学際大規模情報基盤共同利用・共同研究拠点

採択課題 【詳細】

jh180022-NAHI Innovative Multigrid Methods
課題代表者 中島研吾(東京大学)
Kengo Nakajima (The University of Tokyo)
概要 In the present work, we are developing robust and efficient GMG and AMG methods, where we are focusing on development of algorithms for (1) efficient and robust smoother, (2) parallel global reordering/aggregation methods for robustness, (3) utilization of near-kernel vectors for robustness, and (4) hierarchical methods for scalability. Moreover, we develop new algorithms for Parallel-in-Space/Time (PinST).
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