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Performance Evaluation of OpenMP and CUDA on Multicore Systems

机译:OpenMP和CUDA在多核系统上的性能评估

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Nowadays, not only CPU but also GPU goes along the trend of multi-core processors. Parallel processing presents not only an opportunity but also a challenge at the same time. To explicitly parallelize the software by programmers or compilers is the key for enhancing the performance on multi-core chip. In this paper, we first introduce some of the automatic parallel tools based OpenMP, which could save the time to rewrite codes for parallel processing on multicore system. Then we focus on ROSE and explore it in depth. And we also implement an interface to reduce its complexity of use and use some automatic parallelization for CUDA.
机译:如今,不仅CPU,而且GPU都遵循多核处理器的趋势。并行处理不仅带来机会,同时也带来挑战。由程序员或编译器显式并行化软件是增强多核芯片性能的关键。在本文中,我们首先介绍一些基于OpenMP的自动并行工具,这些工具可以节省时间来重写多核系统上并行处理的代码。然后,我们专注于ROSE并进行深入研究。并且我们还实现了一个接口,以减少其使用复杂性,并对CUDA使用一些自动并行化。

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