On Monte Carlo and Quasi-Monte Carlo for Matrix Computations

DOI10.1007/978-3-319-73441-5_26zbMath1476.65006OpenAlexW2781963889MaRDI QIDQ3297445

Diego Davila, Vassil Alexandrov, Emanouil Atanassov, Aneta Karaivanova, T. V. Gurov, Oscar A. Esquivel-Flores

Publication date: 20 July 2020

Published in: Large-Scale Scientific Computing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-3-319-73441-5_26

zbMATH Keywords

hybrid methodsMonte Carlo for linear algebraquasi-Monte Carlo for linear algebra

Mathematics Subject Classification ID

Monte Carlo methods (65C05) Numerical linear algebra (65F99)

Related Items (1)

Monte Carlo method for estimating eigenvalues using error balancing

Uses Software

• MatrixMarket
• SparseMatrix
• MSPAI

Cites Work

• A new algorithm with maximal rate convergence to obtain inverse matrix
• An efficient parallel implementation of the MSPAI preconditioner
• Sparse approximate inverse preconditioning for dense linear systems arising in computational electromagnetics
• Factorized sparse approximate inverses for preconditioning
• Towards Monte Carlo preconditioning approach and hybrid Monte Carlo algorithms for matrix computations
• The university of Florida sparse matrix collection
• On the Preconditioned Quasi-Monte Carlo Algorithm for Matrix Computations
• A Sparse Approximate Inverse Preconditioner for the Conjugate Gradient Method
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