Generating coupled cluster code for modern distributed memory tensor software

Abstract

Scientific groups are struggling to adapt their codes to quickly-developing GPU-based HPC platforms. The domain of distributed coupled cluster (CC) calculations is not an exception. Moreover, our applications to tiny QED effects require higher-order CC which include thousands of tensor contractions, which makes automatic treatment imperative. The challenge is to allow efficient implementation by capturing key symmetries of the problem, while retaining the abstraction from the hardware. We present the tensor programming framework tenpi, which seeks to find this balance. It features a python library user interface, global optimization of intermediates, a visualization module and Fortran code generator that bridges the DIRAC package for relativistic molecular calculations to tensor contraction libraries. tenpi brings higher-order CC functionality to the massively parallel module of DIRAC. The architecture and design decision schemes are accompanied by benchmarks and by first production calculations on Summit, Frontier and LUMI along with state-of-the-art of tensor contraction software.