Solution Distribution
ConceptThe distribution of generated solutions in constrained random simulation, which critically impacts the efficiency of hardware verification flows alongside the performance of the constraint solver.
First seen 7/17/2026
Last seen 7/17/2026
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Overview
In constrained random simulation, the main workhorse in modern hardware verification flows, input stimuli are randomly generated to satisfy a set of declaratively specified input constraints. These stimuli are then applied to validate given design properties by simulation.
The efficiency of the overall verification flow depends critically on two factors:
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1 connectionsThe hybrid constraint solver addresses the quality of solution distribution.
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[1] The efficiency of the overall constrained random simulation flow depends critically on the performance of the constraint solver and the distribution of the generated solutions. Stimulus generation for constrained random simulation
[2] A new hybrid solver based on Markov-chain Monte Carlo methods is proposed to provide good performance and distribution for mixed Boolean/integer variable domains. Stimulus generation for constrained random simulation