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：US09030984B2

公开(公告)日：2015-05-12

申请号：US13743652

申请日：2013-01-17

Applicant: Intel Corporation

Inventor： Rongzhen Yang ,  Hujun Yin ,  Andreas Schmidt ,  Feng Chen ,  Jong-Kae Fwu

IPC: G08C17/00 ,  H04W52/24 ,  H04W52/36 ,  H04W72/04

CPC classification number: H04W52/242 ,  H04W52/06 ,  H04W52/08 ,  H04W52/10 ,  H04W52/367 ,  H04W52/383 ,  H04W72/0446

Abstract: Power control schemes for D2D communications are described. The schemes control the transmission power of a UE during D2D communications in a manner that reduces interference while maintaining the D2D communications link and the cellular link with the eNB. Open-loop and/or closed-loop techniques are employed.

Abstract translation: 描述了D2D通信的功率控制方案。 这些方案在D2D通信期间以降低干扰的方式控制UE的发送功率，同时维持D2D通信链路和与eNB的蜂窝链路。 采用开环和/或闭环技术。

公开(公告)号：US20250166115A1

公开(公告)日：2025-05-22

申请号：US18971949

申请日：2024-12-06

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

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：US11947977B2

公开(公告)日：2024-04-02

申请号：US18146289

申请日：2022-12-23

Applicant: Intel Corporation

Inventor： Li Xu ,  Haihao Xiang ,  Feng Chen ,  Travis Schluessler ,  Yuheng Zhang ,  Sen Lin

IPC: G06F9/448 ,  G06F16/215 ,  G06T1/20 ,  G06T1/60

CPC classification number: G06F9/4488 ,  G06F16/215 ,  G06T1/20 ,  G06T1/60

Abstract: Embodiments are generally directed to a system and method for adapting executable object to a processing unit. An embodiment of a method to adapt an executable object from a first processing unit to a second processing unit, comprises: adapting the executable object optimized for the first processing unit of a first architecture, to the second processing unit of a second architecture, wherein the second architecture is different from the first architecture, wherein the executable object is adapted to perform on the second processing unit based on a plurality of performance metrics collected while the executable object is performed on the first processing unit and the second processing unit.

公开(公告)号：US11748298B2

公开(公告)日：2023-09-05

申请号：US17826674

申请日：2022-05-27

Applicant: Intel Corporation

Inventor： Altug Koker ,  Farshad Akhbari ,  Feng Chen ,  Dukhwan Kim ,  Narayan Srinivasa ,  Nadathur Rajagopalan Satish ,  Liwei Ma ,  Jeremy Bottleson ,  Eriko Nurvitadhi ,  Joydeep Ray ,  Ping T. Tang ,  Michael S. Strickland ,  Xiaoming Chen ,  Tatiana Shpeisman ,  Abhishek R. Appu

IPC: G06F15/80 ,  G06F13/40 ,  G06T1/20 ,  G06F9/30 ,  G06F13/00 ,  G06N3/063 ,  G06N3/084 ,  G06N3/044 ,  G06N3/045 ,  G06N3/048

CPC classification number: G06F15/8007 ,  G06F9/3004 ,  G06F13/00 ,  G06F13/4027 ,  G06N3/044 ,  G06N3/045 ,  G06N3/048 ,  G06N3/063 ,  G06N3/084 ,  G06T1/20

Abstract: An integrated circuit (IC) package apparatus is disclosed. The IC package includes one or more processing units and a bridge, mounted below the one or more processing unit, including one or more arithmetic logic units (ALUs) to perform atomic operations.

