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Bridging OpenCL and CUDA: a comparative analysis and translation

机译:桥接OpenCL和CUDA:比较分析和翻译

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摘要

Heterogeneous systems are widening their user-base, and heterogeneous computing is becoming popular in supercomputing. Among others, OpenCL and CUDA are the most popular programming models for heterogeneous systems. Although OpenCL inherited many features from CUDA and they have almost the same platform model, they are not compatible with each other. In this paper, we present similarities and differences between them and propose an automatic translation framework for both OpenCL to CUDA and CUDA to OpenCL. We describe features that make it difficult to translate from one to the other and provide our solution. We show that our translator achieves comparable performance between the original and target applications in both directions. Since each programming model separately has a wide user-base and large code-base, our translation framework is useful to extend the code-base for each programming model and unifies the efforts to develop applications for heterogeneous systems.
机译:异构系统正在扩大其用户基础,并且异构计算在超级计算中正变得越来越流行。其中,OpenCL和CUDA是异构系统最流行的编程模型。尽管OpenCL从CUDA继承了许多功能,并且它们具有几乎相同的平台模型,但是它们彼此不兼容。在本文中,我们将介绍它们之间的异同,并为从OpenCL到CUDA和从CUDA到OpenCL的自动翻译框架提出建议。我们描述了难以相互转换的功能,并提供了解决方案。我们证明了我们的翻译器在两个方向上都可以在原始应用程序和目标应用程序之间实现可比的性能。由于每种编程模型分别具有广泛的用户群和大型代码库,因此我们的翻译框架可用于扩展每种编程模型的代码库,并统一开发异构系统应用程序的工作。

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