Gpu Acceleration
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An end-to-end open source platform for machine learning with a comprehensive ecosystem of tools and libraries.
An end-to-end open source platform for machine learning with a comprehensive ecosystem of tools and libraries.
A Python package for tensor computation with GPU acceleration and dynamic neural networks built on a tape-based autograd system.
A web UI and optimization library for running and fine-tuning open-source AI models locally with 2x faster training and 70% less VRAM.
A fast, feature-rich, cross-platform terminal emulator with native UI and GPU acceleration, plus an embeddable library.
A library for efficient similarity search and clustering of dense vectors, scaling to billions of vectors on a single server.
A PyTorch wrapper that automates engineering boilerplate for scalable AI model training and deployment.
A deep learning framework to pretrain and finetune any AI model at any scale with zero code changes.
A lightweight tool to run container runtimes like Docker, Containerd, and Incus on macOS and Linux with minimal setup.
A high-performance serving framework for large language models and multimodal models, delivering low-latency and high-throughput inference.
A flexible and efficient deep learning framework that mixes symbolic and imperative programming for heterogeneous distributed systems.
A flexible and efficient deep learning framework that mixes symbolic and imperative programming for heterogeneous distributed systems.
A flexible and efficient deep learning framework that mixes symbolic and imperative programming for heterogeneous distributed systems.
An open-source iOS framework for GPU-accelerated image and video processing using OpenGL ES 2.0.
A hardware-accelerated JavaScript library for training and deploying machine learning models in browsers and Node.js.
A hardware-accelerated JavaScript library for training and deploying machine learning models in the browser and Node.js.
A fast, distributed gradient boosting framework based on decision tree algorithms for ranking, classification, and other machine learning tasks.
A fast, distributed gradient boosting framework based on decision tree algorithms for ranking, classification, and other ML tasks.
A unified deep learning toolkit for describing neural networks as computational graphs, supporting feed-forward DNNs, CNNs, and RNNs/LSTMs.
A deprecated wrapper that enabled Docker containers to access NVIDIA GPU resources.
A comprehensive open-source toolkit for speech recognition research and development.
GPU-accelerated neural network library for JavaScript, running in browsers and Node.js.
An open-source library for rapid development of software dealing with 3D data, with support for C++ and Python.
An advanced offline password cracker supporting hundreds of hash and cipher types across multiple platforms.
NVIDIA's SDK for high-performance deep learning inference optimization and deployment on NVIDIA GPUs.
A differentiable computer vision library for PyTorch, providing geometric vision and image processing algorithms for AI workflows.
A GPU-accelerated DataFrame library for tabular data processing, part of the RAPIDS data science suite.
A scientific computing framework with wide support for machine learning algorithms, built around multi-dimensional tensor operations.
A high-performance gradient boosting library with best-in-class handling of categorical features and support for CPU/GPU training.
WebGL-accelerated machine learning library for JavaScript with linear algebra and automatic differentiation.
A hardware-accelerated GPU terminal emulator that runs on desktops and in web browsers.
A flexible Python deep learning framework using define-by-run dynamic computational graphs for neural network research.
Efficient image captioning code in Torch, using a CNN-RNN model to generate captions for images, optimized for GPU training.
A suite of GPU-accelerated machine learning algorithms with scikit-learn compatible APIs for 10-50x faster performance on large datasets.
A PyTorch library providing GPU-accelerated tools for 3D deep learning, including differentiable rendering and geometric operations.
A Swift framework for GPU-accelerated image and video processing on iOS, macOS, and Linux.
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