Skip to main content

GPGPU algorithms for PyCUDA and PyOpenCL

Project description

Reikna is a library containing various GPU algorithms built on top of PyCUDA and PyOpenCL. The main design goals are:

  • separation of computation cores (matrix multiplication, random numbers generation etc) from simple transformations on their input and output values (scaling, typecast etc);

  • separation of the preparation and execution stage, maximizing the performance of the execution stage at the expense of the preparation stage (in other words, aiming at large simulations)

  • partial abstraction from CUDA/OpenCL

Tests can be run by installing Py.Test and running py.test from the test folder (run py.test --help to get the list of options).

For more information proceed to the project documentation page. If you have a general question that does not qualify as an issue, you can ask it at the discussion forum.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

reikna-0.6.6.tar.gz (162.0 kB view details)

Uploaded Source

File details

Details for the file reikna-0.6.6.tar.gz.

File metadata

  • Download URL: reikna-0.6.6.tar.gz
  • Upload date:
  • Size: 162.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No

File hashes

Hashes for reikna-0.6.6.tar.gz
Algorithm Hash digest
SHA256 760aa5521d050ac42fe93a2cc892abc08259e6fac0b4989cac6662d9b7adc719
MD5 533759db03a45dcb2a2b73ffc6910273
BLAKE2b-256 08ad532c1230986944e3d3c6221d55311fdf7da8a96ec3d3be8dcf4542cc1d05

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page