Blitz++ library

Blitz++ library moves high-level optimizations out of compilers and into libraries in C++. It was created due to the fact that until recently, C++ lagged behind Fortran’s performance by anywhere from 20% to a factor of ten. The C++ programming language offers many features useful for tackling complex scientific computing problems, but unfortunately, these advanced features came with this hefty performance pricetag. This program presents a possible solution. (Source:

References in zbMATH (referenced in 37 articles )

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  1. Khan, Hamid Hassan; Anwer, Syed Fahad; Hasan, Nadeem; Sanghi, Sanjeev: Development and optimisation of a DNS solver using open-source library for high-performance computing (2021)
  2. Matthews, Devin A.: High-performance tensor contraction without transposition (2018)
  3. Gibbons, Jeremy: Aplicative programming with Naperian functors (2017)
  4. De La Cruz, Luis M.; Ramos, Eduardo: General template units for the finite volume method in box-shaped domains (2016)
  5. Einkemmer, Lukas: A resistive magnetohydrodynamics solver using modern C++ and the Boost library (2016)
  6. Eddelbuettel, Dirk; Sanderson, Conrad: RcppArmadillo: accelerating R with high-performance C++ linear algebra (2014)
  7. Li, Xiang; Zhang, Dongxiao: A backward automatic differentiation framework for reservoir simulation (2014)
  8. Fraguela, Basilio B.; Bikshandi, Ganesh; Guo, Jia; Garzarán, María J.; Padua, David; Von Praun, Christoph: Optimization techniques for efficient HTA programs (2012) ioport
  9. Strzodka, Robert: Data layout optimization for multi-valued containers in opencl (2012) ioport
  10. Carette, Jacques; Kiselyov, Oleg: Multi-stage programming with functors and monads: eliminating abstraction overhead from generic code (2011)
  11. Russell, Francis P.; Mellor, Michael R.; Kelly, Paul H. J.; Beckmann, Olav: DESOLA: an active linear algebra library using delayed evaluation and runtime code generation (2011) ioport
  12. Dadvand, Pooyan; Rossi, Riccardo; Oñate, Eugenio: An object-oriented environment for developing finite element codes for multi-disciplinary applications (2010)
  13. Härdtlein, J.; Pflaum, C.; Linke, A.; Wolters, C. H.: Advanced expression templates programming (2010) ioport
  14. Mebane, D. S.; Wang, J. H.: A general method of solution for the cluster variation method in ionic solids, with application to diffusionless transitions in yttria-stabilized zirconia (2010)
  15. Pirkelbauer, Peter; Parent, Sean; Marcus, Mat; Stroustrup, Bjarne: Dynamic algorithm selection for runtime concepts (2010)
  16. Bastian, P.; Blatt, M.; Dedner, A.; Engwer, C.; Klöfkorn, R.; Kornhuber, R.; Ohlberger, M.; Sander, O.: A generic grid interface for parallel and adaptive scientific computing. II: Implementation and tests in DUNE (2008)
  17. Birkeland, Tore; Sørevik, Tor: Parallel redistribution of multidimensional data (2008)
  18. Abedi, Reza; Chung, Shuo-Heng; Hawker, Morgan A.; Palaniappan, Jayandran; Haber, Robert B.: Modeling evolving discontinuities with spacetime discontinuous Galerkin methods (2007)
  19. Cirak, Fehmi; Cummings, Julian C.: Generic programming techniques for parallelizing and extending procedural finite element programs (2007) ioport
  20. Carette, Jacques: Gaussian elimination: a case study in efficient genericity with MetaOCaml (2006)

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