GPU-Accelerated Libraries

NVIDIA CUDA-X™, built on NVIDIA CUDA®, is a collection of libraries, tools, and technologies 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 GPU accelerate computational lithography and the manufacturing of semiconductors

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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.


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

Complete set of application programming interfaces, samples, and documentation for hardware-accelerated video encode and decode on Windows and Linux

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NVIDIA Optical Flow SDK

Exposes 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.



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

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NVIDIA Collective Communication Library (NCCL)


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

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Deep Learning Libraries

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


GPU-accelerated library of primitives for deep neural networks

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

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Platform for developing engaging and contextual AI-powered conversation apps

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Real-time streaming analytics toolkit for AI-based video understanding and multi-sensor processing

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

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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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Get Started

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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