Memory-Access Optimization of Parallel Molecular Dynamics Simulation via Dynamic Data Reordering

Dynamic irregular applications such as molecular dynamics (MD) simulation often suffer considerable performance deterioration during execution. To address this problem, an optimal data-reordering schedule has been developed for runtime memory-access optimization of MD simulations on parallel computers. Analysis of the memory-access penalty during MD simulations shows that the performance improvement from computation and data reordering degrades gradually as data translation lookaside buffer misses increase. We have also found correlations between the performance degradation with physical properties such as the simulated temperature, as well as with computational parameters such as the spatial-decomposition granularity. Based on a performance model and pre-profiling of data fragmentation behaviors, we have developed an optimal runtime data-reordering schedule, thereby archiving speedup of 1.35, 1.36 and 1.28, respectively, for MD simulations of silica at temperatures 300 K, 3,000 K and 6,000 K.