A framework to transform in-core GPU algorithms to out-of-core algorithms
A framework to transform in-core GPU algorithms to out-of-core algorithms
复制标题
将 GPU 核内算法转换为核外算法的框架
DOI：
10.1145/2856400.2876011
复制
发表时间：
2016
期刊：
影响因子：
--
通讯作者：
T. Harada
中科院分区：
文献类型：
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作者：
T. Harada
将现有应用程序移植到 GPU 需要大量的工程工作。然而，由于当今的 GPU 内存与主机内存相比较小，一些需要访问大型数据集的应用程序需要在 GPU 实现之上实现核外逻辑，这是额外的工程工作 [Garanzha 等人。 2011]。我们提出了一个框架，可以轻松地将核内 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，因此我们在本文档中使用 OpenCL 的术语。
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.