Publication | Closed Access
GCoM
18
Citations
28
References
2022
Year
Unknown Venue
Core MicroarchitecturesGpu ArchitectureEngineeringAnalytical ModelsGpu BenchmarkingNumerical SimulationComputer ArchitectureComputer EngineeringSystems EngineeringSimulationParallel ProgrammingComputer ScienceModeling And SimulationParallel ComputingGpu ClusterPerformance PredictionModern GpusGpu Computing
Analytical models can greatly help computer architects perform orders of magnitude faster early-stage design space exploration than using cycle-level simulators. To facilitate rapid design space exploration for graphics processing units (GPUs), prior studies have proposed GPU analytical models which capture first-order stall events causing performance degradation; however, the existing analytical models cannot accurately model modern GPUs due to their outdated and highly abstract GPU core microarchitecture assumptions. Therefore, to accurately evaluate the performance of modern GPUs, we need a new GPU analytical model which accurately captures the stall events incurred by the significant changes in the core microarchitectures of modern GPUs.
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