The open-source serverless GPU container runtime.
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Updated
Jun 2, 2024 - Go
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.
The open-source serverless GPU container runtime.
A high-throughput and memory-efficient inference and serving engine for LLMs
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
CUDA C++ Core Libraries
A retargetable MLIR-based machine learning compiler and runtime toolkit.
Sandbox for graphics paper implementation
OneDiff: An out-of-the-box acceleration library for diffusion models.
High-Performance Cross-Platform Monte Carlo Renderer Based on LuisaCompute
Drop-in, local AI alternative to the OpenAI stack. Multi-engine (llama.cpp, TensorRT-LLM). Powers 👋 Jan
High-Performance Rendering Framework on Stream Architectures
High Performance Monodomain program for cardiac eletrophysiology simulations.
Containers for machine learning
Convolutional Neural Network inference library running on CUDA
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.
An animal can do training and inference every day of its existence until the day of its death. A forward pass is all you need.
PyTorch/TorchScript/FX compiler for NVIDIA GPUs using TensorRT
Some general algorithms implemented in cuda.
FlashInfer: Kernel Library for LLM Serving
Graphics Processing Units Molecular Dynamics
Created by Nvidia
Released June 23, 2007