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A Novel Approach to Parallel Coupled Cluster Calculations:  Combining Distributed and Shared Memory Techniques for Modern Cluster Based Systems

机译:一种新颖的并行耦合集群计算方法:for结合分布式和共享内存技术用于现代基于集群的系统

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摘要

A parallel coupled cluster algorithm that combines distributed and shared memory techniques for the CCSD(T) method (singles + doubles with perturbative triples) is described. The implementation of the massively parallel CCSD(T) algorithm uses a hybrid molecular and “direct” atomic integral driven approach. Shared memory is used to minimize redundant replicated storage per compute process. The algorithm is targeted at modern cluster based architectures that are comprised of multiprocessor nodes connected by a dedicated communication network. Parallelism is achieved on two levels:  parallelism within a compute node via shared memory parallel techniques and parallelism between nodes using distributed memory techniques. The new parallel implementation is designed to allow for the routine evaluation of mid- (500−750 basis function) to large-scale (750−1000 basis function) CCSD(T) energies. Sample calculations are performed on five low-lying isomers of water hexamer using the aug-cc-pVTZ basis set.
机译:描述了一种并行耦合的簇算法,该算法结合了CCSD(T)方法的分布式和共享存储技术(单+加双与扰动三加)。大规模并行CCSD(T)算法的实现使用混合分子和“直接”原子积分驱动方法。共享内存用于最大程度地减少每个计算过程的冗余复制存储。该算法针对基于现代集群的体系结构,该体系结构由通过专用通信网络连接的多处理器节点组成。并行性在两个级别上实现:通过共享内存并行技术在计算节点内实现并行性,以及使用分布式内存技术在节点之间实现并行性。新的并行实现旨在允许对中(500-750基函数)到大规模(750-1000基函数)CCSD(T)能量进行例行评估。使用aug-cc-pVTZ基集对水六聚体的五个低位异构体进行样品计算。

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