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:
Apr. 18, 2023

Filed:

Apr. 28, 2016
Applicant:

Nvidia Corporation, Santa Clara, CA (US);

Inventors:

Ching Y. Hung, Pleasanton, CA (US);

Jagadeesh Sankaran, Dublin, CA (US);

Ravi P. Singh, Austin, TX (US);

Stanley Tzeng, Santa Clara, CA (US);

Assignee:

NVIDIA CORPORATION, Santa Clara, CA (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06F 9/30 (2018.01); G06F 15/82 (2006.01); G06F 9/32 (2018.01); G06F 9/38 (2018.01); G06F 9/345 (2018.01); G06F 9/34 (2018.01); G06F 12/02 (2006.01); G06F 15/80 (2006.01);
U.S. Cl.
CPC ...
G06F 15/82 (2013.01); G06F 9/3001 (2013.01); G06F 9/3013 (2013.01); G06F 9/30036 (2013.01); G06F 9/30072 (2013.01); G06F 9/325 (2013.01); G06F 9/342 (2013.01); G06F 9/345 (2013.01); G06F 9/383 (2013.01); G06F 12/0207 (2013.01); G06F 15/8061 (2013.01);
Abstract

In one embodiment of the present invention, a programmable vision accelerator enables applications to collapse multi-dimensional loops into one dimensional loops. In general, configurable components included in the programmable vision accelerator work together to facilitate such loop collapsing. The configurable elements include multi-dimensional address generators, vector units, and load/store units. Each multi-dimensional address generator generates a different address pattern. Each address pattern represents an overall addressing sequence associated with an object accessed within the collapsed loop. The vector units and the load store units provide execution functionality typically associated with multi-dimensional loops based on the address pattern. Advantageously, collapsing multi-dimensional loops in a flexible manner dramatically reduces the overhead associated with implementing a wide range of computer vision algorithms. Consequently, the overall performance of many computer vision applications may be optimized.


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