NVIDIA CUDA-X

GPU-Accelerated Libraries

NVIDIA CUDA-X™, built on 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.


Components



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

cuBLAS

GPU-accelerated basic linear algebra (BLAS) library.


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 Decorative image of cuFFT math library

cuFFT

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

cuRAND

GPU-accelerated random number generation (RNG).


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Decorative image of cuSOLVER math library

cuSOLVER

GPU-accelerated dense and sparse direct solvers.


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Decorative image of cuSPARSE math library

cuSPARSE

GPU-accelerated BLAS for sparse matrices.


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 Decorative image of cuTENSOR math library

cuTENSOR

GPU-accelerated tensor linear algebra library.


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Decorative image of cuDSS math library

cuDSS

GPU-accelerated direct sparse solver library.


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Decorative image of AmgX math library

AmgX

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.


Thrust

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.


cuLitho

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


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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.


CV-CUDA


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


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nvJPEG


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 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

NVSHMEM

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


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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.


NVIDIA cuDNN

GPU-accelerated library of primitives for deep neural networks.


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NVIDIA TensorRT

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


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NVIDIA Riva

Platform for developing engaging and contextual AI-powered conversation apps.


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NVIDIA DeepStream SDK

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


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NVIDIA DALI

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


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Partner Libraries


OpenCV

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


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FFmpeg

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


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ArrayFire

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


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MAGMA

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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Gunrock

Library for graph-processing designed specifically for the GPU.


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CHOLMOD

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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CUVIlib

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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