INFORMATION THEORETIC CACHING FOR DYNAMIC PROBLEM GENERATION IN CONSTRAINT SOLVING

Patent №

US 9,720,792

Granted

2017-08-01

Filed 2012

Owner

SYNOPSYS, INC.

Lab

AI components

4

ml · kr · planning · hardware

Assignment

Recorded

Dataset

AIPD

2023_r1 edition

Application

13596776

Computer-implemented techniques are disclosed for verifying circuit designs using dynamic problem generation. A device under test (DUT) is modeled as part of a test bench where the test bench is a random process. A set of constraints is solved to generate stimuli for the DUT. Problem generation is repeated numerous times throughout a verification process with problems and sub-problems being generated and solved. When a problem is solved, the problem structure can be stored in a cache. The storage can be based on entropy of variables used in the problem. The problem storage cache can be searched for previously stored problems which match a current problem. By retrieving a problem structure from cache, the computational burden is reduced during verification. Problems can be multi-phase problems with storage and retrieval of problem structures based on the phase level. Caching can be accomplished using an information theoretic approach.

AI classification

Machine learning0.98
Planning0.97
AI hardware0.96
Knowledge representation0.85
Vision0.04
Natural language0.00
Evolutionary computation0.00
Speech0.00

Ownership

SYNOPSYS, INC.

assignment · 288820622

Assignors

GOSWAMI, DHIRAJ, HUNG, NGAI NGAI WILLIAM

On an employer assignment, the assignors are typically the inventors.

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