constrained random


August 17, 2020

Cadence uses machine learning to trim constrained-random runtimes

Cadence has developed a stimulus optimizer based on neural networks to try to improve the runtime of constrained-random verification runs.
Article  |  Topics: Blog - EDA  |  Tags: , , ,   |  Organizations:
February 11, 2015

Accellera sets up group for one-stop verification stimulus

Accellera has set up a working group to develop a language-independent way of capturing and managing test stimuli that can be used across a wide range of verification environments.
Article  |  Topics: Blog - EDA, IP  |  Tags: , ,   |  Organizations:
May 21, 2014

Verification perspectives 2: formal for the masses and graph-based techniques

The second part of our interview with Mark Olen and Jim Kenney, looks at how formal and graph-based techniques move the market beyond simulation.

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