公开(公告)号：US20230236847A1

公开(公告)日：2023-07-27

申请号：US18146289

申请日：2022-12-23

Applicant: Intel Corporation

Inventor： Li Xu ,  Haihao Xiang ,  Feng Chen ,  Travis Schluessler ,  Yuheng Zhang ,  Sen Lin

IPC: G06F9/448 ,  G06F16/215 ,  G06T1/60 ,  G06T1/20

CPC classification number: G06F9/4488 ,  G06F16/215 ,  G06T1/60 ,  G06T1/20

Abstract: Embodiments are generally directed to a system and method for adapting executable object to a processing unit. An embodiment of a method to adapt an executable object from a first processing unit to a second processing unit, comprises: adapting the executable object optimized for the first processing unit of a first architecture, to the second processing unit of a second architecture, wherein the second architecture is different from the first architecture, wherein the executable object is adapted to perform on the second processing unit based on a plurality of performance metrics collected while the executable object is performed on the first processing unit and the second processing unit.

公开(公告)号：US11631198B2

公开(公告)日：2023-04-18

申请号：US17355271

申请日：2021-06-23

Applicant: Intel Corporation

Inventor： Abhishek Appu ,  Altug Koker ,  Joydeep Ray ,  Balaji Vembu ,  Prasoonkumar Surti ,  Kamal Sinha ,  Nadathur Rajagopalan Satish ,  Narayan Srinivasa ,  Feng Chen ,  Dukhwan Kim ,  Farshad Akhbari

IPC: G06T9/00 ,  G06T1/60 ,  G06N3/063 ,  G06N3/04 ,  G06N3/084 ,  G06F12/02 ,  G06T1/20

Abstract: An apparatus to facilitate compute compression is disclosed. The apparatus includes a graphics processing unit including mapping logic to map a first block of integer pixel data to a compression block and compression logic to compress the compression block.

公开(公告)号：US11609856B2

公开(公告)日：2023-03-21

申请号：US17206514

申请日：2021-03-19

Applicant: Intel Corporation

Inventor： Chandrasekaran Sakthivel ,  Prasoonkumar Surti ,  John C. Weast ,  Sara S. Baghsorkhi ,  Justin E. Gottschlich ,  Abhishek R. Appu ,  Nicolas C. Galoppo Von Borries ,  Joydeep Ray ,  Narayan Srinivasa ,  Feng Chen ,  Ben J. Ashbaugh ,  Rajkishore Barik ,  Tsung-Han Lin ,  Kamal Sinha ,  Eriko Nurvitadhi ,  Balaji Vembu ,  Altug Koker

IPC: G06F12/08 ,  G06F12/0837 ,  G06N3/08 ,  G06N20/00 ,  G06T1/20 ,  G06F12/0815 ,  G06N3/063 ,  G06N3/04 ,  G06N3/084 ,  G06N3/088

Abstract: In an example, an apparatus comprises a plurality of processing unit cores, a plurality of cache memory modules associated with the plurality of processing unit cores, and a machine learning model communicatively coupled to the plurality of processing unit cores, wherein the plurality of cache memory modules share cache coherency data with the machine learning model. Other embodiments are also disclosed and claimed.

公开(公告)号：US11592817B2

公开(公告)日：2023-02-28

申请号：US15581124

申请日：2017-04-28

Applicant: Intel Corporation

Inventor： Abhishek R. Appu ,  John C. Weast ,  Sara S. Baghsorkhi ,  Justin E. Gottschlich ,  Prasoonkumar Surti ,  Chandrasekaran Sakthivel ,  Altug Koker ,  Farshad Akhbari ,  Feng Chen ,  Dukhwan Kim ,  Narayan Srinivasa ,  Nadathur Rajagopalan Satish ,  Kamal Sinha ,  Joydeep Ray ,  Balaji Vembu ,  Mike B. Macpherson ,  Linda L. Hurd ,  Sanjeev Jahagirdar ,  Vasanth Ranganathan

IPC: G06N3/063 ,  G06N3/08 ,  G06N3/04 ,  G05D1/00 ,  G06F9/50 ,  G06N3/084

Abstract: A mechanism is described for facilitating storage management for machine learning at autonomous machines. A method of embodiments, as described herein, includes detecting one or more components associated with machine learning, where the one or more components include memory and a processor coupled to the memory, and where the processor includes a graphics processor. The method may further include allocating a storage portion of the memory and a hardware portion of the processor to a machine learning training set, where the storage and hardware portions are precise for implementation and processing of the training set.

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.