一个将内核GPU算法转换为外核算法的框架

T. Harada
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引用次数: 5

摘要

将现有的应用程序移植到GPU上需要大量的工程工作。然而,由于今天的GPU内存与主机内存相比更小,一些需要访问大型数据集的应用程序需要在GPU实现之上实现外核逻辑,这是额外的工程工作[Garanzha等人,2011]。我们提出了一个框架,可以很容易地将核内GPU实现转换为核外GPU实现。在这项工作中,我们假设核外内存访问是只读的。所提出的方法是使用OpenCL实现的,因此我们在本文中使用OpenCL术语。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A framework to transform in-core GPU algorithms to out-of-core algorithms
Porting an existing application to the GPU requires a lot of engineering effort. However, as the GPU memory of today is smaller compared to the host memory, some application which requires to access to a large data set needs to implement an out-of-core logic on top of the GPU implementation which is additional engineering work [Garanzha et al. 2011]. We present a framework to make it easy to transform an in-core GPU implementation to an out-of-core GPU implementation. In this work, we assume that the out-of-core memory access is read only. The proposed method is implemented using OpenCL thus we use the terminology of OpenCL in this document.
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