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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.
High-performance TensorFlow library for quantitative finance.
Where the GPU for the Web work happens!
ArrayFire: a general purpose GPU library.
A .NET library to run C# code in parallel on the GPU through DX12, D2D1, and dynamically generated HLSL compute and pixel shaders, with the goal of making GPU computing easy to use for all .NET developers! 🚀
ILGPU JIT Compiler for high-performance .Net GPU programs
A C++ GPU Computing Library for OpenCL
ThunderSVM: A Fast SVM Library on GPUs and CPUs
An efficient C++20 GPU numerical computing library with Python-like syntax
stdgpu: Efficient STL-like Data Structures on the GPU
Fast Clojure Matrix Library
Robotics with GPU computing
Thin, unified, C++-flavored wrappers for the CUDA APIs
⚡ Datoviz: high-performance GPU rendering for scientific data visualization
ThunderGBM: Fast GBDTs and Random Forests on GPUs
Exascale multiphase flow solver — 2025 Gordon Bell Prize Finalist | 200T grid points on 43K+ GPUs
High-performance Bayesian Data Analysis on the GPU in Clojure
Vulkan compute for people
CEED Library: Code for Efficient Extensible Discretizations
Open source math and physics engine that executes MATLAB-syntax code. Features a modern compiler, automatic GPU acceleration for large calculations, and support for math on geometry / FEA calculations.
Kubernetes operator for self-hosted LLM inference across a heterogeneous GPU fleet: NVIDIA CUDA, AMD Vulkan, and Apple Silicon Metal. Runtimes: llama.cpp, vLLM, TGI, mlx-server. Multi-GPU sharding, model caching, OpenAI-compatible endpoints. Apache-2.0, run across homelab and on-prem fleets, actively developed.