GPUMLib

GPU 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.

Features

Multiple Back-Propagation (MBP)
Back-Propagation (BP)
Radial Basis Functions (RBF)
Non-Negative Matrix Factorization (NMF)
Semi-Supervised Non-Negative Matrix Factorization (SSNMF)
Restricted Boltzmann Machines (RBM)
Deep Belief Networks (DBN)
Autonomous Training System (ATS)
Support Vector Machines (SVM)
Self Organizing Maps (SOM)

Project Samples

Project Activity

See All Activity >

License

GNU General Public License version 3.0 (GPLv3)

Follow GPUMLib

GPUMLib Web Site

Other Useful Business Software

Enterprise-grade ITSM, for every business

Give your IT, operations, and business teams the ability to deliver exceptional services—without the complexity.

Freshservice is an intuitive, AI-powered platform that helps IT, operations, and business teams deliver exceptional service without the usual complexity. Automate repetitive tasks, resolve issues faster, and provide seamless support across the organization. From managing incidents and assets to driving smarter decisions, Freshservice makes it easy to stay efficient and scale with confidence.

Try it Free

Rate This Project

User Reviews

Be the first to post a review of GPUMLib!

Additional Project Details

Intended Audience

Science/Research, Education, Developers, Engineering

User Interface

.NET/Mono, Console/Terminal, Qt

Programming Language

C#, C++

Related Categories

C# Machine Learning Software, C++ Machine Learning Software

Registered

2010-02-22

Similar Business Software

Torch

Torch is a scientific computing framework with wide support for machine learning algorithms that puts GPUs first. It is easy to use and efficient, thanks to an easy and fast scripting language, LuaJIT, and an underlying C/CUDA implementation. The goal of Torch is to have maximum flexibility and...

See Software
Ray

Develop on your laptop and then scale the same Python code elastically across hundreds of nodes or GPUs on any cloud, with no changes. Ray translates existing Python concepts to the distributed setting, allowing any serial application to be easily parallelized with minimal code changes. Easily...

See Software
Amazon SageMaker Model Training

Amazon SageMaker Model Training reduces the time and cost to train and tune machine learning (ML) models at scale without the need to manage infrastructure. You can take advantage of the highest-performing ML compute infrastructure currently available, and SageMaker can automatically scale...

See Software