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公开(公告)号:US20210142448A1
公开(公告)日:2021-05-13
申请号:US17090170
申请日:2020-11-05
Applicant: Intel Corporation
Inventor: Anbang Yao , Ming Lu , Yikai Wang , Xiaoming Chen , Junjie Huang , Tao Lv , Yuanke Luo , Yi Yang , Feng Chen , Zhiming Wang , Zhiqiao Zheng , Shandong Wang
Abstract: Embodiments are generally directed to an adaptive deformable kernel prediction network for image de-noising. An embodiment of a method for de-noising an image by a convolutional neural network implemented on a compute engine, the image including a plurality of pixels, the method comprising: for each of the plurality of pixels of the image, generating a convolutional kernel having a plurality of kernel values for the pixel; generating a plurality of offsets for the pixel respectively corresponding to the plurality of kernel values, each of the plurality of offsets to indicate a deviation from a pixel position of the pixel; determining a plurality of deviated pixel positions based on the pixel position of the pixel and the plurality of offsets; and filtering the pixel with the convolutional kernel and pixel values of the plurality of deviated pixel positions to obtain a de-noised pixel.
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102.
公开(公告)号:US20210035255A1
公开(公告)日:2021-02-04
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
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.
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公开(公告)号:US10902547B2
公开(公告)日:2021-01-26
申请号:US15819093
申请日:2017-11-21
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
Abstract: An apparatus to facilitate compute optimization is disclosed. The apparatus includes a plurality of processing units each comprising a plurality of execution units (EUs), wherein the plurality of EUs comprise a first EU type and a second EU type.
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公开(公告)号:US20200226096A1
公开(公告)日:2020-07-16
申请号:US16744407
申请日:2020-01-16
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
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.
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公开(公告)号:US20200013194A1
公开(公告)日:2020-01-09
申请号:US16511757
申请日:2019-07-15
Applicant: Intel Corporation
Inventor: Abhishek R. Appu , Altug Koker , Joydeep Ray , Balaji Vembu , Prasoonkumar Surti , Kamal Sinha , Nadathur Rajagoplan Satish , Narayan Srinivasa , Feng Chen , Dukhwan Kim , Farshad Akhbari
IPC: G06T9/00
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.
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公开(公告)号:US20190304054A1
公开(公告)日:2019-10-03
申请号:US16446398
申请日:2019-06-19
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 , G06N3/08 , G06N3/04 , G06T15/00 , G09G5/36 , G06F9/30 , G06F3/14 , G06N3/063 , G06F9/38
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 16-bit and/or 32 bit floating-point elements.
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公开(公告)号:US10410115B2
公开(公告)日:2019-09-10
申请号:US15581133
申请日:2017-04-28
Applicant: Intel Corporation
Inventor: Brian T. Lewis , Feng Chen , Jeffrey R. Jackson , Justin E. Gottschlich , Rajkishore Barik , Xiaoming Chen , Prasoonkumar Surti , Mike B. Macpherson , Murali Sundaresan
Abstract: A mechanism is described for facilitating smart collection of data and smart management of 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 combining a first computation directed to be performed locally at a local computing device with a second computation directed to be performed remotely at a remote computing device in communication with the local computing device over the one or more networks, where the first computation consumes low power, wherein the second computation consumes high power.
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公开(公告)号:US10346166B2
公开(公告)日:2019-07-09
申请号:US15581080
申请日:2017-04-28
Applicant: Intel Corporation
Inventor: Feng Chen , Narayan Srinivasa , Abhishek R. Appu , Altug Koker , Kamal Sinha , Balaji Vembu , Joydeep Ray , Nicolas C. Galoppo Von Borries , Prasoonkumar Surti , Ben J. Ashbaugh , Sanjeev Jahagirdar , Vasanth Ranganathan
IPC: G06T1/00 , G06F9/30 , G06F9/38 , G06F12/0862 , G06F12/0875 , G06F9/50
Abstract: A mechanism is described for facilitating intelligent dispatching and vectorizing at autonomous machines. A method of embodiments, as described herein, includes detecting a plurality of threads corresponding to a plurality of workloads associated with tasks relating to a graphics processor. The method may further include determining a first set of threads of the plurality of threads that are similar to each other or have adjacent surfaces, and physically clustering the first set of threads close together using a first set of adjacent compute blocks.
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公开(公告)号:US20180314521A1
公开(公告)日:2018-11-01
申请号:US15581080
申请日:2017-04-28
Applicant: Intel Corporation
Inventor: Feng Chen , Narayan Srinivasa , Abhishek R. Appu , Altug Koker , Kamal Sinha , Balaji Vembu , Joydeep Ray , Nicolas C. Galoppo Von Borries , Prasoonkumar Surti , Ben J. Ashbaugh , Sanjeev Jahagirdar , Vasanth Ranganathan
IPC: G06F9/30 , G06F9/38 , G06F12/0862 , G06F12/0875
CPC classification number: G06F9/3009 , G06F9/30036 , G06F9/30145 , G06F9/3836 , G06F9/3867 , G06F9/3887 , G06F9/5033 , G06F9/5066 , G06F12/0862 , G06F12/0875 , G06F2212/452 , G06F2212/602
Abstract: A mechanism is described for facilitating intelligent dispatching and vectorizing at autonomous machines. A method of embodiments, as described herein, includes detecting a plurality of threads corresponding to a plurality of workloads associated with tasks relating to a graphics processor. The method may further include determining a first set of threads of the plurality of threads that are similar to each other or have adjacent surfaces, and physically clustering the first set of threads close together using a first set of adjacent compute blocks.
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公开(公告)号:US20180285734A1
公开(公告)日:2018-10-04
申请号:US15477056
申请日:2017-04-01
Applicant: Intel Corporation
Inventor: Feng Chen , Anbang Yao
Abstract: An apparatus to facilitate calibration of a neural network (NN) is disclosed. The apparatus includes scoring logic to simultaneously test accuracy of a plurality of versions of a NN model based on received input data and select a first of the plurality of model versions having a highest accuracy.
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