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 489 articles )

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  1. Bosner, Nela: Parallel reduction of four matrices to condensed form for a generalized matrix eigenvalue algorithm (2021)
  2. Bosner, Nela: Parallel Prony’s method with multivariate matrix pencil approach and its numerical aspects (2021)
  3. Tobias Schoch: wbacon: Weighted BACON algorithms for multivariate outlier nomination (detection) and robust linear regression (2021) not zbMATH
  4. Bollhöfer, Matthias; Schenk, Olaf; Janalik, Radim; Hamm, Steve; Gullapalli, Kiran: State-of-the-art sparse direct solvers (2020)
  5. Frison, Gianluca; Sartor, Tommaso; Zanelli, Andrea; Diehl, Moritz: The BLAS API of BLASFEO: optimizing performance for small matrices (2020)
  6. Iakymchuk, Roman; Barreda, Maria; Wiesenberger, Matthias; Aliaga, José I.; Quintana-Ortí, Enrique S.: Reproducibility strategies for parallel preconditioned conjugate gradient (2020)
  7. Ji, Hao; Mascagni, Michael; Li, Yaohang: Gaussian variant of Freivalds’ algorithm for efficient and reliable matrix product verification (2020)
  8. Sauk, Benjamin; Ploskas, Nikolaos; Sahinidis, Nikolaos: GPU parameter tuning for tall and skinny dense linear least squares problems (2020)
  9. Van Zee, Field G.: Implementing high-performance complex matrix multiplication via the 1M method (2020)
  10. Yuan, Xinru; Huang, Wen; Absil, P.-A.; Gallivan, Kyle A.: Computing the matrix geometric mean: Riemannian versus Euclidean conditioning, implementation techniques, and a Riemannian BFGS method. (2020)
  11. Amestoy, Patrick R.; de la Kethulle de Ryhove, Sébastien; L’Excellent, Jean-Yves; Moreau, Gilles; Shantsev, Daniil V.: Efficient use of sparsity by direct solvers applied to 3D controlled-source EM problems (2019)
  12. Amestoy, Patrick R.; L’Excellent, Jean-Yves; Moreau, Gilles: On exploiting sparsity of multiple right-hand sides in sparse direct solvers (2019)
  13. Barlow, Jesse L.: Block modified Gram-Schmidt algorithms and their analysis (2019)
  14. Bosse, Torsten: (Almost) matrix-free solver for piecewise linear functions in abs-normal form. (2019)
  15. Bylina, Beata; Bylina, Jarosław: The parallel tiled WZ factorization algorithm for multicore architectures (2019)
  16. De Terán, Fernando; Iannazzo, Bruno; Poloni, Federico; Robol, Leonardo: Nonsingular systems of generalized Sylvester equations: an algorithmic approach. (2019)
  17. Du, Cheng-Han; Chiou, Yih-Peng; Wang, Weichung: Compressed hierarchical Schur algorithm for frequency-domain analysis of photonic structures (2019)
  18. Farzin, Saeed; Fatehi, Rouhollah; Hassanzadeh, Yousef: Position explicit and iterative implicit consistent incompressible SPH methods for free surface flow (2019)
  19. Fung, Samy Wu; Ruthotto, Lars: A multiscale method for model order reduction in PDE parameter estimation (2019)
  20. Lang, Bruno: Efficient reduction of banded Hermitian positive definite generalized eigenvalue problems to banded standard eigenvalue problems (2019)

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