Coupled‐cluster singles, doubles and perturbative triples with density fitting approximation for massively parallel heterogeneous platforms. Issue 12 (12th January 2019)

• Record Type: Journal Article
• Authors: Peng, Chong; Calvin, Justus A.; Valeev, Edward F.
• Other Names: Alexeev Yuri guestEditor.; Harrison Robert guestEditor.
• Is Part Of: International journal of quantum chemistry. Volume 119:Issue 12(2019)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2019-01-12
• Subjects: coupled‐cluster perturbative triples -- coupled‐cluster singles doubles -- density‐fitting -- graphics processing units -- parallel computing; Quantum chemistry -- Periodicals; 541.28
• DOI: 10.1002/qua.25894
• Languages: English
• ISSNs: 0020-7608

Abstract

Abstract: A high‐performance implementation of the coupled‐cluster singles, doubles, and perturbative triples [CCSD(T)] is developed in the Massively Parallel Quantum Chemistry program. Novel features include: (1) reduced memory requirements via a density‐fitting (DF) CCSD implementation utilizing distributed lazy evaluation for tensors with more than two unoccupied indices and (2) the ability to utilize efficiently many‐core nodes (Intel Xeon Phi) and heterogeneous nodes with multiple NVIDIA GPUs on each node. All data that are greater than quadratic in the system size are distributed among processes. Excellent strong scaling is observed on distributed‐memory computers equipped with conventional CPUs, Intel Xeon Phi processors, and heterogeneous nodes with multiple NVIDIA GPUs Canonical CCSD(T) energies can be evaluated for systems containing 200 electrons and 1000 basis functions in a few days using a small size commodity cluster, with even larger computations possible on leadership‐class computing resources. Abstract : The multi‐node multi‐GPU performance of the (T) implementation in the Massively Parallel Quantum Chemistry package.