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：US11599777B2

公开(公告)日：2023-03-07

申请号：US15499900

申请日：2017-04-28

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: G06N3/00 ,  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：US20220197703A1

公开(公告)日：2022-06-23

申请号：US17561500

申请日：2021-12-23

Applicant: Intel Corporation

Inventor： Michael Behar ,  Moshe Maor ,  Ronen Gabbai ,  Roni Rosner ,  Zigi Walter ,  Oren Agam

IPC: G06F9/50 ,  G06F3/06

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed that enable out-of-order pipelined execution of static mapping of a workload to one or more computational building blocks of an accelerator. An example apparatus includes an interface to load a first number of credits into memory; a comparator to compare the first number of credits to a threshold number of credits associated with memory availability in a buffer; and a dispatcher to, when the first number of credits meets the threshold number of credits, select a workload node of the workload to be executed at a first one of the one or more computational building blocks.

公开(公告)号：US11347551B2

公开(公告)日：2022-05-31

申请号：US16539496

申请日：2019-08-13

Applicant: Intel Corporation

Inventor： Zigi Walter ,  Anat Heilper

IPC: G06F9/50 ,  G06F12/02

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed to manage memory allocation. An example apparatus includes a memory detector to scan a platform for available memory. The example apparatus also includes a memory size checker to retrieve a virtual memory layout associated with the available memory devices associated with the platform and to determine whether virtual address boundaries of respective ones of a available memory device generate a virtual address gap therebetween. The example apparatus also includes a address assigner to reassign virtual addresses of at least one of the respective ones of the available memory devices to remove the virtual address gap.

公开(公告)号：US11231963B2

公开(公告)日：2022-01-25

申请号：US16542012

申请日：2019-08-15

Applicant: Intel Corporation

Inventor： Michael Behar ,  Moshe Maor ,  Ronen Gabbai ,  Roni Rosner ,  Zigi Walter ,  Oren Agam

IPC: G06F9/46 ,  G06F9/50 ,  G06F3/06

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed that enable out-of-order pipelined execution of static mapping of a workload to one or more computational building blocks of an accelerator. An example apparatus includes an interface to load a first number of credits into memory; a comparator to compare the first number of credits to a threshold number of credits associated with memory availability in a buffer; and a dispatcher to, when the first number of credits meets the threshold number of credits, select a workload node of the workload to be executed at a first one of the one or more computational building blocks.