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公开(公告)号:US20240160910A1
公开(公告)日:2024-05-16
申请号:US18527734
申请日:2023-12-04
Applicant: Intel Corporation
Inventor: Uzi Sarel , Ehud Cohen , Tomer Schwartz , Amitai Armon , Yahav Shadmiy , Amit Bleiweiss , Gal Leibovich , Jeremie Dreyfuss , Lev Faivishevsky , Tomer Bar-On , Yaniv Fais , Jacob Subag
CPC classification number: G06N3/063 , G06F9/30014 , G06F9/30025 , G06F9/30043 , G06N3/044 , G06N3/045 , G06N3/084
Abstract: In an example, an apparatus comprises a plurality of execution units comprising at least a first type of execution unit and a second type of execution unit and logic, at least partially including hardware logic, to expose embedded cast operations in at least one of a load instruction or a store instruction; determine a target precision level for the cast operations; and load the cast operations at the target precision level. Other embodiments are also disclosed and claimed.
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公开(公告)号:US11704564B2
公开(公告)日:2023-07-18
申请号:US17404153
申请日:2021-08-17
Applicant: Intel Corporation
Inventor: Lev Faivishevsky , Tomer Bar-On , Yaniv Fais , Jacob Subag , Jeremie Dreyfuss , Amit Bleiweiss , Tomer Schwartz , Raanan Yonatan Yehezkel Rohekar , Michael Behar , Amitai Armon , Uzi Sarel
Abstract: In an example, an apparatus comprises a plurality of execution units comprising and logic, at least partially including hardware logic, to receive a plurality of data inputs for training a neural network, wherein the data inputs comprise training data and weights inputs; represent the data inputs in a first form; and represent the weight inputs in a second form. Other embodiments are also disclosed and claimed.
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公开(公告)号:US11620766B2
公开(公告)日:2023-04-04
申请号:US17344639
申请日:2021-06-10
Applicant: INTEL CORPORATION
Inventor: Tomer Bar-On , Jacob Subag , Yaniv Fais , Jeremie Dreyfuss , Gal Novik , Gal Leibovich , Tomer Schwartz , Ehud Cohen , Lev Faivishevsky , Uzi Sarel , Amitai Armon , Yahav Shadmiy
Abstract: In an example, an apparatus comprises logic, at least partially including hardware logic, to implement a lossy compression algorithm which utilizes a data transform and quantization process to compress data in a convolutional neural network (CNN) layer.
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公开(公告)号:US20220067496A1
公开(公告)日:2022-03-03
申请号:US17398302
申请日:2021-08-10
Applicant: Intel Corporation
Inventor: Uzi Sarel , Ehud Cohen , Tomer Schwartz , Amitai Armon , Yahav Shadmiy , Amit Bleiweiss , Gal Leibovich , Jeremie Dreyfuss , Lev Faivishevsky , Tomer Bar-On , Yaniv Fais , Jacob Subag
Abstract: In an example, an apparatus comprises a plurality of execution units comprising at least a first type of execution unit and a second type of execution unit and logic, at least partially including hardware logic, to expose embedded cast operations in at least one of a load instruction or a store instruction; determine a target precision level for the cast operations; and load the cast operations at the target precision level. Other embodiments are also disclosed and claimed.
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35.
公开(公告)号:US11250610B2
公开(公告)日:2022-02-15
申请号:US17006253
申请日:2020-08-28
Applicant: Intel Corporation
Inventor: Uzi Sarel , Ehud Cohen , Tomer Schwartz , Amitai Armon , Yahav Shadmiy , Itamar Ben-Ari , Amit Bleiweiss , Lev Faivishevsky , Tomer Bar-On , Yaniv Fais , Jacob Subag , Michael Behar , Guy Jacob , Gal Leibovich , Jeremie Dreyfuss
Abstract: In an example, an apparatus comprises a plurality of execution units; and logic, at least partially including hardware logic, to determine a sub-graph of a network that can be executed in a frequency domain and apply computations in the sub-graph in the frequency domain. Other embodiments are also disclosed and claimed.
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公开(公告)号:US11132601B2
公开(公告)日:2021-09-28
申请号:US15494887
申请日:2017-04-24
Applicant: Intel Corporation
Inventor: Lev Faivishevsky , Tomer Bar-On , Yaniv Fais , Jacob Subag , Jeremie Dreyfuss , Amit Bleiweiss , Tomer Schwartz
Abstract: In an example, an apparatus comprises a plurality of execution units comprising and logic, at least partially including hardware logic, to receive a plurality of data inputs for training a neural network, wherein the data inputs comprise training data and weights inputs; represent the data inputs in a first form; and represent the weight inputs in a second form. Other embodiments are also disclosed and claimed.
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37.
公开(公告)号:US10467795B2
公开(公告)日:2019-11-05
申请号:US15482724
申请日:2017-04-08
Applicant: Intel Corporation
Inventor: Uzi Sarel , Ehud Cohen , Tomer Schwartz , Amitai Armon , Yahav Shadmiy , Itamar Ben-Ari , Amit Bleiweiss , Lev Faivishevsky , Tomer Bar-On , Yaniv Fais , Jacob Subag , Michael Behar , Guy Jacob , Gal Leibovich , Jeremie Dreyfuss
Abstract: In an example, an apparatus comprises a plurality of execution units; and logic, at least partially including hardware logic, to determine a sub-graph of a network that can be executed in a frequency domain and apply computations in the sub-graph in the frequency domain. Other embodiments are also disclosed and claimed.
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公开(公告)号:US20180307987A1
公开(公告)日:2018-10-25
申请号:US15494861
申请日:2017-04-24
Applicant: Intel Corporation
Inventor: Amit Bleiweiss , Itamar Ben-Ari , Michael Behar , Guy Jacob , Gal Leibovich , Jacob Subag , Lev Faivishevsky , Yaniv Fais , Tomer Schwartz
CPC classification number: G06N3/082 , G06F8/52 , G06F9/44552 , G06N3/04 , G06N3/0445 , G06N3/0454 , G06N3/084 , G06N3/105 , G06N5/04
Abstract: In an example, an apparatus comprises at least one execution platform; and logic, at least partially including hardware logic, to receive a trained neural network model in a model optimizer and convert the trained neural network model to an optimized model comprising parameters that are fit to the at least one execution platform. Other embodiments are also disclosed and claimed.
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公开(公告)号:US20180293758A1
公开(公告)日:2018-10-11
申请号:US15482725
申请日:2017-04-08
Applicant: Intel Corporation
Inventor: Tomer Bar-On , Jacob Subag , Yaniv Fais , Jeremie Dreyfuss , Gal Novik , Gal Leibovich , Tomer Schwartz , Ehud Cohen , Lev Faivishevsky , Uzi Sarel , Amitai Armon , Yahav Shadmiy
IPC: G06T9/00
Abstract: In an example, an apparatus comprises logic, at least partially including hardware logic, to implement a lossy compression algorithm which utilizes a data transform and quantization process to compress data in a convolutional neural network (CNN) layer. Other embodiments are also disclosed and claimed.
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