GFCCLib：可扩展的高效耦合簇格林函数库，用于精确解决多种体电子结构问题
GFCCLib: Scalable and Efficient Coupled-Cluster Green's Function Library for Accurately Tackling Many Body Electronic Structure Problems
摘要：
耦合团簇格林函数（GFCC）计算由于能够从多体的角度系统地研究分子和材料的电子结构问题，近年来受到了广泛的关注。然而，科学计算集群上的GFCC计算通常受到复杂空间中昂贵的高维张量收缩、昂贵的进程间通信和严重的负载不平衡的影响，这限制了它在处理电子结构问题中的常规使用。在这里，我们提出了一个数值库原型，是专门为大规模GFCC计算。该库的设计集中在系统优化的计算策略，以提高其可扩展性和效率。通过在远程巨型计算集群上运行GFCC计算的相关分析，证明了该库的性能。该库的能力是突出的计算宽近价带的富勒烯C60分子的第一次在GFCCSD水平，表现出良好的协议与实验光谱。
英文摘要：
Coupled cluster Green's function (GFCC) calculation has drawn much attention in the recent years for targeting the molecular and material electronic structure problems from a many body perspective in a systematically improvable way. However, GFCC calculations on scientific computing clusters usually suffer from expensive higher dimensional tensor contractions in the complex space, expensive interprocess communication, and severe load imbalance, which limits it's routine use for tackling electronic structure problems. Here we present a numerical library prototype that is specifically designed for large scale GFCC calculations. The design of the library is focused on a systematically optimal computing strategy to improve its scalability and efficiency. The performance of the library is demonstrated by the relevant profiling analysis of running GFCC calculations on remote giant computing clusters. The capability of the library is highlighted by computing a wide near valence band of a fullerene C60 molecule for the first time at the GFCCSD level that shows excellent agreement with the experimental spectrum.
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