Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/319905
Type: Artigo de periódico
Title: Seismic Wave Propagation Simulations On Low-power And Performance-centric Manycores
Author: Castro
M; Francesquini
E; Dupros
F; Aochi
H; Navaux
POA; Mehaut
JF
Abstract: 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 efficient than ever. As a response to this need, energy-efficient 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 efficient 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 efficient seismic wave propagation kernel on these platforms are very different. In this work we compare the performance and energy efficiency 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 efficiency, 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. (C) 2016 Elsevier B.V. All rights reserved.
Subject: Seismic Wave Propagation
Mppa-256
Xeon Phi
Hpc
Performance
Energy Efficiency
Editor: ELSEVIER SCIENCE BV
Rights: fechado
Identifier DOI: 10.1016/j.parco.2016.01.011
Address: http://www-sciencedirect-com.ez88.periodicos.capes.gov.br/science/article/pii/S0167819116000417
Date Issue: 2016
Appears in Collections:Unicamp - Artigos e Outros Documentos

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