Skip to content

This repository provides a GPU implementation of the Partial Least Squares (PLS) algorithm.

Notifications You must be signed in to change notification settings

arturjordao/PLSGPU

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

14 Commits
 
 
 
 
 
 
 
 

Repository files navigation

PLSGPU

This repository provides a GPU implementation of the Partial Least Squares (PLS) algorithm.

Requirements

Quick Start

main.py provides an example of usage of the PLS GPU. Currently, we do not implement the learning stage, therefore, you need to learn a PLS model using scikit-learn (which is performed in CPU). By experiments, we note that for a small number of samples (for example., 100) the CPU version is slightly faster. According to the figure, our GPU implementation of PLS achieves considerable speed-up compared to the CPU version.

Parameters

Our PLSGPU takes two parameters:

  1. A PLS model learnt from scikit-learn.
  2. Batch size. This parameter controls the number of samples sent to GPU.

About

This repository provides a GPU implementation of the Partial Least Squares (PLS) algorithm.

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages