GATSim: Abstract Timing Simulation of GPUs

Kishore Punniyamurthya, Behzad Boroujerdianb and Andreas Gerstlauerc
The University of Texas at Austin.


General-Purpose Graphic Processing Units (GPUs) have become an integral part of heterogeneous system architectures. Ever increasing complexities have made rapid, early performance evaluation of GPU-based architectures and applications a primary design concern. Traditional cycle-accurate GPU simulators are too slow, while existing analytical or source-level estimation approaches are often inaccurate. This paper proposes a novel abstract GPU performance simulation approach that is based on flexible separation of functional and timing models, combining a fast functional execution either on existing simulators or native GPU hardware with a light, fast and accurate abstract timing model. Micro-architecture timing of individual GPU cores is abstracted through static, one-time pre-characterization of code, and only the dynamic scheduling effects are simulated. Using a native GPU for functional execution and excluding pre-characterization, our GPU simulation achieves a throughput of more than 80 MIPS. This is on average 400x faster with 4% error compared to a cycle-accurate GPU simulator for standard GPU benchmarks. Moreover, our simple timing model provides flexibility to target different GPU configurations with little or no extra effort.

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