Seismic wave propagation simulations on low-power and performance-centric manycores

The large processing requirements of seismic wave propagation simulations make High Performance Computing (HPC) architectures a natural choice for their execution. However, to keep both the current pace of performance improvements and the power consumption under a strict power budget, HPC systems must be more energy e cient than ever. As a response to this need, energye cient and low-power processors began to make their way into the market. In this paper we employ a novel low-power processor, the MPPA-256 manycore, to perform seismic wave propagation simulations. It has 256 cores connected by a NoC, no cache-coherence and only a limited amount of on-chip memory. We describe how its particular architectural characteristics influenced our solution for an energy-e cient implementation. As a counterpoint to the low-power MPPA-256 architecture, we employ Xeon Phi, a performance-centric manycore. Although both processors share some architectural similarities, the challenges to implement an e cient seismic wave propagation kernel on these platforms are very di↵erent. In this work we compare the performance and energy e ciency of our implementations for these processors to proven and optimized solutions for other hardware platforms such as general-purpose processors and a GPU. Our experimental results show that MPPA-256 has the best energy e ciency, consuming at least 77% less energy than the other evaluated platforms, whereas the performance of our solution for the Xeon Phi is on par with a state-of-the-art solution for GPUs.