An out-of-core implementation of the COLUMBUS massively-parallel multireference configuration interaction program

Abstract

In this paper, we describe a novel parallelization approach we developed to solve the largest multireference configuration interaction (MRCI) problem ever attempted. From the mathematical perspective, the program solves the eigenvalue problem for a very large, sparse, symmetric Hamilton matrix. Using an out-of-core approach, shared memory programming model, improved data compression algorithms, and dynamic load balancing we were able to solve a problem six times larger than previously reported. The potential curve for the chromium dimer was calculated with a Hamilton matrix of dimension 1.3 billion (1,295,937,374). This task involved moving 1.5 terabytes of data between main memory and secondary storage per MRCI iteration. Furthermore, by employing Active Messages and user-level striping to combine multiple files on local disks on the IBM SP into a single logically-shared file, the execution time of the program was reduced by a factor of three, as compared to our initial implementation on top of the IBM PIOFS parallel filesystem.