GPUMLib  0.2.6
GPU Machine Learning Library
GPUMLib Documentation

About GPUMLib

GPUMLib is an open source Graphic Processing Unit Machine Learning Library. This library aims to provide machine learning researchers and practitioners with a high performance library by taking advantage of the GPU enormous computational power. The library is developed in C++ and CUDA.

This version includes the following machine learning algorithms and components (complete and working):

Next version will include:


GPUMLib Download:
GPUMLib Homepage:

Getting Started

Together with the code there is a folder examples, which allows you to use the algorithms. For Windows you can download the executables directly.

Getting Help and Reporting Problems

To get help with GPUMLib or to report a problem please send an email to (Please include GPUMLib keyword in the subject).


The following publications describe work integrated in GPUMLib: Other related articles:

Citing GPUMLib

If you make use of GPUMLib in your work and want to cite GPUMLib (thank you), we would prefer that you would cite the appropriate papers above, since they form the core of GPUMLib.

Release Notes

Release: 0.2.6: Release: 0.2.5: Release: 0.2.4: Release: 0.2.3: Release: 0.2.2: Release: 0.2.1: Release: 0.2.0: Release: 0.1.9: Release: 0.1.8: Release: 0.1.7: Release: 0.1.6: Release: 0.1.5: Release: 0.1.4: Release: 0.1.3: Release: 0.1.2: Release: 0.1.1 implements the following:


Noel Lopes1,2
Bernardete Ribeiro1 (Advisor)
Ricardo Quintas1
João Gonçalves1
Shafaatunnur Hasan3
Siti Mariyam Shamsuddin3

1CISUC - Center for Informatics and Systems of University of Coimbra, Portugal
2IPG - Polytechnic of Guarda, Portugal
3UTM Big Data Centre, Skudai, Johor, Malaysia

If you are interested in join the development teem, please send an email to