CUDA (Compute Unified Device Architecture) is a parallel computing platform and application programming interface (API) model created by NVIDIA for general computing on its own GPUs (Graphics Processing Units). It empowers application developers to leverage the parallel processing capabilities of NVIDIA's GPUs to accelerate computation-heavy tasks, such as matrix operations, physics simulations, deep learning training, and real-time video processing. CUDA provides a C-like programming language that allows developers to write kernel functions, which are executed on the GPU, and manage memory between the host (CPU) and device (GPU) environments. Utilizing CUDA can lead to significant performance improvements in suitable applications, and it integrates well with various programming environments, including Python through libraries like PyCUDA or through frameworks like TensorFlow with GPU support. Understanding basic concepts such as kernels, threads, blocks, and warps is essential for developers to effectively harness the power of GPU programming with CUDA.
View the most prominent open source CUDA projects in the list below. Click on a specific project to view its alternative or complementary packages. Make comparisons and find the best package for your app.
- A high-throughput and memory-efficient inference and serving engine for LLMs☆55,787Updated this week
- World's fastest and most advanced password recovery utility☆23,977Updated this week
- Build and run Docker containers leveraging NVIDIA GPUs☆17,412Updated last year
- SGLang is a fast serving framework for large language models and vision language models.☆16,953Updated this week
- Instant neural graphics primitives: lightning fast NeRF and more☆16,847Updated 3 weeks ago
- kaldi-asr/kaldi is the official location of the Kaldi project.☆15,051Updated 3 weeks ago
- CUDA on non-NVIDIA GPUs☆12,916Updated this week
- Open3D: A Modern Library for 3D Data Processing☆12,678Updated this week
- Burn is a next generation Deep Learning Framework that doesn't compromise on flexibility, efficiency and portability.☆12,604Updated this week
- Solve puzzles. Learn CUDA.☆11,372Updated 11 months ago
- TensorRT-LLM provides users with an easy-to-use Python API to define Large Language Models (LLMs) and support state-of-the-art optimizati…☆11,365Updated this week
- NumPy aware dynamic Python compiler using LLVM☆10,582Updated this week
- NumPy & SciPy for GPU☆10,426Updated this week
- OneFlow is a deep learning framework designed to be user-friendly, scalable and efficient.☆9,361Updated this week
- cuDF - GPU DataFrame Library☆9,125Updated this week
- Containers for machine learning☆8,776Updated this week
- A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other ma…☆8,521Updated this week
- CUDA Templates for Linear Algebra Subroutines☆8,249Updated last week
- Samples for CUDA Developers which demonstrates features in CUDA Toolkit☆7,962Updated 2 weeks ago
- Modular ZK(Zero Knowledge) backend accelerated by GPU☆7,760Updated 8 months ago
- Go package for computer vision using OpenCV 4 and beyond. Includes support for DNN, CUDA, OpenCV Contrib, and OpenVINO.☆7,184Updated 2 weeks ago
- 📚LeetCUDA: Modern CUDA Learn Notes with PyTorch for Beginners🐑, 200+ CUDA Kernels, Tensor Cores, HGEMM, FA-2 MMA.🎉☆6,127Updated this week
- A flexible framework of neural networks for deep learning☆5,909Updated last year
- An interactive NVIDIA-GPU process viewer and beyond, the one-stop solution for GPU process management.☆5,895Updated this week
- A Python framework for accelerated simulation, data generation and spatial computing.☆5,422Updated this week
- ALIEN is a CUDA-powered artificial life simulation program.☆5,220Updated this week
- [ARCHIVED] The C++ parallel algorithms library. See https://github.com/NVIDIA/cccl☆4,984Updated last year
- cuML - RAPIDS Machine Learning Library☆4,874Updated this week
- A PyTorch Library for Accelerating 3D Deep Learning Research☆4,866Updated last week
- Supercharge Your LLM with the Fastest KV Cache Layer☆4,693Updated this week
- ArrayFire: a general purpose GPU library.☆4,757Updated 3 weeks ago
- Ecosystem of libraries and tools for writing and executing fast GPU code fully in Rust.☆4,633Updated this week
- Tengine is a lite, high performance, modular inference engine for embedded device☆4,487Updated 5 months ago
- Making it easier to work with shaders☆4,423Updated this week
- Lightning fast C++/CUDA neural network framework☆4,181Updated this week
- HIP: C++ Heterogeneous-Compute Interface for Portability☆4,156Updated this week
- Fast inference engine for Transformer models☆3,965Updated 4 months ago
- FlashInfer: Kernel Library for LLM Serving☆3,571Updated this week
- Simple, scalable AI model deployment on GPU clusters☆3,369Updated this week
- A retargetable MLIR-based machine learning compiler and runtime toolkit.☆3,301Updated this week