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A Data-Centric Directive-Based Framework to Accelerate Out-of-Core Stencil Computation on a GPU
2020
IEICE transactions on information and systems
Graphics processing units (GPUs) are highly efficient architectures for parallel stencil code; however, the small device (i.e., GPU) memory capacity (several tens of GBs) necessitates the use of out-of-core computation to process excess data. Great programming effort is needed to manually implement efficient out-of-core stencil code. To relieve such programming burdens, directive-based frameworks emerged, such as the pipelined accelerator (PACC); however, they usually lack specific
doi:10.1587/transinf.2020pap0014
fatcat:z6dwu7a2g5fj3kahvb4elv5s4q