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:
May. 02, 2023

Filed:

Jun. 26, 2020
Applicant:

Intel Corporation, Santa Clara, CA (US);

Inventors:

Mariano Tepper, Portland, OR (US);

Bryn Keller, Vancouver, WA (US);

Mihai Capota, Portland, OR (US);

Vy Vo, Portland, OR (US);

Nesreen Ahmed, Santa Clara, CA (US);

Theodore Willke, Portland, OR (US);

Assignee:

Intel Corporation, Santa Clara, CA (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06F 8/75 (2018.01); G06N 3/08 (2006.01); G06N 3/04 (2006.01);
U.S. Cl.
CPC ...
G06F 8/75 (2013.01); G06N 3/0445 (2013.01); G06N 3/08 (2013.01);
Abstract

Systems, apparatuses and methods may provide for technology that generates a dependence graph based on a plurality of intermediate representation (IR) code instructions associated with a compiled program code, generates a set of graph embedding vectors based on the plurality of IR code instructions, and determines, via a neural network, one of an analysis of the compiled program code or an enhancement of the program code based on the dependence graph and the set of graph embedding vectors. The technology may provide a graph attention neural network that includes a recurrent block and at least one task-specific neural network layer, the recurrent block including a graph attention layer and a transition function. The technology may also apply dynamic per-position recurrence-halting to determine a number of recurring steps for each position in the recurrent block based on adaptive computation time.


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