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Bitpit

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Scientific computing software library
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bitpit
Stable release1.9.0 / December 31st 2023
Repository
Written inC++
Operating systemLinux
Typesimulation software
LicenseGNU Lesser General Public License
Websitehttp://bitpit.it

bitpit is an open source modular library for scientific computing. The goal of bitpit is to ease the burden of writing scientific programs providing the common building blocks needed by every scientific application.

Each module of the bitpit library is developed to address a specific aspect of real-life application development. Modules can be used as building blocks to quickly develop a high-performance scientific application. The library consists of several modules ranging from low level functionalities like algebraic operators to high level functionalities like the evaluation of distance functions on computational meshes.

Features and modules

Features and the modules of bitpit include:

See also

References

  1. H. Telib, bitpit: a numerical sandpit for bridging scientific computing and industrial applications, Abstract, SISSA Trieste, Tuesday, 23 September 2014
  2. M. Cisternino, A. Iollo, L. Weynans, A. Colin, P. Poulin. Electrostrictive materials: modelling and simulation , in: 7 th European Congress on Computational Methods in Applied Sciences and Engineering, Hersonissos, Greece, ECCOMAS, June 2016. Abstract
  3. M. Cisternino, E. Lombardi, PABLO - Open source PArallel Balanced Linear Octree, an industrial tool for scientific computing. JDEV 2015, Bordeaux, France. Poster
  4. H.Telib, M. Cisternino, V. Ruggiero, F. Bernard, RAPHI: Rarefied Flow Simulations on Xeon Phi Architecture, SHAPE White Papers, PRACE Download
  5. Project Team MEMPHIS - INRIA, Activity Report 2016, Bordeaux,France. Paper
  6. A. Raeli, A. Azaïez, M. Bergmann, A. Iollo. Numerical Modelling for Phase Change Materials. CANUM, May 2016, Obernai, France. Presentation
  7. F. Tesser, Discretization of the Laplacian operator using a multitude of overlapping cartesian grids, Sessions, EuroSciPy 2016, Erlangen, Germany
  8. F. Bernard, A. Iollo, S. Riffaud. Reduced-order model for the BGK equation based on POD and optimal transport, Journal of Computational Physics, Elsevier, 2018, 373, pp.545-570
  9. F. Bernard, A. Iollo, G. Puppo. BGK Polyatomic Model for Rarefied Flows, Journal of Scientific Computing, Springer Verlag, 2019, 78(3)
  10. E. Abbate, A. Iollo, G. Puppo. An asymptotic-preserving all-speed scheme for fluid dynamics and non linear elasticity, SIAM Journal on Scientific Computing, Society for Industrial and Applied Mathematics, 2019

External links

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