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Parallel simulation of mixed-abstraction SystemC models on GPUs and multicore CPUs

Rohit Sinha, Aayush Prakash, Hiren D. Patel
Electrical and Computer Engineering, University of Waterloo, Waterloo, Canada
17th Asia and South Pacific Design Automation Conference (ASP-DAC), 2012

@inproceedings{sinha2012parallel,

   title={Parallel simulation of mixed-abstraction SystemC models on GPUs and multicore CPUs},

   author={Sinha, R. and Prakash, A. and Patel, H.D.},

   booktitle={Design Automation Conference (ASP-DAC), 2012 17th Asia and South Pacific},

   pages={455–460},

   year={2012},

   organization={IEEE}

}

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This work presents a methodology that parallelizes the simulation of mixed-abstraction level SystemC models across multicore CPUs, and graphics processing units (GPUs) for improved simulation performance. Given a SystemC model, we partition it into processes suitable for GPU execution and CPU execution. We convert the processes identified for GPU execution into GPU kernels with additional SystemC wrapper processes that invoke these kernels. The wrappers enable seamless communication of events in all directions between the GPUs and CPUs. We alter the OSCI SystemC simulation kernel to allow parallel execution of processes. Hence, we co-simulate in parallel, the SystemC processes on multiple CPUs, and the GPU kernels on the GPUs; exploit both the CPUs, and GPUs for faster simulation. We experiment with synthetic benchmarks and a set-top box case study.
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