Efficient and optimal parallel algorithms for cholesky decomposition

Eunice E. Santos, Pei Yue Chu

Research output: Contribution to journalArticlepeer-review


In this paper, we consider the problem of developing efficient and optimal parallel algorithms for Cholesky decomposition. We design our algorithms based on different data layouts and methods. We thereotically analyze the run-time of each algorithm. In order to determine the optimality of the algorithms designed, we derive theoretical lower bounds on running time based on initial data layout and compare them against the algorithmic run-times. To address portability, we design our algorithms and perform complexity analysis on the LogP model. Lastly, we implement our algorithms and analyze performance data.

Original languageEnglish (US)
Pages (from-to)217-234
Number of pages18
JournalJournal of Mathematical Modelling and Algorithms
Issue number3
StatePublished - 2003


  • Algorithms and complexity
  • Cholesky decomposition
  • LogP model
  • Numerical linear algebra
  • Parallel complexity

ASJC Scopus subject areas

  • Modeling and Simulation
  • Applied Mathematics


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