GFCCLib: Scalable and efficient coupled-cluster Green's function library for accurately tackling many-body electronic structure problems

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 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. Program summary Program Title: GFCCLib CPC Library link to program files: https://doi.org/10.17632/j594wydctd.1 Code Ocean capsule: https://doi.org/10.24433/CO.5131827.v1 Licensing provisions: MIT License Programming language: C++ Nature of problem: The applications of coupled cluster Green's function on large scale molecular electronic structure problems suffer from expensive higher dimensional tensor contractions in the complex space, expensive inter-process communication, and severe load imbalance. Tackling these issues are a key step in building high-performance coupled cluster Green's function library for its routine use in large scale molecular science. Solution method: We have developed a C++ library for large scale molecular GFCC calculations on highperformance computing clusters. We provide implementations for high dimensional tensor algebra for many-body methods (TAMM), Cholesky decomposition of high dimensional electron repulsion integral tensors, process group technique for mitigating load imbalance. The library is written in C++. The source code, tutorials and documentation are provided online. A continuous integration mechanism is set up to automatically run a series of regression tests and check code coverage when the codebase is updated. (C) 2021 Elsevier B.V. All rights reserved.

Automated summary

GFCC calculations are limited by expensive higher dimensional tensor contractions, interprocess communication, and load imbalance on scientific computing clusters. This study presents a numerical library prototype designed for large-scale GFCC calculations with a focus on improving scalability and efficiency. The performance of the library is demonstrated through profiling analysis of running GFCC calculations on remote computing clusters.