BLAS

Low-level utilities common to many mathematical software packages. Primarily the Fortran BLAS (Basic Linear Algebra Subroutines) collected together by level (1, 2 and 3) and precision (real, double, complex, double complex). Also includes specialized BLAS implementations, the PORT machine-dependent constant routines, and the MACHAR software for dynamically determining machine-dependent arithmetic properties


References in zbMATH (referenced in 462 articles )

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  1. Amestoy, Patrick R.; L’Excellent, Jean-Yves; Moreau, Gilles: On exploiting sparsity of multiple right-hand sides in sparse direct solvers (2019)
  2. Fung, Samy Wu; Ruthotto, Lars: A multiscale method for model order reduction in PDE parameter estimation (2019)
  3. Rodríguez-Sánchez, Rafael; Catalán, Sandra; Herrero, José R.; Quintana-Ortí, Enrique S.; Tomás, Andrés E.: Look-ahead in the two-sided reduction to compact band forms for symmetric eigenvalue problems and the SVD (2019)
  4. Dongarra, Jack; Gates, Mark; Haidar, Azzam; Kurzak, Jakub; Luszczek, Piotr; Tomov, Stanimire; Yamazaki, Ichitaro: The singular value decomposition: anatomy of optimizing an algorithm for extreme scale (2018)
  5. Duersch, Jed A.; Shao, Meiyue; Yang, Chao; Gu, Ming: A robust and efficient implementation of LOBPCG (2018)
  6. Harlim, John; Yang, Haizhao: Diffusion forecasting model with basis functions from QR-decomposition (2018)
  7. Huang, Jianyu; Matthews, Devin A.; van de Geijn, Robert A.: Strassen’s algorithm for tensor contraction (2018)
  8. Matthews, Devin A.: High-performance tensor contraction without transposition (2018)
  9. Aliaga, José I.; Carratalá-Sáez, Rocío; Quintana-Ortí, Enrique S.: Parallel solution of hierarchical symmetric positive definite linear systems (2017)
  10. Alonso, Pedro; Ibáñez, Javier; Sastre, Jorge; Peinado, Jesús; Defez, Emilio: Efficient and accurate algorithms for computing matrix trigonometric functions (2017)
  11. Belonosov, Mikhail; Dmitriev, Maxim; Kostin, Victor; Neklyudov, Dmitry; Tcheverda, Vladimir: An iterative solver for the 3D Helmholtz equation (2017)
  12. Bosner, Nela; Karlsson, Lars: Parallel and heterogeneous (m)-Hessenberg-triangular-triangular reduction (2017)
  13. Figueras, Jordi-Lluís; de la Llave, Rafael: Numerical computations and computer assisted proofs of periodic orbits of the Kuramoto-Sivashinsky equation (2017)
  14. Gentle, James E.: Matrix algebra. Theory, computations and applications in statistics (2017)
  15. Glinskiy, Boris; Kuchin, Nikolay; Kostin, Victor; Solovyev, Sergey: Parallel computations for solving 3D Helmholtz problem by using direct solver with low-rank approximation and HSS technique (2017)
  16. Gupta, Anshul: Enhancing performance and robustness of ILU preconditioners by blocking and selective transposition (2017)
  17. Harizanov, Stanislav; Lirkov, Ivan; Georgiev, Krassimir; Paprzycki, Marcin; Ganzha, Maria: Performance analysis of a parallel algorithm for restoring large-scale CT images (2017)
  18. Huismann, Immo; Stiller, Jörg; Fröhlich, Jochen: Factorizing the factorization -- a spectral-element solver for elliptic equations with linear operation count (2017)
  19. Ji, Hao; Li, Yaohang: Block conjugate gradient algorithms for least squares problems (2017)
  20. Kutepov, A. L.; Oudovenko, V. S.; Kotliar, G.: Linearized self-consistent quasiparticle GW method: application to semiconductors and simple metals (2017)

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