https://github.com/dnouri/gnumpy

A distutils package for gnumpy and npmat
https://github.com/dnouri/gnumpy

Last synced: 2 months ago
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A distutils package for gnumpy and npmat

• Host: GitHub
• URL: https://github.com/dnouri/gnumpy
• Owner: dnouri
• License: other
• Created: 2012-12-19T23:50:20.000Z (about 12 years ago)
• Default Branch: master
• Last Pushed: 2017-11-10T18:46:06.000Z (about 7 years ago)
• Last Synced: 2024-10-04T13:33:22.698Z (3 months ago)
• Language: Python
• Size: 145 KB
• Stars: 18
• Watchers: 5
• Forks: 6
• Open Issues: 4
• Metadata Files:
  • Readme: README.rst
  • License: LICENSE.txt

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README

        
[This document is a copy of the original.  `The latest version is

available on Tijmen Tieleman's

homepage. `_]

Gnumpy is free software, but if you use it in scientific work that

gets published, you should cite `this tech report

`_ in your

publication.

Documentation: `here

`_.

Do you want to have both the compute power of GPU's and the

programming convenience of Python numpy? Gnumpy + Cudamat will bring

you that.

Gnumpy is a simple Python module that interfaces in a way almost

identical to numpy, but does its computations on your computer's

GPU. See `this example

`_, training an

RBM using Gnumpy.

Gnumpy runs on top of, and therefore requires, the excellent `cudamat

`_ library, written by `Vlad Mnih

`_.

Gnumpy can run in simulation mode: everything happens on the CPU, but

the interface is the same. This can be helpful if you like to write

your programs on your GPU-less laptop before running them on a

GPU-equipped machine. It also allows you to easily test what

performance gain you get from using a GPU. The simulation mode

requires `npmat `_, written

by `Ilya Sutskever `_.  [npmat is

included in this distribution.]

Gnumpy is licensed with a BSD-style license (i.e. it's completely free

to use for everyone, also as a component in commercial software), with

one added note: if you use it for scientific work that gets published,

you must include reference to the Gnumpy tech report in your

publication. For details of the license, see the top of gnumpy.py.

Recent changes:

- 2012-07-25: Bugfix. gnumpy.dot(x, x), when x is a 1-dimensional array, didn't work but now works.

- 2011-06-06: gnumpy.dot() now takes arrays of ndim>2.

- 2011-04-19: Bugfix: several bugs involving zero size arrays were fixed.

- 2011-04-15: Bugfix. "x=gnumpy.zeros(10); x[array([])] = garray([])" didn't work as it should. Now it does.

- 2011-03-24: Added gnumpy.outer().

- 2011-03-15: The ability to check for infs and nans automatically has been added to Gnumpy.

- 2010-07-19: Cudamat now enables fast indexing with arrays of indices. Download the newest Cudamat to have fast indexing with arrays in Gnumpy.

- 2010-07-08: Renamed the project to Gnumpy. It used to be called Gpunnumpy.