PyOpenCL

PyOpenCL gives you easy, Pythonic access to the OpenCL parallel computation API. Object cleanup tied to lifetime of objects. This idiom, often called RAII in C++, makes it much easier to write correct, leak- and crash-free code. Completeness. PyOpenCL puts the full power of OpenCL’s API at your disposal, if you wish. Every obscure get_info() query and all CL calls are accessible. Automatic Error Checking. All errors are automatically translated into Python exceptions. Speed. PyOpenCL’s base layer is written in C++, so all the niceties above are virtually free. Helpful Documentation. You’re looking at it. ;) Liberal license. PyOpenCL is open-source under the MIT license and free for commercial, academic, and private use.


References in zbMATH (referenced in 26 articles )

Showing results 1 to 20 of 26.
Sorted by year (citations)

1 2 next

  1. Gräf, Manuel; Neumayer, Sebastian; Hielscher, Ralf; Steidl, Gabriele; Liesegang, Moritz; Beck, Tilmann: An image registration model in electron backscatter diffraction (2022)
  2. Habring, Andreas; Holler, Martin: A generative variational model for inverse problems in imaging (2022)
  3. Amos Egel, Krzysztof M. Czajkowski, Dominik Theobald, Konstantin Ladutenko, Alexey S. Kuznetsov, Lorenzo Pattelli: SMUTHI: A python package for the simulation of light scattering by multiple particles near or between planar interfaces (2021) arXiv
  4. B. Boys, T. J. Dodwell, M. Hobbs, M. Girolami: PeriPy - A High Performance OpenCL Peridynamics Package (2021) arXiv
  5. Boys, B.; Dodwell, T. J.; Hobbs, M.; Girolami, M.: PeriPy -- a high performance peridynamics package (2021)
  6. Li, Xue; Schiavazzi, Daniele E.: An ensemble solver for segregated cardiovascular FSI (2021)
  7. Ramachandran, Prabhu; Bhosale, Aditya; Puri, Kunal; Negi, Pawan; Muta, Abhinav; Dinesh, A.; Menon, Dileep; Govind, Rahul; Sanka, Suraj; Sebastian, Amal S.; Sen, Ananyo; Kaushik, Rohan; Kumar, Anshuman; Kurapati, Vikas; Patil, Mrinalgouda; Tavker, Deep; Pandey, Pankaj; Kaushik, Chandrashekhar; Dutt, Arkopal; Agarwal, Arpit: PySPH: a Python-based framework for smoothed particle hydrodynamics (2021)
  8. Victor Couty, Jean-François Witz, Pauline Lecomte-Grosbras, Julien Berthe, Eric Deletombe, Mathias Brieu: GPUCorrel: A GPU accelerated Digital Image Correlation software written in Python (2021) not zbMATH
  9. Y. Dallilar, S. von Fellenberg, M. Bauböck, P.T. de Zeeuw, A. Drescher, F. Eisenhauer, R. Genzel, S. Gillessen, M. Habibi, T. Ott, G. Ponti, J. Stadler, O. Straub, F. Widmann, G. Witzel, A. Young: Flaremodel: An open-source Python package for one-zone numerical modelling of synchrotron sources (2021) arXiv
  10. Pfister, Luke; Bhargava, Rohit; Bresler, Yoram; Carney, P. Scott: Composition-aware spectroscopic tomography (2020)
  11. Seyoon Ko, Hua Zhou, Jin Zhou, Joong-Ho Won: DistStat.jl: Towards Unified Programming for High-Performance Statistical Computing Environments in Julia (2020) arXiv
  12. Chekrygin, I. I.; Faraonov, A. A.: Statistcal analysis of geophysical signals with the use of parallel calculations (2019)
  13. Essadki, Mohamed; Jung, Jonathan; Larat, Adam; Pelletier, Milan; Perrier, Vincent: A task-driven implementation of a simple numerical solver for hyperbolic conservation laws (2018)
  14. Jyh-Miin Lin: Python Non-Uniform Fast Fourier Transform (PyNUFFT): multi-dimensional non-Cartesian image reconstruction package for heterogeneous platforms and applications to MRI (2017) arXiv
  15. Hornikx, Maarten; Krijnen, Thomas; van Harten, Louis: openPSTD: the open source pseudospectral time-domain method for acoustic propagation (2016)
  16. Merrison-Hort, Robert: Fireflies: new software for interactively exploring dynamical systems using GPU computing (2015)
  17. Witherden, F. D.; Vermeire, B. C.; Vincent, P. E.: Heterogeneous computing on mixed unstructured grids with pyfr (2015)
  18. Cooper, Christopher D.; Bardhan, Jaydeep P.; Barba, L. A.: A biomolecular electrostatics solver using python, GPUs and boundary elements that can handle solvent-filled cavities and stern layers (2014)
  19. Cottet, G.-H.; Etancelin, J.-M.; Perignon, F.; Picard, C.: High order semi-Lagrangian particle methods for transport equations: numerical analysis and implementation issues (2014)
  20. Januszewski, M.; Kostur, M.: Sailfish: a flexible multi-GPU implementation of the lattice Boltzmann method (2014)

1 2 next