Parallel For Loops on Heterogeneous Resources
作者： Frederick Edward Weber
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摘要: In recent years, Graphics Processing Units (GPUs) have piqued the interest of researchers in scientific computing. Their immense floating point throughput and massive parallelism make them ideal for not just graphical applications, but many general algorithms as well. Load balancing applications taking advantage all computational resources a machine is difficult challenge, especially when are heterogeneous. This dissertation presents clUtil library, which vastly simplifies developing OpenCL heterogeneous systems. The core focus this lies clUtil’s ParallelFor construct our novel PINA scheduler can efficiently load balance work onto multiple GPUs CPUs simultaneously.
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