Hybrid CUDA, OpenMP, and MPI parallel programming on multicore GPU clusters
صفحه : 4 زبان :  سال : 2010 میلادی حجم : 485.1 کیلوبایت رسته : 
Nowadays, NVIDIA’s CUDA is a general purpose scalable parallel programming model for writing highly
parallel applications. It provides several key abstractions – a hierarchy of thread blocks, shared memory,
and barrier synchronization. This model has proven quite successful at programming multithreaded many
core GPUs and scales transparently to hundreds of cores: scientists throughout industry and academia are
already using CUDA to achieve dramatic speedups on production and research codes. In this paper, we
propose a parallel programming approach using hybrid CUDA OpenMP, and MPI programming, which
partition loop iterations according to the number of C1060 GPU nodes in a GPU cluster which consists
of one C1060 and one S1070. Loop iterations assigned to one MPI process are processed in parallel by
CUDA run by the processor cores in the same computational node.
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