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

Non-negative matrix factorization

Project Activity

See All Activity >

Categories

Machine Learning

License

GNU General Public License version 3.0 (GPLv3)

Follow GPUMLib

GPUMLib Web Site

Other Useful Business Software
Host LLMs in Production With On-Demand GPUs Icon
Host LLMs in Production With On-Demand GPUs

NVIDIA L4 GPUs. 5-second cold starts. Scale to zero when idle.

Deploy your model, get an endpoint, pay only for compute time. No GPU provisioning or infrastructure management required.
Start Free
Rate This Project
Login To Rate This Project

User Reviews

Be the first to post a review of GPUMLib!

Additional Project Details

Intended Audience

Developers, Education, Engineering, Science/Research

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
Report inappropriate content