MatrixMarket

The Matrix Market provides convenient access to a repository of test data for use in comparative studies of algorithms for numerical linear algebra. Matrices as well as matrix generation software and services, from linear systems, least squares, and eigenvalue computations in a wide variety of scientific and engineering disciplines are provided. Tools for browsing through the collection or for searching for matrices with special properties are included. Each matrix (and matrix set) has its own ”home page” which provides details of matrix properties, visualization of matrix structure, and permits downloading of the matrix in one of several text file formats. Similarly, each matrix generator has a home page describing its properties. Generators are either static software which you can download and include in your applications, Java applets which will generate matrices in your Web browser, or form-based requests to generate matrices at the Matrix Market and return them to your browser. Currently, 482 individual matrices and 25 matrix generators are available. Our database now includes the entire Harwell-Boeing Sparse Matrix Collection (Release I), Yousef Saad’s SPARSKIT collection, and the Nonsymmetric Eigenvalue Problem (NEP) collection of Bai, Day, Demmel and Dongarra. The Matrix Market is a component of the NIST project on Tools for Evaluation of Mathematical and Statistical Software which has focus areas in linear algebra, special functions and statistics.


References in zbMATH (referenced in 160 articles )

Showing results 1 to 20 of 160.
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  1. Behling, Roger; Bello-Cruz, J.-Yunier; Santos, Luiz-Rafael: The block-wise circumcentered-reflection method (2020)
  2. Benner, Peter; Heinkenschloss, Matthias; Saak, Jens; Weichelt, Heiko K.: Efficient solution of large-scale algebraic Riccati equations associated with index-2 DAEs via the inexact low-rank Newton-ADI method (2020)
  3. Chen, Tyler; Carson, Erin: Predict-and-recompute conjugate gradient variants (2020)
  4. Marques, Osni; Demmel, James; Vasconcelos, Paulo B.: Bidiagonal SVD computation via an associated tridiagonal eigenproblem (2020)
  5. Ravibabu, Mashetti; Singh, Arindama: The least squares and line search in extracting eigenpairs in Jacobi-Davidson method (2020)
  6. Yang, Zhen; Jing, Yan-Fei; Niu, Qiang: Restarted simpler GMRES augmented with harmonic Ritz vectors and approximate errors (2020)
  7. Zhang, Liping; Fan, Hung-Yuan; Chu, Eric King-Wah: Krylov subspace methods for discrete-time algebraic Riccati equations (2020)
  8. Zhao, Kang; Liao, Anping: Updating the undamped piezoelectric smart structure system with no-spillover (2020)
  9. Astudillo, R.; de Gier, J. M.; van Gijzen, M. B.: Accelerating the induced dimension reduction method using spectral information (2019)
  10. Camps, Daan; Meerbergen, Karl; Vandebril, Raf: A rational QZ method (2019)
  11. Heyouni, Mohammed; Saberi-Movahed, Farid; Tajaddini, Azita: On global Hessenberg based methods for solving Sylvester matrix equations (2019)
  12. Hoshi, Takeo; Imachi, Hiroto; Kuwata, Akiyoshi; Kakuda, Kohsuke; Fujita, Takatoshi; Matsui, Hiroyuki: Numerical aspect of large-scale electronic state calculation for flexible device material (2019)
  13. Lopes, R.; Santos, S. A.; Silva, P. J. S.: Accelerating block coordinate descent methods with identification strategies (2019)
  14. Lupo Pasini, Massimiliano: Convergence analysis of Anderson-type acceleration of Richardson’s iteration. (2019)
  15. Mchedlidze, Tamara; Pak, Alexey; Klammler, Moritz: Aesthetic discrimination of graph layouts (2019)
  16. Pandur, Marija Miloloža: Preconditioned gradient iterations for the eigenproblem of definite matrix pairs (2019)
  17. Pozza, Stefano; Simoncini, Valeria: Inexact Arnoldi residual estimates and decay properties for functions of non-Hermitian matrices (2019)
  18. Sacchi, Giulia; Simoncini, Valeria: A GMRES convergence analysis for localized invariant subspace ill-conditioning (2019)
  19. Yin, Guojian: A contour-integral based method for counting the eigenvalues inside a region (2019)
  20. Addam, Mohamed; Elbouyahyaoui, Lakhdar; Heyouni, Mohammed: On Hessenberg type methods for low-rank Lyapunov matrix equations (2018)

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Further publications can be found at: http://math.nist.gov/MatrixMarket/bib.html