标题： 大规模并行的解析本征耦合簇方法在分子系统数值原子中心轨道框架中的实现 显示英文标题

标题： Massive-parallel Implementation of the Resolution-of-Identity Coupled-cluster Approaches in the Numeric Atom-centered Orbital Framework for Molecular Systems

摘要： 我们介绍了在FHI-aims包中实现的分辨能力（RI）耦合簇方法的大规模并行版本，该方法包括单重、双重和微扰三重激发，即RI-CCSD(T)，用于分子系统。 设计了一种基于域的分布式内存算法，在MPI/OpenMP混合框架中，以有效利用内存带宽并显著减少互连通信，特别是粒子-粒子梯子项评估中的张量收缩。 我们的实现特点是没有实时磁盘存储，并且在10,000个以上核心上具有出色的强可扩展性。 通过一组不同大小的分子，我们证明了我们的CCSD(T)代码的并行性能与最先进的高性能计算（HPC）计算化学包中的CC实现相竞争。 我们还证明了在我们的RI-CCSD(T)中使用RI近似所产生的数值误差可以忽略不计。 结合相关一致的数值原子中心轨道（NAO）基组NAO-VCC-nZ，该方法被用于生成22种生物导向的弱相互作用（S22）、11种气态半胱氨酸构象体（CYCONF）的构象能量和32种异构化能量（ISO32）的准确理论参考数据。 显示英文摘要

摘要： We present a massive-parallel implementation of the resolution-of-identity (RI) coupled-cluster approach that includes single, double and perturbatively triple excitations, namely RI-CCSD(T), in the FHI-aims package for molecular systems. A domain-based distributed-memory algorithm in the MPI/OpenMP hybrid framework has been designed to effectively utilize the memory bandwidth and significantly minimize the interconnect communication, particularly for the tensor contraction in the evaluation of the particle-particle ladder term. Our implementation features a rigorous avoidance of the on-the-fly disk storage and an excellent strong scaling up to 10,000 and more cores. Taking a set of molecules with different sizes, we demonstrate that the parallel performance of our CCSD(T) code is competitive with the CC implementations in state-of-the-art high-performance computing (HPC) computational chemistry packages. We also demonstrate that the numerical error due to the use of RI approximation in our RI-CCSD(T) is negligibly small. Together with the correlation-consistent numeric atom-centered orbital (NAO) basis sets, NAO-VCC-nZ, the method is applied to produce accurate theoretical reference data for 22 bio-oriented weak interactions (S22), 11 conformational energies of gaseous cysteine conformers (CYCONF), and 32 isomerization energies (ISO32).