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 402 articles )

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  1. Alonso, Pedro; Ibáñez, Javier; Sastre, Jorge; Peinado, Jesús; Defez, Emilio: Efficient and accurate algorithms for computing matrix trigonometric functions (2017)
  2. Harizanov, Stanislav; Lirkov, Ivan; Georgiev, Krassimir; Paprzycki, Marcin; Ganzha, Maria: Performance analysis of a parallel algorithm for restoring large-scale CT images (2017)
  3. Abdelfattah, A.; Anzt, H.; Dongarra, J.; Gates, M.; Haidar, A.; Kurzak, J.; Luszczek, P.; Tomov, S.; Yamazaki, I.; YarKhan, A.: Linear algebra software for large-scale accelerated multicore computing (2016)
  4. Chohra, Chemseddine; Langlois, Philippe; Parello, David: Efficiency of reproducible level 1 BLAS (2016)
  5. Hager, William W.; Zhang, Hongchao: Projection onto a polyhedron that exploits sparsity (2016)
  6. Jessup, Elizabeth; Motter, Pate; Norris, Boyana; Sood, Kanika: Performance-based numerical solver selection in the Lighthouse framework (2016)
  7. Rashedi, Somaiyeh; Ebadi, Ghodrat; Birk, Sebastian; Frommer, Andreas: On short recurrence Krylov type methods for linear systems with many right-hand sides (2016)
  8. Takahashi, Toru; Shimba, Yuta; Isakari, Hiroshi; Matsumoto, Toshiro: An efficient blocking M2L translation for low-frequency fast multipole method in three dimensions (2016)
  9. Zacate, Matthew O.; Evenson, William E.: Stochastic hyperfine interactions modeling library -- version 2 (2016)
  10. Barlow, Jesse L.: Block Gram-Schmidt downdating (2015)
  11. Bosner, Nela: Efficient algorithm for simultaneous reduction to the $m$-Hessenberg-triangular-triangular form (2015)
  12. Kolberg, Mariana; Bohlender, Gerd; Fernandes, Luiz Gustavo: An efficient approach to solve very large dense linear systems with verified computing on clusters. (2015)
  13. Nassif, Nabil; Erhel, Jocelyne; Philippe, Bernard: Introduction to computational linear algebra (2015)
  14. Nelson, Thomas; Belter, Geoffrey; Siek, Jeremy G.; Jessup, Elizabeth; Norris, Boyana: Reliable generation of high-performance matrix algebra (2015)
  15. Röhrig-Zöllner, Melven; Thies, Jonas; Kreutzer, Moritz; Alvermann, Andreas; Pieper, Andreas; Basermann, Achim; Hager, Georg; Wellein, Gerhard; Fehske, Holger: Increasing the performance of the Jacobi-Davidson method by blocking (2015)
  16. Vannieuwenhoven, Nick; Meerbergen, Karl; Vandebril, Raf: Computing the gradient in optimization algorithms for the CP decomposition in constant memory through tensor blocking (2015)
  17. Van Zee, Field G.; van de Geijn, Robert A.: BLIS: a framework for rapidly instantiating BLAS functionality (2015)
  18. Willenbring, James M.: Replicated computational results (RCR) report for “BLIS: a framework for rapidly instantiating BLAS functionality” (2015)
  19. Carpentieri, Bruno; Liao, Jia; Sosonkina, Masha: VBARMS: a variable block algebraic recursive multilevel solver for sparse linear systems (2014)
  20. Di Napoli, Edoardo; Fabregat-Traver, Diego; Quintana-Ortí, Gregorio; Bientinesi, Paolo: Towards an efficient use of the BLAS library for multilinear tensor contractions (2014)

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