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Toward the Minimal Floating Operation Count Cholesky Decomposition of Electron Repulsion Integrals

机译:朝向最小的浮动操作,数量尖锐分解电子排斥积分

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As quantum chemistry calculations deal with molecular systems of increasing size, the memory requirement to store electron-repulsion integrals (ERIs) greatly outpaces the physical memory available in computing hardware. The Cholesky decomposition of ERIs provides a convenient yet accurate technique to reduce the storage requirement of integrals. Recent developments of a two-step algorithm have drastically reduced the memory operation (MOP) count, leaving the floating operation (FLOP) count as the last frontier of cost reduction in the Cholesky ERI algorithm. In this report, we introduce a dynamic integral tracking, reusing, and compression/elimination protocol embedded in the two-step Cholesky ERI method. Benchmark studies suggest that this technique becomes particularly advantageous when the basis set consists of many computationally expensive high-angular-momentum basis functions. With this dynamic-ERI improvement, the Cholesky ERI approach proves to be a highly efficient algorithm with minimal FLOP and MOP count.
机译:随着量子化学计算处理越来越大的分子系统,存储电子排斥积分(ERI)的内存需求大大超过了计算硬件中可用的物理内存。ERIs的Cholesky分解为减少积分的存储需求提供了一种方便而精确的技术。两步算法的最新发展极大地减少了内存操作(MOP)计数,使浮点操作(FLOP)计数成为Cholesky ERI算法中成本降低的最后一个前沿。在本报告中,我们介绍了嵌入在两步Cholesky ERI方法中的动态积分跟踪、重用和压缩/消除协议。基准研究表明,当基集由许多计算代价高昂的高角动量基函数组成时,这种技术变得特别有利。通过这种动态ERI改进,Cholesky ERI方法被证明是一种具有最小失败次数和MOP计数的高效算法。

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