TY - GEN
T1 - Performance evaluation of a next-generation CFD on various supercomputing systems
AU - Komatsu, Kazuhiko
AU - Soga, Takashi
AU - Egawa, Ryusuke
AU - Takizawa, Hiroyuki
AU - Kobayashi, Hiroaki
PY - 2013
Y1 - 2013
N2 - The Building-Cube Method (BCM) has been proposed as a new CFD method for an efficient three-dimensional flow simulation on large-scale supercomputing systems, and is based on equally-spaced Cartesian meshes. As a flow domain can be divided into equally-partitioned cells due to the equally-spaced meshes, the flow computations can be divided to partial computations of the same computational cost. To achieve a high sustained performance, architecture-aware implementations and optimizations considering characteristics of supercomputing systems are essential because there have been various types of supercomputing systems such as a scalar type, a vector type, and an accelerator type. This paper discusses the architecture-aware implementations and optimizations for various supercomputing systems such as an Intel Nehalem-EP cluster, an Intel Nehalem-EX cluster, Fujitsu FX-1, Hitachi SR16000 M1, NEC SX-9, and a GPU cluster, and analyses their sustained performance for BCM. The performance analysis shows that memory and network capabilities largely affect the performance of BCM rather than computational potentials.
AB - The Building-Cube Method (BCM) has been proposed as a new CFD method for an efficient three-dimensional flow simulation on large-scale supercomputing systems, and is based on equally-spaced Cartesian meshes. As a flow domain can be divided into equally-partitioned cells due to the equally-spaced meshes, the flow computations can be divided to partial computations of the same computational cost. To achieve a high sustained performance, architecture-aware implementations and optimizations considering characteristics of supercomputing systems are essential because there have been various types of supercomputing systems such as a scalar type, a vector type, and an accelerator type. This paper discusses the architecture-aware implementations and optimizations for various supercomputing systems such as an Intel Nehalem-EP cluster, an Intel Nehalem-EX cluster, Fujitsu FX-1, Hitachi SR16000 M1, NEC SX-9, and a GPU cluster, and analyses their sustained performance for BCM. The performance analysis shows that memory and network capabilities largely affect the performance of BCM rather than computational potentials.
UR - http://www.scopus.com/inward/record.url?scp=84896631761&partnerID=8YFLogxK
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U2 - 10.1007/978-3-642-32454-3_11
DO - 10.1007/978-3-642-32454-3_11
M3 - Conference contribution
AN - SCOPUS:84896631761
SN - 9783642324536
T3 - Sustained Simulation Performance 2012 - Proceedings of the Joint Workshop on High Performance Computing on Vector Systems, and Workshop on Sustained Simulation Performance
SP - 123
EP - 132
BT - Sustained Simulation Performance 2012 - Proceedings of the Joint Workshop on High Performance Computing on Vector Systems, and Workshop on Sustained Simulation Performance
PB - Springer Science and Business Media, LLC
T2 - Joint Workshop on High Performance Computing on Vector Systems and 15th Workshop on Sustained Simulation Performance 2012
Y2 - 1 March 2012 through 1 March 2012
ER -