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Evaluating application performance and energy consumption on hybrid CPU+GPU architecture

机译:在混合CPU + GPU架构上评估应用程序性能和能耗

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The High Performance Computing (HPC) community aimed for many years to increase performance regardless of energy consumption. Until the end of the decade, a next generation of HPC systems is expected to reach sustained performances of the order of exaflops. This requires many times more performance compared to the fastest supercomputers of today. Achieving this goal is unthinkable with current technology due to strict constraints on supplied power. Therefore, finding ways to improve energy efficiency become a main challenge on state-of-the-art research. The present paper investigates energy efficiency on heterogeneous CPU + GPU architectures using a scientific application from the agroforestry domain as a case-study. Differently from other works, our work evaluates how the workload of the application may affect energy efficiency on hybrid architectures. Results point out that the power supplier constraints depend also on the workload.
机译:高性能计算(HPC)社区多年来一直致力于提高性能,而与能耗无关。到本世纪末,下一代HPC系统有望达到exaflops级别的持续性能。与当今最快的超级计算机相比,这需要许多倍的性能。由于对供电的严格限制,使用现有技术无法实现此目标。因此,寻找提高能源效率的方法成为当前研究的主要挑战。本文以农林业领域的科学应用为案例,研究了异构CPU + GPU架构上的能源效率。与其他工作不同,我们的工作评估应用程序的工作负载如何影响混合架构上的能源效率。结果指出,电源供应商的约束也取决于工作量。

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