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In this paper, we introduce a new Java-based parallel GPGPU simulator, GpuTejas. GpuTejas is a fast trace driven simulator, which uses relaxed synchronization, and non-blocking data structures to derive its speedups. Secondly, it introduces a novel scheduling and partitioning scheme for parallelizing a GPU simulator. We evaluate the performance of our simulator with a set of Rodinia benchmarks. We demonstrate a mean speedup of 17.33x with 64 threads over sequential execution, and a speedup of 429X over the widely used simulator GPGPU-Sim. We validated our timing and simulation model by comparing our results with a native system (NVIDIA Tesla M2070). As compared to the sequential version of GpuTejas, the parallel version has an error limited to <;7.67% for our suite of benchmarks, which is similar to the numbers reported by competing parallel simulators.
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Malhotra et al. (2014) studied this question.