The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Oct. 24, 2023

Filed:

Nov. 04, 2021
Applicant:

Neuralmagic Inc., Somerville, MA (US);

Inventors:

Alexander Matveev, Cambridge, MA (US);

Dan Alistarh, Meyrin, CH;

Justin Kopinsky, Cambridge, MA (US);

Rati Gelashvili, Cambridge, MA (US);

Mark Kurtz, Medford, MA (US);

Nir Shavit, Cambridge, MA (US);

Assignee:

Neuralmagic, Inc., Somerville, MA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06N 3/08 (2023.01); G06F 9/30 (2018.01); G06F 16/24 (2019.01); G06N 3/082 (2023.01); G06N 3/063 (2023.01); G06F 17/16 (2006.01); G06F 9/50 (2006.01); G06N 20/10 (2019.01); G06N 3/084 (2023.01);
U.S. Cl.
CPC ...
G06N 3/082 (2013.01); G06F 9/5027 (2013.01); G06F 17/16 (2013.01); G06N 3/063 (2013.01); G06N 20/10 (2019.01); G06N 3/084 (2013.01);
Abstract

A system and method of accelerating execution of a NN model, by at least one processor may include: receiving a first matrix A, representing elements of a kernel K of the NN model and a second matrix B, representing elements of an input I to kernel K; producing from matrix A, a group-sparse matrix A', comprising G tensors of elements. The number of elements in each tensor is defined by, or equal to a number of entries in each index of an input tensor register used for a specific Single Instruction Multiple Data (SIMD) tensor operation, and all elements of A′ outside said G tensors are null. The system and method may further include executing kernel K on input I, by performing at least one computation of the SIMD tensor operation, having as operands elements of a tensor of the G tensors and corresponding elements of the B matrix.


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