Gpu Acceleration GitHub Repositories (2026) · Open Source Tools

Free, open-source RAW editor for Linux, Android, Windows and macOS. GPU-accelerated, non-destructive, with masks, HDR merge and local AI.

Open source Python/CUDA C/C++ to SASS/CUDA Binary compiler (previously closed source by nvidia), ~16.5% faster than PyTorch CUDA API in ML tasks, tie PTXAS on ReLU, GeLU, Adam etc. Open for specific kernel optimization that break the existing categories further down into cases as well as architectural innovations.

Free, open-source, 100% offline voice dictation for Linux. Speak and type anywhere via whisper.cpp, Whisper & VOSK engines, GPU-accelerated, works on X11 + Wayland!

Write Java. Run on GPUs. Fast.

A Python framework for GPU-accelerated simulation, robotics, and machine learning.

AI agent builder with a VM at its heart. Every agent gets its own microVM sandbox to install software, run code and use the GPU in. Python, Node.js and Rust.

Tensor Fusion is a state-of-the-art GPU virtualization and pooling solution designed to optimize GPU cluster utilization to its fullest potential.

Heterogeneous GPU Sharing on Kubernetes

AMD's graph optimization engine.

EvoRL is a fully GPU-accelerated framework for Evolutionary Reinforcement Learning, implemented with JAX. It supports Reinforcement Learning (RL), Evolutionary Computation (EC), Evolution-guided Reinforcement Learning (ERL), AutoRL, and seamless integration with GPU-optimized simulation environments.

An end-to-end, GPU-accelerated, and modular platform for building generalized Embodied Intelligence.

Data Parallel Extension for NumPy

An Axum-based Rust web framework with Lean 4-verifiable application kernels that run on servers, bare-metal embedded devices, and GPUs, plus integrated security testing.