公开(公告)号：US11238338B2

公开(公告)日：2022-02-01

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 ,  Raanan Yonatan Yehezkel Rohekar ,  Michael Behar ,  Amital Armon ,  Uzi Sarel

IPC: G06N3/08 ,  G06N20/00 ,  G06N20/10

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.

公开(公告)号：US11100393B2

公开(公告)日：2021-08-24

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

IPC: G06N3/08 ,  G06N20/00 ,  G06N20/10

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.

公开(公告)号：US10762685B2

公开(公告)日：2020-09-01

申请号：US16670749

申请日：2019-10-31

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

IPC: G06N3/02 ,  G06N3/08 ,  G06N3/063 ,  G06T15/00 ,  G06N3/04

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.

公开(公告)号：US20200143579A1

公开(公告)日：2020-05-07

申请号：US16670749

申请日：2019-10-31

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

IPC: G06T15/00 ,  G06N3/02 ,  G06N3/04 ,  G06N3/063 ,  G06N3/08

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.

公开(公告)号：US20180293777A1

公开(公告)日：2018-10-11

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

IPC: G06T15/00 ,  G06N3/04 ,  G06N3/08

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.

公开(公告)号：US09218679B2

公开(公告)日：2015-12-22

申请号：US13647071

申请日：2012-10-08

Applicant: INTEL CORPORATION

Inventor： Jacob Subag ,  Nir Benty

IPC: G06T15/00 ,  G06T11/40 ,  G06T15/10

CPC classification number: G06T11/40 ,  G06T15/10 ,  G06T2210/12

Abstract: Techniques are disclosed for carrying out rasterization of a given graphics workload, wherein portions of the workload associated with relatively high bit count operations are processed via a first process path, and portions of the workload associated with relatively lower bit count operations are processed via a second, relatively faster process path, in accordance with an embodiment. In a more general sense, maximal bit count associated with a given primitive can be identified and compared to a threshold to determine which one of multiple available processing paths can be used.

Abstract translation: 公开了用于执行给定图形工作负载的光栅化的技术，其中与相对较高的比特计数操作相关联的工作负载的部分经由第一处理路径被处理，并且与相对较低的比特计数操作相关联的部分工作量经由第二 ，相对较快的处理路径，根据一个实施例。 在更一般的意义上，可以识别与给定基元相关联的最大位计数，并将其与阈值进行比较，以确定可以使用多个可用处理路径中的哪一个。

公开(公告)号：US12033063B2

公开(公告)日：2024-07-09

申请号：US18174275

申请日：2023-02-24

Applicant: Intel Corporation

Inventor： Eran Ben-Avi ,  Neta Zmora ,  Guy Jacob ,  Lev Faivishevsky ,  Jeremie Dreyfuss ,  Tomer Bar-On ,  Jacob Subag ,  Yaniv Fais ,  Shira Hirsch ,  Orly Weisel ,  Zigi Walter ,  Yarden Oren

IPC: G06N3/06 ,  G06N3/044 ,  G06N3/045 ,  G06N3/063 ,  G06N3/084

CPC classification number: G06N3/063 ,  G06N3/044 ,  G06N3/045 ,  G06N3/084

Abstract: In an example, an apparatus comprises a plurality of execution units comprising and logic, at least partially including hardware logic, to traverse a solution space, score a plurality of solutions to a scheduling deep learning network execution, and select a preferred solution from the plurality of solutions to implement the deep learning network. Other embodiments are also disclosed and claimed.

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

IPC: G06N3/063 ,  G06F9/30 ,  G06N3/044 ,  G06N3/045 ,  G06N3/084

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.

公开(公告)号：US20230281435A1

公开(公告)日：2023-09-07

申请号：US18174275

申请日：2023-02-24

Applicant: Intel Corporation

Inventor： Eran Ben-Avi ,  Neta Zmora ,  Guy Jacob ,  Lev Faivishevsky ,  Jeremie Dreyfuss ,  Tomer Bar-On ,  Jacob Subag ,  Yaniv Fais ,  Shira Hirsch ,  Orly Weisel ,  Zigi Walter ,  Yarden Oren

IPC: G06N3/063 ,  G06N3/084 ,  G06N3/044 ,  G06N3/045

CPC classification number: G06N3/063 ,  G06N3/084 ,  G06N3/044 ,  G06N3/045

Abstract: In an example, an apparatus comprises a plurality of execution units comprising and logic, at least partially including hardware logic, to traverse a solution space, score a plurality of solutions to a scheduling deep learning network execution, and select a preferred solution from the plurality of solutions to implement the deep learning network. Other embodiments are also disclosed and claimed.

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

IPC: G06N3/08 ,  G06N20/00 ,  G06N20/10

CPC classification number: G06N3/08 ,  G06N20/00 ,  G06N20/10

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.