PACC : An Extension of OpenACC for Pipelined Processing of Large Data on a GPU
PACC : An Extension of OpenACC for Pipelined Processing of Large Data on a GPU
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PACC：OpenACC 的扩展，用于在 GPU 上对大数据进行流水线处理
DOI：
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发表时间：
2014
期刊：
影响因子：
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通讯作者：
K. Hagihara
中科院分区：
文献类型：
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作者：
Tomochika Kato;Fumihiko Ino;K. Hagihara
我们提出了一套指令，命名为流水线加速器（PACC），并实现了在图形处理单元（GPU）上加速大规模计算。PACC扩展了OpenACC，实现了不能完全存储在设备内存中的大数据的分割。给定一个带有PACC指令的程序，我们的PACC转换器将该程序重写为OpenACC程序，以便将数据分成多个块以加速执行。此外，生成的程序在管道中处理块，以便CPU和GPU之间的数据传输可以与GPU上的计算重叠。本文还给出了一些初步结果，以显示PACC在程序执行时间和可成功处理的最大数据大小方面的影响。
We present a suite of directives, named pipelined accelerator (PACC), and its implementation for accelerating large-scale computation on a graphics processing unit (GPU). PACC extends OpenACC to achieve division of large data that cannot be entirely stored in device memory. Given a program with PACC directives, our PACC translator rewrites the program into an OpenACC program such that data is divided into multiple chunks for accelerated execution. Furthermore, the generated program processes chunks in a pipeline so that data transfer between the CPU and GPU can overlap with computation on the GPU. Some preliminary results are also presented to show the impact of PACC in terms of the program execution time and the maximum data size that can be processed successfully.