Parallelization of a multiconfigurational perturbation theory

TY - JOUR

T1 - Parallelization of a multiconfigurational perturbation theory

AU - Vancoillie, Steven

AU - Delcey, Mickael G.

AU - Lindh, Roland

AU - Vysotskiy, Victor

AU - Malmqvist, Per-Åke

AU - Veryazov, Valera

N1 - The information about affiliations in this record was updated in December 2015. The record was previously connected to the following departments: Theoretical Chemistry (S) (011001039)

PY - 2013

Y1 - 2013

N2 - In this work, we present a parallel approach to complete and restricted active space second-order perturbation theory, (CASPT2/RASPT2). We also make an assessment of the performance characteristics of its particular implementation in the Molcas quantum chemistry programming package. Parallel scaling is limited by memory and I/O bandwidth instead of available cores. Significant time savings for calculations on large and complex systems can be achieved by increasing the number of processes on a single machine, as long as memory bandwidth allows, or by using multiple nodes with a fast, low-latency interconnect. We found that parallel efficiency drops below 50% when using 8-16 cores on the shared-memory architecture, or 16-32 nodes on the distributed-memory architecture, depending on the calculation. This limits the scalability of the implementation to a moderate amount of processes. Nonetheless, calculations that took more than 3 days on a serial machine could be performed in less than 5 h on an InfiniBand cluster, where the individual nodes were not even capable of running the calculation because of memory and I/O requirements. This ensures the continuing study of larger molecular systems by means of CASPT2/RASPT2 through the use of the aggregated computational resources offered by distributed computing systems. (c) 2013 Wiley Periodicals, Inc.

AB - In this work, we present a parallel approach to complete and restricted active space second-order perturbation theory, (CASPT2/RASPT2). We also make an assessment of the performance characteristics of its particular implementation in the Molcas quantum chemistry programming package. Parallel scaling is limited by memory and I/O bandwidth instead of available cores. Significant time savings for calculations on large and complex systems can be achieved by increasing the number of processes on a single machine, as long as memory bandwidth allows, or by using multiple nodes with a fast, low-latency interconnect. We found that parallel efficiency drops below 50% when using 8-16 cores on the shared-memory architecture, or 16-32 nodes on the distributed-memory architecture, depending on the calculation. This limits the scalability of the implementation to a moderate amount of processes. Nonetheless, calculations that took more than 3 days on a serial machine could be performed in less than 5 h on an InfiniBand cluster, where the individual nodes were not even capable of running the calculation because of memory and I/O requirements. This ensures the continuing study of larger molecular systems by means of CASPT2/RASPT2 through the use of the aggregated computational resources offered by distributed computing systems. (c) 2013 Wiley Periodicals, Inc.

KW - parallellization

KW - CASPT2

KW - multiconfigurational perturbation theory

KW - high

KW - performance computing

U2 - 10.1002/jcc.23342

DO - 10.1002/jcc.23342

M3 - Article

C2 - 23749386

VL - 34

SP - 1937

EP - 1948

JO - Journal of Computational Chemistry

JF - Journal of Computational Chemistry

SN - 1096-987X

IS - 22

ER -