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Design and performance characterization of electronic structure calculations on massively parallel supercomputers: a case study of GPAW on the Blue Gene/P architecture

机译:大规模并行超级计算机上电子结构计算的设计和性能表征:基于Blue Gene / P架构的GPAW案例研究

摘要

Density function theory (DFT) is the most widely employed electronic structure method because of its favorable scaling with system size and accuracy for a broad range of molecular and condensed-phase systems. The advent of massively parallel supercomputers has enhanced the scientific community's ability to study larger system sizes. Ground-state DFT calculations on ~103 valence electrons using traditional ON3 algorithms can be routinely performed on present-day supercomputers. The performance characteristics of these massively parallel DFT codes on >104 computer cores are not well understood. The GPAW code was ported an optimized for the Blue Gene/P architecture. We present our algorithmic parallelization strategy and interpret the results for a number of benchmark test cases.
机译:密度泛函理论(DFT)是应用最广泛的电子结构方法,因为它对系统范围和分子和凝聚相系统的精度具有良好的缩放比例。大规模并行超级计算机的出现增强了科学界研究更大系统尺寸的能力。使用传统的ON3算法对〜103个价电子进行基态DFT计算可在当今的超级计算机上常规执行。这些在104多个计算机内核上的大规模并行DFT代码的性能特征尚未得到很好的理解。 GPAW代码已移植为Blue Gene / P体系结构进行了优化。我们介绍了我们的算法并行化策略,并解释了许多基准测试用例的结果。

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