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☆50,864Updated this week
- World's fastest and most advanced password recovery utility☆22,920Updated this week
- Build and run Docker containers leveraging NVIDIA GPUs☆17,392Updated last year
- Instant neural graphics primitives: lightning fast NeRF and more☆16,705Updated this week
- kaldi-asr/kaldi is the official location of the Kaldi project.☆14,941Updated 2 months ago
- SGLang is a fast serving framework for large language models and vision language models.☆15,567Updated this week
- Open3D: A Modern Library for 3D Data Processing☆12,475Updated this week
- CUDA on non-NVIDIA GPUs☆11,567Updated this week
- Burn is a next generation Deep Learning Framework that doesn't compromise on flexibility, efficiency and portability.☆11,416Updated this week
- Solve puzzles. Learn CUDA.☆11,180Updated 10 months ago
- NumPy aware dynamic Python compiler using LLVM☆10,492Updated last week
- NumPy & SciPy for GPU☆10,293Updated this week
- cuDF - GPU DataFrame Library☆9,011Updated this week
- Containers for machine learning☆8,685Updated this week
- OneFlow is a deep learning framework designed to be user-friendly, scalable and efficient.☆9,156Updated 2 weeks ago
- A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other ma…☆8,442Updated this week
- Modular ZK(Zero Knowledge) backend accelerated by GPU☆7,762Updated 7 months ago
- CUDA Templates for Linear Algebra Subroutines☆7,754Updated this week
- Samples for CUDA Developers which demonstrates features in CUDA Toolkit☆7,655Updated last month
- Go package for computer vision using OpenCV 4 and beyond. Includes support for DNN, CUDA, OpenCV Contrib, and OpenVINO.☆7,111Updated last month
- 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.☆5,664Updated last month
- ALIEN is a CUDA-powered artificial life simulation program.☆5,187Updated this week
- A Python framework for accelerated simulation, data generation and spatial computing.☆5,238Updated this week
- [ARCHIVED] The C++ parallel algorithms library. See https://github.com/NVIDIA/cccl☆4,974Updated last year
- A PyTorch Library for Accelerating 3D Deep Learning Research☆4,808Updated 2 weeks ago
- cuML - RAPIDS Machine Learning Library☆4,796Updated this week
- ArrayFire: a general purpose GPU library.☆4,729Updated this week
- Tengine is a lite, high performance, modular inference engine for embedded device☆4,474Updated 3 months ago
- Ecosystem of libraries and tools for writing and executing fast GPU code fully in Rust.☆4,488Updated last month
- 📚LeetCUDA: Modern CUDA Learn Notes with PyTorch for Beginners🐑, 200+ CUDA/Tensor Cores Kernels, HGEMM, FA-2 MMA.🎉☆5,101Updated this week
- Lightning fast C++/CUDA neural network framework☆4,086Updated last week
- HIP: C++ Heterogeneous-Compute Interface for Portability☆4,096Updated this week
- Making it easier to work with shaders☆4,175Updated this week
- Fast inference engine for Transformer models☆3,884Updated 2 months ago
- LightSeq: A High Performance Library for Sequence Processing and Generation☆3,279Updated 2 years ago
- Single C file, Realtime CPU/GPU Profiler with Remote Web Viewer☆3,234Updated 10 months ago
- Jittor is a high-performance deep learning framework based on JIT compiling and meta-operators.☆3,176Updated 2 weeks ago
- A retargetable MLIR-based machine learning compiler and runtime toolkit.☆3,197Updated this week
- A GPU-powered real-time analytics storage and query engine.☆3,055Updated 11 months ago