CUDA® is a parallel computing platform and programming model developed by NVIDIA for general computing on graphical processing units (GPUs). With CUDA, developers are able to dramatically speed up computing applications by harnessing the power of GPUs.
Open3D: A Modern Library for 3D Data Processing
A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.
Modular ZK(Zero Knowledge) backend accelerated by GPU
OneFlow is a deep learning framework designed to be user-friendly, scalable and efficient.
CUDA Templates for Linear Algebra Subroutines
ALIEN is a CUDA-powered artificial life simulation program.
[ARCHIVED] The C++ parallel algorithms library. See https://github.com/NVIDIA/cccl
ArrayFire: a general purpose GPU library.
cuML - RAPIDS Machine Learning Library
Tengine is a lite, high performance, modular inference engine for embedded device
HIP: C++ Heterogeneous-Compute Interface for Portability
Lightning fast C++/CUDA neural network framework
Fast inference engine for Transformer models
LightSeq: A High Performance Library for Sequence Processing and Generation
HeavyDB (formerly OmniSciDB)
CV-CUDA™ is an open-source, GPU accelerated library for cloud-scale image processing and computer vision.
Created by Nvidia
Released June 23, 2007