Synopsys, Inc.

Danish Jawed

Parijat Biswas

Rajarshi Mukherjee

Ying Chen

Jiang Chen

Bhaskar Pal

Badri P Gopalan

Pravash Chandra Dash

Esha Dutta

Enzhi Ni

Sharad Gaur

A method for verifying an integrated circuit (IC) design described in a hardware description or hardware verification language (HDHVL) is provided. The method includes identifying connections between random variables and coverage areas of the IC design, as described in HDHVL code, the connections being identified by determining which coverage areas of the IC design will be influenced during simulation by which random variables. The method can further include storing the identified connections in a database, and using, by a processor, connections retrieved from the database to simulate and verify the coverage areas of the IC design.

Connecting random variables to coverage targets using an ensemble of static analysis, dynamic analysis and machine learning and guided constraint solving of the random variables during simulation of an integrated circuit

A data analysis engine is implemented in a testbench to improve coverage convergence during simulation of a device-under-validation (DUV). During a first simulation phase initial stimulus data is generated according to initial random variables based on user-provided constraint parameters. The data analysis engine then uses a time-based technique to match coverage variables sampled from simulation response data with corresponding initial random variables, determines a functional dependency (relationship) between the sampled coverage variables and corresponding initial random variables, then automatically generates revised constraint parameters based on the functional dependency. The revised constraint parameters are then used during a second simulation phase to generate focused random variables used to stimulate the DUV to reach additional coverage variables. In one embodiment, the functional dependency is determined by cross-correlating sampled coverage variables and corresponding initial random variables.

Automated coverage convergence by correlating random variables with coverage variables sampled from simulation result data

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Karnataka, India

Danish Jawed