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:
Jun. 18, 2019

Filed:

Nov. 21, 2017
Applicant:

Intel Ip Corporation, Santa Clara, CA (US);

Inventors:

Gurpreet Singh Kalsi, Bengaluru, IN;

Om Ji Omer, Bengaluru, IN;

Dipan Kumar Mandal, Bangalore, IN;

Santhosh Kumar Rethinagiri, Bengaluru, IN;

Gopi Neela, Bengaluru, IN;

Assignee:

Intel IP Corporation, Santa Clara, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06F 7/527 (2006.01); G06F 12/02 (2006.01); G06F 13/16 (2006.01); G06F 13/40 (2006.01); G06F 13/42 (2006.01); G06F 17/12 (2006.01); G06F 9/30 (2018.01);
U.S. Cl.
CPC ...
G06F 7/527 (2013.01); G06F 9/3001 (2013.01); G06F 12/0215 (2013.01); G06F 13/161 (2013.01); G06F 13/1673 (2013.01); G06F 13/4022 (2013.01); G06F 13/4234 (2013.01); G06F 17/12 (2013.01); G06F 2212/654 (2013.01);
Abstract

Systems and methods for matrix-solve applications include a memory-optimized hardware acceleration (HWA) solution with scalable architecture (i.e. specialized circuitry) for HWA matrix-solve operations. The matrix-solve solutions described herein may include a scalable hardware architecture with parallel processing (e.g., 'within column' processing), which provides the ability to compute several output values in parallel. The HWA matrix-solve solutions described herein may include simultaneous multi-column processing, which provides a lower execution cycle count and a reduced total number of memory accesses. This HWA matrix-solve provides a low latency and energy-efficient matrix-solve solutions, which may be used to reduce energy consumption and improve performance in various matrix-based applications, such as computer vision, SLAM, AR/VR/mixed-reality, machine learning, data analytics, and other matrix-based applications.


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