Multi-core aware process mapping and its impact on communication overhead of parallel applications

We propose an approach to reduce the execution time of applications with a steady communication pattern on clusters of multi-core processors by leveraging the asymmetry of core communication speeds. In addition to the well known fact that communication link speeds on a fixed cluster vary with processor selection, we consider one effect of multicore processor chips: link speeds vary with core selection within a single processor chip. The approach requires measuring link speeds among cluster cores as well as communication volumes and computational loads of the selected application processes. This data is fed into the dual recursive bipartitioning method to obtain close to optimal application process placement on cluster cores. We apply this approach to a real world application achieving sensible execution time reduction without even recompiling source code.