Publication | Open Access
MGPUSim
93
Citations
40
References
2019
Year
Unknown Venue
Cluster ComputingGpu ArchitectureEngineeringGpu BenchmarkingRaw Computational PowerRuntime LibrariesComputer ArchitectureComputer EngineeringSystems EngineeringGraphics Processing UnitsParallel ProgrammingComputer ScienceModeling And SimulationParallel ComputingGpu ClusterGpu ComputingGpu Virtualization
The rapidly growing popularity and scale of data-parallel workloads demand a corresponding increase in raw computational power of Graphics Processing Units (GPUs). As single-GPU platforms struggle to satisfy these performance demands, multi-GPU platforms have started to dominate the high-performance computing world. The advent of such systems raises a number of design challenges, including the GPU microarchitecture, multi-GPU interconnect fabric, runtime libraries, and associated programming models. The research community currently lacks a publicly available and comprehensive multi-GPU simulation framework to evaluate next-generation multi-GPU system designs.
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