A parallel scalable PETSc-based Jacobi-Davidson polynomial Eigensolver with application in quantum dot simulation

Zih Hao Wei*, Feng Nan Hwang, Tsung Ming Huang, Weichung Wang

*此作品的通信作者

研究成果: 書貢獻/報告類型會議論文篇章

1 引文 斯高帕斯(Scopus)

摘要

The Jacobi-Davidson (JD) algorithm recently has gained popularity for finding a few selected interior eigenvalues of large sparse polynomial eigenvalue problems, which commonly appear in many computational science and engineering PDE based applications. As other inner-outer algorithms like Newton type method, the bottleneck of the JD algorithm is to solve approximately the inner correction equation. In the previous work, [Hwang, Wei, Huang, and Wang, A Parallel Additive Schwarz Preconditioned Jacobi-Davidson (ASPJD) Algorithm for Polynomial Eigenvalue Problems in Quantum Dot (QD) Simulation, Journal of Computational Physics (2010)], the authors proposed a parallel restricted additive Schwarz preconditioner in conjunction with a parallel Krylov subspace method to accelerate the convergence of the JD algorithm. Based on the previous computational experiences on the algorithmic parameter tuning for the ASPJD algorithm, we further investigate the parallel performance of a PETSc based ASPJD eigensolver on the Blue Gene/P, and a QD quintic eigenvalue problem is used as an example to demonstrate its scalability by showing the excellent strong scaling up to 2,048 cores.

原文英語
主出版物標題Domain Decomposition Methods in Science and Engineering XIX
頁面157-164
頁數8
DOIs
出版狀態已發佈 - 2010
事件19th International Conference on Domain Decomposition, DD19 - Zhanjiajie, 中国
持續時間: 2009 八月 172009 八月 22

出版系列

名字Lecture Notes in Computational Science and Engineering
78 LNCSE
ISSN(列印)1439-7358

會議

會議19th International Conference on Domain Decomposition, DD19
國家/地區中国
城市Zhanjiajie
期間2009/08/172009/08/22

ASJC Scopus subject areas

  • 建模與模擬
  • 工程 (全部)
  • 離散數學和組合
  • 控制和優化
  • 計算數學

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