We present a number of application program interfaces (APIs) for coding linear algebra algorithms. On the surface, these APIs for the MATLAB M-script and C programming languages appear to be simple, almost trivial, extensions of those languages. Yet with them, the task of programming and maintaining families of algorithms for a broad spectrum of linear algebra operations is greatly simplified. In combination with our formal linear algebra methods environment (FLAME) approach to deriving such families of algorithms, dozens of algorithms for a single linear algebra operation can be derived, verified to be correct, implemented, and tested, often in a matter of minutes per algorithm. Since the algorithms are expressed in code much like they are explained in a classroom setting, these APIs become not just a tool for implementing libraries, but also a valuable tool for teaching the algorithms that are incorporated in the libraries. In combination with an extension of the parallel linear algebra package (PLAPACK) API, the approach presents a migratory path from algorithm to MATLAB implementation to high-performance sequential implementation to parallel implementation. Finally, the APIs are being used to create a repository of algorithms and implementations for linear algebra operations, the FLAME interface REpository (FIRE), which already features hundreds of algorithms for dozens of commonly encountered linear algebra operations

References in zbMATH (referenced in 39 articles , 2 standard articles )

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  1. D’Alberto, Paolo; Nicolau, Alexandru: Adaptive Winograd’s matrix multiplications (2009)
  2. Deissenberg, Christophe; van der Hoog, Sander; Dawid, Herbert: EURACE: A massively parallel agent-based model of the European economy (2008)
  3. Jin, Haoqiang; Chapman, Barbara; Huang, Lei; Mey, Dieter An; Reichstein, Thomas: Performance evaluation of a multi-zone application in different openmp approaches (2008)
  4. Terrel, A. R.; Scott, L. R.; Knepley, M. G.; Kirby, R. C.: Automated FEM discretizations for the Stokes equation (2008)
  5. Van Zee, Field G.; Bientinesi, Paolo; Low, Tze Meng; van de Geijn, Robert A.: Scalable parallelization of FLAME code via the workqueuing model. (2008)
  6. Barnes, David J.; Hopkins, Tim R.: Improving test coverage of LAPACK (2007)
  7. Anagnostakis, K. G.; Greenwald, M. B.; Ioannidis, S.; Li, D.; Smith, J. M.: Flexible network monitoring with FLAME (2006)
  8. Benner, Peter; Quintana-Ortí, Enrique S.; Quintana-Ortí, Gregorio: Solving stable Sylvester equations via rational iterative schemes (2006)
  9. Tsukerman, Igor: A class of difference schemes with flexible local approximation (2006)
  10. Basermann, Achim; Tsukerman, Igor: Parallel generalized finite element method for magnetic multiparticle problems (2005)
  11. Bientinesi, Paolo; Gunnels, John A.; Myers, Margaret E.; Quintana-Ortí, Enrique S.; van de Geijn, Robert A.: The science of deriving dense linear algebra algorithms (2005)
  12. Bientinesi, Paolo; Quintana-Ortí, Enrique S.; van de Geijn, Robert A.: Representing linear algebra algorithms in code: The FLAME application program interfaces (2005)
  13. Kirby, Robert C.; Knepley, Matthew; Logg, Anders; Scott, L. Ridgway: Optimizing the evaluation of finite element matrices (2005)
  14. Anagnostakis, Kostas G.; Greenwald, Michael; Ioannidis, Sotiris; Miltchev, Stefan: Open packet monitoring on FLAME: Safety, performance, and applications (2002)
  15. Koch, Andreas: Compilation for adaptive computing systems using complex parameterized hardware objects (2002)
  16. Valsalam, Vinod; Skjellum, Anthony: A framework for high-performance matrix multiplication based on hierarchical abstractions, algorithms and optimized low-level kernels (2002)
  17. Gunnels, John A.; Gustavson, Fred G.; Henry, Greg M.; van de Geijn, Robert A.: FLAME: formal linear algebra methods environment (2001)
  18. Neumann, Tilman; Koch, Andreas: A generic library for adaptive computing environments (2001)
  19. Omelchenko, Yu. A.; Sudan, R. N.: A 3-D Darwin-EM hybrid PIC code for ion ring studies (1997)