This paper introduces Go-Fast, a novel approach that accelerates the simulation and optimization of LUT-based FPGA circuits using GPUs. Unlike previous GPU-based simulators that target general digital circuits with event-driven approaches, Go-Fast employs batch simulation techniques specifically optimized for approximate computing scenarios. The system utilizes both data parallelism to execute testbenches across numerous threads and structural parallelism for simultaneous simulation and logic pruning. Go-Fast fully exploits GPU architectural features by maximizing register usage, minimizing memory access, and allocating more work per thread. This domain-specific approach generates efficient source-to-source CUDA code that achieves significant performance improvements: five orders of magnitude over the Verilator simulator and two to three orders over optimized multi-core implementations.
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关键词
FPGA simulation,GPU acceleration,Batch simulation,Approximate computing,Source-To-source CUDA