Search

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).

Silicon nanowires are potentially useful in next-generation field-effect transistors, and it is important to clarify the electron states of silicon nanowires to know the behavior of new devices. Computer simulations are promising tools for calculating electron states. Real-space density functional theory (RSDFT) code performs first-principles electronic structure calculations. To obtain higher performance, we applied various optimization techniques to the code: multi-level parallelization, load balance management, sub-mesh/torus allocation, and a message-passing interface library tuned for the K computer. We measured and evaluated the performance of the modified RSDFT code on the K computer. A 5.48 petaflops (PFLOPS) sustained performance was measured for an iteration of a self-consistent field calculation for a 107,292-atom Si nanowire simulation using 82,944 compute nodes, which is 51.67% of the K computer’s peak performance of 10.62 PFLOPS. This scale of simulation enables analysis of the behavior of a silicon nanowire with a diameter of 10–20 nm.

Plasma turbulence research based on five-dimensional (5D) gyrokinetic simulations is one of the most critical and demanding issues in fusion science. To pioneer new physics regimes both in problem sizes and in timescales, an improvement of strong scaling is essential. Overlap of computations and communications using non-blocking MPI communication schemes is a promising approach to improving strong scaling, but it often fails on practical applications with conventional MPI libraries. In this work, this classical issue is resolved by developing communication-overlap techniques with additional MPI support for non-blocking communication routines and with heterogeneous OpenMP threads, which work even on conventional MPI libraries and network hardware. These techniques dramatically improved the parallel efficiency of a gyrokinetic toroidal 5D Eulerian code GT5D on the K-computer, which has a dedicated network, and on the Helios system which has a commodity network. On the K-computer, excellent strong scaling was achieved beyond 100k cores whilst keeping a sustained performance of [Formula: see text]10% ([Formula: see text]307 TFlops using 196,608 cores), and simulations for next-generation large-scale fusion experiments are significantly accelerated. This performance is 16[Formula: see text] sped up compared with the maximum performance reported at the 2011 International Conference for High Performance Computing, Networking, Storage and Analysis ([Formula: see text]19 TFlops using 16,384 cores of the BX900 cluster) (Idomura, 2011).