On the optimization of a pipeline model to integrate the reduced dimensionality Schrödinger equations for distributed memory architectures

This paper examines the problem of dealing with the integration of a two-dimensional Schrödinger equation using a sector-diabatic coupled-channel approach when the coupling matrix is too large to fit into the memory of individual nodes of a multiple-instruction, multiple-data (MIMD) parallel machine. For this case, the distribution of blocks of the coupling matrix among the different nodes and the use of a pipeline model are investigated. To measure performances and to compare them with those measured for a previously optimized task farm model, the pipeline model was implemented on a hypercube and its structure optimized. Benchmarks were performed for dimensions of the coupling matrix manageable by both task farm and pipeline models.