Bhatelé et al.
Our methodology builds upon the idea of object-based decomposition used in Charm++ which separates the processes of decomposition from mapping of computation to processors and allows a more flexible mapping based on communication patterns between objects. Exploiting this and the topology of the allocated job partition, we present mapping strategies for a production code, OpenAtom to improve overall performance and scaling. OpenAtom presents complex communication scenarios of interaction between multiple groups of objects and makes the mapping task a challenge. Results are presented for OpenAtom on up to 16,384 processors of Blue Gene/L, 8,192 processors of Blue Gene/P and 2,048 processors of Cray XT3.