Harwell-Boeing sparse matrix collection

Sparse matrix test problems. We describe the Harwell-Boeing sparse matrix collection, a set of standard test matrices for sparse matrix problems. Our test set comprises problems in linear systems, least squares, and eigenvalue calculations from a wide variety of scientific and engineering disciplines. The problems range from small matrices, used as counter-examples to hypotheses in sparse matrix research, to large test cases arising in large-scale computation. We offer the collection to other researchers as a standard benchmark for comparative studies of algorithms. The procedures for obtaining and using the test collection are discussed. We also describe the guidelines for contributing further test problems to the collection.

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  2. Cipolla, Stefano; Durastante, Fabio; Tudisco, Francesco: Nonlocal pagerank (2021)
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  11. Gonzaga de Oliveira, Sanderson L.; Bernardes, Júnior A. B.; Chagas, Guilherme O.: An evaluation of low-cost heuristics for matrix bandwidth and profile reductions (2018)
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  13. Schlüter, Federico; Strappa, Yanela; Milone, Diego H.; Bromberg, Facundo: Blankets joint posterior score for learning Markov network structures (2018)
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  15. Jacquelin, Mathias; Lin, Lin; Yang, Chao: \textttPselinv-- a distributed memory parallel algorithm for selected inversion, the symmetric case (2017)
  16. Ji, Hao; Li, Yaohang: A breakdown-free block conjugate gradient method (2017)
  17. Stachurski, Andrzej: On a conjugate directions method for solving strictly convex QP problem (2017)
  18. Wei, Wei; Dai, Hua: Implicitly restarted refined partially orthogonal projection method with deflation (2017)
  19. Zhu, Yao; Gleich, David F.; Grama, Ananth: Erasure coding for fault-oblivious linear system solvers (2017)
  20. Gu, Xian-Ming; Huang, Ting-Zhu; Carpentieri, Bruno: BiCGCR2: A new extension of conjugate residual method for solving non-Hermitian linear systems (2016)

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