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Gate-Level Simulation with GPU Computing

Debapriya Chatterjee, Andrew Deorio, Valeria Bertacco
University of Michigan
ACM Transactions on Design Automation of Electronic Systems (TODAES), Volume 16 Issue 3, June 2011

@article{chatterjee2011gate,

   title={Gate-Level Simulation with GPU Computing},

   author={Chatterjee, D. and Deorio, A. and Bertacco, V.},

   journal={ACM Transactions on Design Automation of Electronic Systems (TODAES)},

   volume={16},

   number={3},

   pages={30},

   year={2011},

   publisher={ACM}

}

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Functional verification of modern digital designs is a crucial, time-consuming task impacting not only the correctness of the final product, but also its time to market. At the heart of most of today’s verification efforts is logic simulation, used heavily to verify the functional correctness of a design for a broad range of abstraction levels. In mainstream industry verification methodologies, typical setups coordinate the validation effort of a complex digital system by distributing logic simulation tasks among vast server farms for months at a time. Yet, the performance of logic simulation is not sufficient to satisfy the demand, leading to incomplete validation processes, escaped functional bugs, and continuous pressure on the EDA industry to develop faster simulation solutions. In this work we propose GCS, a solution to boost the performance of logic simulation, gate-level simulation in particular, by more than a factor of 10 using recent hardware advances in Graphic Processing Unit (GPU) technology. Noting the vast available parallelism in the hardware of modern GPUs and the inherently parallel structures of gate-level netlists, we propose novel algorithms for the efficient mapping of complex designs to parallel hardware. Our novel simulation architecture maximizes the utilization of concurrent hardware resources while minimizing expensive communication overhead. The experimental results show that our GPU-based simulator is capable of handling the validation of industrial-size designs while delivering more than an order-of-magnitude performance improvements on average, over the fastest multithreaded simulators commercially available.
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