SPARSKIT

SPARSKIT: A basic toolkit for sparse matrix computations This paper presents the main features of a tool package for manipulating and working with sparse matrices. One of the goals of the package is to provide basic tools to facilitate exchange of software and data between researchers in sparse matrix computations. Our starting point is the Harwell/Boeing collection of matrices for which we provide a number of tools. Among other things the package provides programs for converting data structures, printing simple statistics on a matrix, plotting a matrix pro le, performing basic linear algebra operations with sparse matrices and so on


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  1. Capilla, M. T.; Talavera, C. F.; Ginestar, D.; Verdú, G.: Validation of the SHNC time-dependent transport code based on the spherical harmonics method for complex nuclear fuel assemblies (2020)
  2. Dansou, Anicet; Mouhoubi, Saïda; Chazallon, Cyrille: Optimizations of a fast multipole symmetric Galerkin boundary element method code (2020)
  3. Dansou, Anicet; Mouhoubi, Saïda; Chazallon, Cyrille; Bonnet, Marc: Modeling multicrack propagation by the fast multipole symmetric Galerkin BEM (2019)
  4. Gómez, Pablo; Zanzi, Claudio; López, Joaquín; Hernández, Julio: Simulation of high density ratio interfacial flows on cell vertex/edge-based staggered octree grids with second-order discretization at irregular nodes (2019)
  5. Özgün, Özlem; Kuzuoğlu, Mustafa: MATLAB-based finite element programming in electromagnetic modeling (2019)
  6. Ghasemi, Maryam; Eberl, Hermann J.: Time adaptive numerical solution of a highly degenerate diffusion-reaction biofilm model based on regularisation (2018)
  7. Ghasemi, Maryam; Hense, Burkhard A.; Eberl, Hermann J.; Kuttler, Christina: Simulation-based exploration of quorum sensing triggered resistance of biofilms to antibiotics (2018)
  8. Sanderson, Conrad; Curtin, Ryan: A user-friendly hybrid sparse matrix class in C++ (2018)
  9. Tan, Guangming; Liu, Junhong; Li, Jiajia: Design and implementation of adaptive SpMV library for multicore and many-core architecture (2018)
  10. Yang, Chang; Claustre, Jonathan; Deluzet, Fabrice: Iterative solvers for elliptic problems with arbitrary anisotropy strengths (2018)
  11. Gupta, Anshul: Enhancing performance and robustness of ILU preconditioners by blocking and selective transposition (2017)
  12. Hyndman, Rob J.; Lee, Alan J.; Wang, Earo: Fast computation of reconciled forecasts for hierarchical and grouped time series (2016)
  13. Il’in, V. P.; Skopin, I. N.: About performance and intellectuality of supercomputer modeling (2016) ioport
  14. Shoele, Kourosh; Mittal, Rajat: Energy harvesting by flow-induced flutter in a simple model of an inverted piezoelectric flag (2016)
  15. Corsaro, S.; Marazzina, D.; Marino, Z.: A parallel wavelet-based pricing procedure for Asian options (2015)
  16. Janna, Carlo; Castelletto, Nicola; Ferronato, Massimiliano: The effect of graph partitioning techniques on parallel block FSAI preconditioning: a computational study (2015)
  17. Porcelli, Margherita; Binante, Vincenzo; Girardi, Maria; Padovani, Cristina; Pasquinelli, Giuseppe: A solution procedure for constrained eigenvalue problems and its application within the structural finite-element code NOSA-ITACA (2015)
  18. Salkuyeh, Davod Khojasteh; Rafiei, Amin; Roohani, Hadi: ILU preconditioning based on the FAPINV algorithm (2015)
  19. Ştefănescu, R.; Sandu, A.; Navon, I. M.: POD/DEIM reduced-order strategies for efficient four dimensional variational data assimilation (2015)
  20. Abdel-Rehim, A. M.; Stathopoulos, Andreas; Orginos, Kostas: Extending the eigCG algorithm to nonsymmetric Lanczos for linear systems with multiple right-hand sides. (2014)

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