaji Vembu ,  Abhishek R. Appu ,  Joydeep Ray ,  Altug Koker

IPC: G06F9/38 ,  G06F9/46 ,  G06T1/20 ,  G06F9/52 ,  G06F9/48 ,  G06F9/54 ,  G06F15/16 ,  G06F9/50 ,  G06F15/76 ,  G06F12/0897 ,  G06F12/0866 ,  G06T1/60

Abstract: An apparatus to facilitate thread scheduling is disclosed. The apparatus includes logic to store barrier usage data based on a magnitude of barrier messages in an application kernel and a scheduler to schedule execution of threads across a plurality of multiprocessors based on the barrier usage data.

公开(公告)号：US20210334637A1

公开(公告)日：2021-10-28

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: G06N3/063 ,  G06N3/08 ,  G06N3/04 ,  G06T1/20 ,  G06F9/30 ,  G06T15/00 ,  G06F15/78 ,  G06F15/76 ,  G06F1/3287 ,  G06F1/3293

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.

公开(公告)号：US11099800B2

公开(公告)日：2021-08-24

申请号：US16881262

申请日：2020-05-22

Applicant: Intel Corporation

Inventor： Eric J. Asperheim ,  Subramaniam M. Maiyuran ,  Kiran C. Veernapu ,  Sanjeev S. Jahagirdar ,  Balaji Vembu ,  Devan Burke ,  Philip R. Laws ,  Kamal Sinha ,  Abhishek R. Appu ,  Elmoustapha Ould-Ahmed-Vall ,  Peter L. Doyle ,  Joydeep Ray ,  Travis T. Schluessler ,  John H. Feit ,  Nikos Kaburlasos ,  Jacek Kwiatkowski ,  Altug Koker

IPC: G06F3/14 ,  G06F3/01 ,  G09G5/391 ,  G06F3/0484 ,  G09G5/00

Abstract: In accordance with some embodiments, the render rate is varied across and/or up and down the display screen. This may be done based on where the user is looking in order to reduce power consumption and/or increase performance. Specifically the screen display is separated into regions, such as quadrants. Each of these regions is rendered at a rate determined by at least one of what the user is currently looking at, what the user has looked at in the past and/or what it is predicted that the user will look at next. Areas of less focus may be rendered at a lower rate, reducing power consumption in some embodiments.

公开(公告)号：US20210255957A1

公开(公告)日：2021-08-19

申请号：US17161465

申请日：2021-01-28

Applicant: Intel Corporation

Inventor： Vikranth Vemulapalli ,  Lakshminarayanan Striramassarma ,  Mike MacPherson ,  Aravindh Anantaraman ,  Ben Ashbaugh ,  Murali Ramadoss ,  William B. Sadler ,  Jonathan Pearce ,  Scott Janus ,  Brent Insko ,  Vasanth Ranganathan ,  Kamal Sinha ,  Arthur Hunter, JR. ,  Prasoonkumar Surti ,  Nicolas Galoppo von Borries ,  Joydeep Ray ,  Abhishek R. Appu ,  ElMoustapha Ould-Ahmed-Vall ,  Altug Koker ,  Sungye Kim ,  Subramaniam Maiyuran ,  Valentin Andrei

IPC: G06F12/0862 ,  G06T1/20 ,  G06T1/60

Abstract: Embodiments are generally directed to data prefetching for graphics data processing. An embodiment of an apparatus includes one or more processors including one or more graphics processing units (GPUs); and a plurality of caches to provide storage for the one or more GPUs, the plurality of caches including at least an L1 cache and an L3 cache, wherein the apparatus to provide intelligent prefetching of data by a prefetcher of a first GPU of the one or more GPUs including measuring a hit rate for the L1 cache; upon determining that the hit rate for the L1 cache is equal to or greater than a threshold value, limiting a prefetch of data to storage in the L3 cache, and upon determining that the hit rate for the L1 cache is less than a threshold value, allowing the prefetch of data to the L1 cache.

公开(公告)号：US11080813B2

公开(公告)日：2021-08-03

申请号：US16584076

申请日：2019-09-26

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 ,  G06T15/04

Abstract: An apparatus to facilitate compute optimization is disclosed. The apparatus includes a mixed precision core to perform a mixed precision multi-dimensional matrix multiply and accumulate operation on 8-bit and/or 32 bit signed or unsigned integer elements.