Parallel-algorithm extension for tsunami and earthquake-cycle simulators for massively parallel execution on the K computer

Abstract

This article presents a case study on the extension of parallel algorithms in tsunami and earthquake-cycle simulators for massively parallel execution on the K computer. We use two target applications: a tsunami-simulation program, “JAGURS,” and an earthquake-cycle program, “RSGDX.” Our optimization strategy for collective communication is to split the Message Passing Interface (MPI) communicator and perform multistage localized communication to minimize the communication frequency, transferred data size, and network congestion. Moreover, in the case of severe load imbalances, we apply cyclic distribution and extend the axes for parallelization. For each application, we conduct a performance evaluation with massively parallel execution on the K computer. It is shown that our optimized code enables JAGURS to attain a 21.8× speedup for collective communication and a 7.9× speedup for the time-step loop on 8748 nodes (69,984 cores). RSGDX attains a 4.25× speedup for collective communication and an 18.7× speedup for the time-step loop on 8192 nodes (65,536 cores).