ComputingComputer EngineeringComputer ScienceParallel AlgorithmsParallel ComputingSchedulingData ParallelismGraphics Processing Unit ArchitectureGraphics Processing Unit ComputingHardware AccelerationParallel ArchitecturesParallel Computing SystemsCompute Unified Device ArchitectureData Parallel ExecutionExecution Time AnalysisGpu Runtime SystemsHardware MappingKernel OptimizationKernel Performance OptimizationSystem Performance Modeling
Executing multiple OpenCL kernels on the same GPU concurrently is a promising method for improving hardware utilisation and system performance. Schemes of scheduling impact the resulting performance significantly by selecting different kernels to run together on the same GPU. Existing approaches use either execution time or relative speedup of kernels as a guide to group and map them to the device. However, these simple methods work on the cost of providing suboptimal performance.
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Claude Berge · Proceedings of the National Academy of Sciences · 1957 · 574 citations · Full text
The case for GPGPU spatial multitasking
Jacob T. Adriaens, Katherine Compton, Nam Sung Kim et al. · 2012 · 214 citations
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Ivan Tanasić, Isaac Gelado, Javier Cabezas et al. · ACM SIGARCH Computer Architecture News · 2014 · 172 citations · Full text