NVIDIA CUDA-X

GPU-Accelerated Libraries

NVIDIA® CUDA-X, built on top of NVIDIA CUDA®, is a collection of libraries, tools, and technologies that deliver dramatically higher performance—compared to CPU-only alternatives— across multiple application domains, from artificial intelligence (AI) to high performance computing (HPC).

NVIDIA libraries run everywhere from resource-constrained IoT devices, to self-driving cars, to the largest supercomputers on the planet. As a result, you get highly-optimized implementations of an ever-expanding set of algorithms. Whether you’re building a new application or accelerating an existing application, NVIDIA libraries provide 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.


cuBLAS

GPU-accelerated basic linear algebra (BLAS) library

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cuFFT

GPU-accelerated library for Fast Fourier Transforms

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CUDA Math Library

GPU-accelerated standard mathematical function library

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cuRAND

GPU-accelerated random number generation (RNG)

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cuSOLVER

GPU-accelerated dense and sparse direct solvers

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cuSPARSE

GPU-accelerated BLAS for sparse matrices

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cuTENSOR

GPU-accelerated tensor linear algebra library

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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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Image and Video Libraries

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


nvJPEG

High performance GPU-accelerated library for JPEG decoding

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NVIDIA Performance Primitives

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

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NVIDIA Video Codec SDK

A complete set of APIs, samples, and documentation for 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 Turing™ 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.


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 communications that maximizes bandwidth while maintaining low latency.

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Deep Learning Libraries

GPU-accelerated libraries for Deep Learning applications that leverage 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 Jarvis

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 plugins 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, 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 from medical, industrial, and defense domains

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Resources


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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