NVIDIA CUDA-X™ Libraries, built on CUDA®, is a collection of libraries that deliver dramatically higher performance—compared to CPU-only alternatives—across application domains, including AI and high-performance computing.

NVIDIA libraries run everywhere from resource-constrained IoT devices to self-driving cars to the largest supercomputers on the planet. As a result, users receive highly optimized implementations of an ever-expanding set of algorithms. Whether building a new application or accelerating an existing application, developers can tap NVIDIA libraries for the easiest way to get started with GPU acceleration.


Math Libraries

GPU-accelerated math libraries lay the foundation for compute-intensive applications in areas such as molecular dynamics, computational fluid dynamics, computational chemistry, medical imaging, and seismic exploration.

Decorative image of cuBLAS math library


GPU-accelerated basic linear algebra (BLAS) library.

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 Decorative image of cuFFT math library


GPU-accelerated library for Fast Fourier Transform implementations.

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Decorative image of CUDA math library

CUDA Math Library

GPU-accelerated standard mathematical function library.

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Decorative image of cuRAND math library


GPU-accelerated random number generation (RNG).

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Decorative image of cuSOLVER math library


GPU-accelerated dense and sparse direct solvers.

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Decorative image of cuSPARSE math library


GPU-accelerated BLAS for sparse matrices.

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 Decorative image of cuTENSOR math library


GPU-accelerated tensor linear algebra library.

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Decorative image of cuDSS math library


GPU-accelerated direct sparse solver library.

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Decorative image of AmgX math library


GPU-accelerated linear solvers for simulations and implicit unstructured methods.

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Parallel Algorithm Libraries

GPU-accelerated libraries of highly efficient parallel algorithms for several operations in C++ and for use with graphs when studying relationships in natural sciences, logistics, travel planning, and more.


GPU-accelerated library of C++ parallel algorithms and data structures.

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Computational Lithography Library

Targeting the modern-day challenges of nanoscale computational lithography.


Library with optimized tools and algorithms to accelerate computational lithography and the manufacturing of semiconductors using GPUs.

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Data Processing Libraries

GPU-accelerated libraries to accelerate data processing workflows for tabular, text, and image data.


Accelerate pandas with zero code changes.

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Feature engineering and preprocessing library for training recommender systems.

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NeMo Data Curator

Python library for curating natural language processing (NLP) data for training large language models (LLMs).

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RAPIDS cuGraph

Quickly navigate graph analytics libraries with a python API that follows NetworkX.

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Apply cuVS algorithms to accelerate vector search, including world-class performance from CAGRA.

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Open application framework that optimizes cybersecurity AI pipelines for analyzing large volumes of real-time data.

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GPU Direct Storage

NVIDIA GPUDirect® Storage creates a direct data path between local or remote storage, such as NVMe or NVMe over Fabrics (NVMe-oF), and GPU memory.

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Expand data science pipelines to multiple nodes with RAPIDS on Dask.

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RAPIDS Accelerator for Apache Spark

Accelerate your existing Apache Spark applications with minimal code changes.

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Image and Video Libraries

GPU-accelerated libraries for image and video decoding, encoding, and processing that use CUDA and specialized hardware components of GPUs.


Accelerate input/output (IO), computer vision, and image processing of n-dimensional, especially biomedical images.

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Open-source library for high-performance, GPU-accelerated pre- and post-processing in vision AI pipelines.

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Portable, open-source library for decoding and augmenting images and videos to accelerate deep learning applications.

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High-performance GPU-accelerated library for JPEG decoding.

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NVIDIA Performance Primitives

GPU-accelerated image, video, and signal processing functions.

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NVIDIA Video Codec SDK

Hardware-accelerated video encode and decode on Windows and Linux.

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NVIDIA Optical Flow SDK

Exposes the latest hardware capability of NVIDIA GPUs dedicated to computing the relative motion of pixels between images.

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Communication Libraries

Performance-optimized multi-GPU and multi-node communication primitives.

Decorative image of NVSHMEM communication library


OpenSHMEM standard for GPU memory, with extensions for improved performance on GPUs.

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Decorative image of NCCL communication library


Open-source library for fast multi-GPU, multi-node communication that maximizes bandwidth while maintaining low latency.

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Deep Learning Core Libraries

GPU-accelerated libraries for deep learning applications that use CUDA and specialized hardware components of GPUs.


High-performance deep learning inference optimizer and runtime for production deployment.

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GPU-accelerated library of primitives for deep neural networks.

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Partner Libraries


GPU-accelerated open-source library for computer vision, image processing, and machine learning, now supporting real-time operation.

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Open-source multimedia framework with a library of plug-ins for audio and video processing.

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GPU-accelerated open-source library for matrix, signal, and image processing.

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GPU-accelerated linear algebra routines for heterogeneous architectures, by Magma.

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IMSL Fortran Numerical Library

GPU-accelerated open-source Fortran library with functions for math, signal and image processing, and statistics, by RogueWave.

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Library for graph-processing designed specifically for the GPU.

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GPU-accelerated functions for sparse direct solvers, included in the SuiteSparse linear algebra package, authored by Prof.

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Triton Ocean SDK

Real-time visual simulation of oceans, water bodies in games, simulation, and training applications, by Triton.

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Primitives for accelerating imaging applications in medical, industrial, and defense domains.

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View CUDA-X Documentation


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Joing the CUDA-X Community


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Members of the NVIDIA Developer Program get early access to all CUDA library releases and the NVIDIA online bug reporting and feature request system.

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