Recent memory and performance improvements in Octopus code

Abstract

In this work we present the improvements made to the Octopus code in order to reduce the memory requirements and to optimise parallel data distribution. Both topics are central for efficiency and feasibility of calculations when the system must be run in a large HPC environment. These modifications were mainly made in the real-space mesh partitioning and mapping algorithms, and are thus transferable to other codes using this type of real-space representation of data. The code became much more efficient, and we present several scalability results showing that it is now possible to address ab-initio quantum-mechanical simulations of the interaction of light with big biomolecules, paving the way for a better understanding of phenomena such as energy conversion in plants. © 2014 Springer International Publishing.