#cuda

cuDF - GPU DataFrame Library

A high-throughput and memory-efficient inference and serving engine for LLMs

LMCache: Supercharge Your LLM with the Fastest KV Cache Layer

NVIDIA cuML: GPU-Accelerated Machine Learning

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

NumPy & SciPy for GPU

RAPIDS Memory Manager

Containers for machine learning

SGLang is a high-performance serving framework for large language models and multimodal models.

:metal: TT-NN operator library, and TT-Metalium low level kernel programming model.

FlashInfer: Kernel Library for LLM Serving

PyTorch native quantization and sparsity for training and inference

CUDA Core Compute Libraries

RAFT contains fundamental widely-used algorithms and primitives for machine learning and information retrieval. The algorithms are CUDA-accelerated and form building blocks for more easily writing high performance applications.

A retargetable MLIR-based machine learning compiler and runtime toolkit.

Making it easier to work with shaders

DaCe - Data Centric Parallel Programming

A GPU cluster manager for high-performance AI model serving (vLLM, SGLang) and on-demand SSH-accessible GPU instances.

CUDA Templates and Python DSLs for High-Performance Linear Algebra

Main repository for QMCPACK, an open-source production level many-body ab initio Quantum Monte Carlo code for computing the electronic structure of atoms, molecules, and solids with full performance portable GPU support

An electronic structure package based on either plane wave basis or numerical atomic orbitals.

Open security scanner and self-hosted control plane for AI, MCP, and cloud. One evidence model — run scans in your environment, centralize findings, govern in your VPC.

Burn is a next generation tensor library and Deep Learning Framework that doesn't compromise on flexibility, efficiency and portability.

PyTorch/TorchScript/FX compiler for NVIDIA GPUs using TensorRT