http://swrc.ontoware.org/ontology#InProceedings
Development of Explicit Eulerian Finite Difference Solver for Large-Scale Fluid-Structure Interaction Systems
en
アプリケーション
The University of Tokyo
Fujitsu Nagano Systems Engineering Ltd.
Riken
Riken
The University of Tokyo
The University of Tokyo／Riken
The University of Tokyo
Riken
Kazuyasu Sugiyama
Yasuhiro Kawashima
Hiroshi Koyama
Shigeho Noda
Satoshi Ii
Shu Takagi
Yoichiro Matsumoto
Ryutaro Himeno
A scalable numerical algorithm has been reconsidered for massively parallel computations of fluid-structure interaction systems as biological applications. A new Eulerian method using a fixed mesh has been developed to solve the basic equation set for the incompressible Newtonian fluid and hyperelastic material in a finite difference manner. A new artificial compressibility method, corresponding to one of full explicit time-stepping algorithms, with adaptive parameters is proposed. The advocated solver easily attains excellent scalability since it makes the workload on each core equivalent and reduces the amount of node-to-node communication required for the iterative computation. It is applied to wall-bounded flows with biconcave particles, which replicate the shape of red blood cells. The computational performance on a Xeon cluster is presented in terms of a weak scaling and also of a strong scaling with O(109) grid points up to 8,192 cores.
A scalable numerical algorithm has been reconsidered for massively parallel computations of fluid-structure interaction systems as biological applications. A new Eulerian method using a fixed mesh has been developed to solve the basic equation set for the incompressible Newtonian fluid and hyperelastic material in a finite difference manner. A new artificial compressibility method, corresponding to one of full explicit time-stepping algorithms, with adaptive parameters is proposed. The advocated solver easily attains excellent scalability since it makes the workload on each core equivalent and reduces the amount of node-to-node communication required for the iterative computation. It is applied to wall-bounded flows with biconcave particles, which replicate the shape of red blood cells. The computational performance on a Xeon cluster is presented in terms of a weak scaling and also of a strong scaling with O(109) grid points up to 8,192 cores.
ハイパフォーマンスコンピューティングと計算科学シンポジウム論文集
2012
153-162
2012-01-17