Acceleration of industrial application of speed-up methods in ultra large_scale domain decomposition computation

2017 Fiscal Year Final Research Report

• Project/Area Number: 15K04762
• Research Category: Grant-in-Aid for Scientific Research (C)
• Allocation Type: Multi-year Fund
• Section: 一般
• Research Field: Computational science
• Research Institution: Japan Women's University
• Principal Investigator: Kanayama Hiroshi 日本女子大学, 理学部, 研究員 (90294884)
• Project Period (FY): 2015-04-01 – 2018-03-31
• Keywords: BDD-DIAG前処理 / DIAG前処理 / 静磁場解析 / 熱対流解析

Outline of Final Research Achievements

An iterative domain decomposition method is proposed for numerical analysis of 3-Dimensional (3D) linear magnetostatic problems taking the magnetic vector potential as an unknown function. The iterative domain decomposition method is combined with the Preconditioned Conjugate Gradient (PCG) procedure and the Hierarchical Domain Decomposition Method (HDDM) which is adopted in parallel computing. Our previously employed preconditioner was the Neumann-Neumann (NN) preconditioner. Numerical results showed that the method was only effective for smaller problems. In this research, we consider its improvement with the Balancing Domain Decomposition DIAGonal scaling (BDD-DIAG) preconditioner. Specially, the multi-part processing is challenged for the first time though our present success is mainly limited to a single part processing.

Free Research Field

偏微分方程式の有限要素近似による大規模計算