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.
Keywords for this software
References in zbMATH (referenced in 114 articles )
Showing results 1 to 20 of 114.
Sorted by year (- Bertaccini, Daniele; Durastante, Fabio: Iterative methods and preconditioning for large and sparse linear systems with applications (2018)
- Rendl, Fanz; Sotirov, Renata: The MIN-cut and vertex separator problem (2018)
- Schlüter, Federico; Strappa, Yanela; Milone, Diego H.; Bromberg, Facundo: Blankets joint posterior score for learning Markov network structures (2018)
- Stanimirović, Ivan: Computation of generalized matrix inverses and applications (2018)
- Dehghan, Mehdi; Mohammadi-Arani, Reza: Generalized product-type methods based on bi-conjugate gradient (GPBiCG) for solving shifted linear systems (2017)
- Stachurski, Andrzej: On a conjugate directions method for solving strictly convex QP problem (2017)
- Torun, F. Sukru; Manguoglu, Murat; Aykanat, Cevdet: Parallel minimum norm solution of sparse block diagonal column overlapped underdetermined systems (2017)
- Guglielmi, Nicola: On the method by Rostami for computing the real stability radius of large and sparse matrices (2016)
- Jessup, Elizabeth; Motter, Pate; Norris, Boyana; Sood, Kanika: Performance-based numerical solver selection in the Lighthouse framework (2016)
- Kestyn, James; Polizzi, Eric; Tang, Ping Tak Peter: Feast eigensolver for non-Hermitian problems (2016)
- Kostić, Vladimir R.; Międlar, Agnieszka; Cvetković, Ljiljana: An algorithm for computing minimal Ger\vsgorinsets. (2016)
- Michailidis, Panagiotis D.; Margaritis, Konstantinos G.: Scientific computations on multi-core systems using different programming frameworks (2016)
- Wellin, Paul: Essentials of programming in Mathematica (2016)
- Bebiano, N.; da Provid^encia, J.; Nata, A.; da Provid^encia, J. P.: An inverse indefinite numerical range problem (2015)
- Beik, Fatemeh Panjeh Ali; Salkuyeh, Davod Khojasteh: Weighted versions of Gl-FOM and Gl-GMRES for solving general coupled linear matrix equations (2015)
- Bujanović, Zvonimir; Drmač, Zlatko: A new framework for implicit restarting of the Krylov-Schur algorithm. (2015)
- Buttà, P.; Guglielmi, N.; Manetta, M.; Noschese, S.: Differential equations for real-structured defectivity measures (2015)
- Gaaf, Sarah W.; Hochstenbach, Michiel E.: Probabilistic bounds for the matrix condition number with extended Lanczos bidiagonalization (2015)
- Gower, Robert M.; Richtárik, Peter: Randomized iterative methods for linear systems (2015)
- Kostić, Vladimir R.; Miȩdlar, Agnieszka; Stolwijk, Jeroen J.: On matrix nearness problems: distance to delocalization (2015)
Further publications can be found at: http://math.nist.gov/MatrixMarket/bib.html