GPUStats

gpustats is a PyCUDA-based library implementing functionality similar to that present in scipy.stats. It implements a simple framework for specifying new CUDA kernels and extending existing ones. Here is a (partial) list of target functionality:

• Probability density functions (pdfs). These are intended to speed up likelihood calculations in particular in Bayesian inference applications, such as in PyMC
• Random variable generation using CURAND

Requirements

• NumPy
• SciPy
• Working PyCUDA (http://pypi.python.org/pypi/pycuda) installation
• (optional) PyMC, for test suite

Installation and testing

To install, run:

python setup.py install

If you have nose installed, you may run the test suite by running:

import gpustats
    gpustats.test()

Use

import gpustats

Some development guidelines

• Use spaces (4 per indent), not tabs
• Trim whitespace at the end of lines (most text editors will do this for you)
• PEP8-consistent Python style

People

Cliburn Chan cliburn.chan (at) duke.edu Andrew Cron ajc40 (at) stat.duke.edu Jacob Frelinger jacob.frelinger (at) duke.edu Wes McKinney wesmckinn (at) gmail.com Adam Richards adam.richards (at) duke.edu Marc Suchard msuchard (at) ucla.edu Quanli Wang quanli (at) stat.duke.edu Mike West mw (at) stat.duke.edu

Notes

Requires working PyCUDA installation