NVIDIA Documentation Hub

The integration of NVIDIA RAPIDS into the Cloudera Data Platform (CDP) provides transparent GPU acceleration of data analytics workloads using Apache Spark. This documentation describes the integration and suggested reference architectures for deployment.

This documentation should be of interest to cluster admins and support personnel of enterprise GPU deployments. It includes monitoring and management tools and application programming interfaces (APIs), in-field diagnostics and health monitoring, and cluster setup and deployment.

The MONAI framework is the open-source foundation being created by Project MONAI. MONAI is a freely available, community-supported, PyTorch-based framework for deep learning in healthcare imaging. It provides domain-optimized foundational capabilities for developing healthcare imaging training workflows in a native PyTorch paradigm.

End-to-end networking solutions with smart adapters, switches, cables, and management software that reduce latency, increase efficiency, enhance security, and simplify data center automation so applications run faster.

The NVIDIA BlueField® data processing unit (DPU) ignites unprecedented innovation for modern data centers and supercomputing infrastructures. By offloading, accelerating, and isolating a broad range of advanced networking, storage, and security services, BlueField DPUs provide a secure and accelerated infrastructure for any workload, in any environment, from cloud to data center to edge.

The NVIDIA® Mellanox® LinkX® product family of cables and transceivers provides the industry's most complete line of 10, 25, 40, 50, 100, 200, and 400GbE in Ethernet and EDR, HDR, and NDR in InfiniBand products for Cloud, HPC, Web 2.0, Enterprise, telco, storage and artificial intelligence, data center applications.

Manuals of NIC Drivers, FW, Accelerators, Switch OS, Management, Tools for Networking.

NVIDIA Networking Solutions Labs is glad to provide a set of Reference Deployment Guides (RDGs), HOW-TOs and Configuration manuals. These documents allow for easy experimentation with and deployment of advanced data center workloads, such as Machine Learning, Big Data, Cloud and Containerized workloads, Telecom and others using NVIDIA Networking cutting edge technologies. Our RDGs cover all aspects of the solution including Bill of Materials, SW/HW/Network components design, step by step installation and configuration, application deployment, and performance benchmarks.

InfiniBand and Ethernet switch solutions for accelerating the data center, HPC, AI, industrial and scientific applications.

nvCOMP is a high performance GPU enabled data compression library. Includes both open-source and non-OS components. The nvCOMP library provides fast lossless data compression and decompression using a GPU. It features generic compression interfaces to enable developers to use high-performance GPU compressors in their applications.

NVIDIA AI Enterprise is a software suite that enables organizations to harness the power of AI, even if they don’t have AI expertise today. Optimized to streamline AI development and deployment, NVIDIA AI Enterprise includes proven, open-sourced containers and frameworks which are certified to run on common data center platforms from VMware and Red Hat, NVIDIA Certified servers configured with GPUs or CPU only, and on the public cloud.

NVIDIA Ansel is a revolutionary way to capture in-game shots and share the moment. Compose your screenshots from any position, adjust them with post-process filters, capture HDR images in high-fidelity formats, and share them in 360 degrees using your mobile phone, PC, or VR headset.

NVIDIA Base Command Platform is a world-class infrastructure solution for businesses and their data scientists who need a premium AI development experience.

NVIDIA Bright Cluster Manager offers fast deployment and end-to-end management for heterogeneous HPC and AI server clusters at the edge, in the data center and in multi/hybrid-cloud environments. It automates provisioning and administration for clusters ranging in size from a single node to hundreds of thousands, supports CPU-based and NVIDIA GPU-accelerated systems, and orchestration with Kubernetes.

NVIDIA Capture SDK (formerly GRID SDK) enables developers to easily and efficiently capture, and optionally encode, the display content.

NVIDIA® Clara™ is an open, scalable computing platform that enables developers to build and deploy medical imaging applications into hybrid (embedded, on-premises, or cloud) computing environments to create intelligent instruments and automate healthcare workflows.

NVIDIA cloud-native technologies enable developers to build and run GPU-accelerated containers using Docker and Kubernetes.

CloudXR is NVIDIA's solution for streaming virtual reality (VR), augmented reality (AR), and mixed reality (MR) content from any OpenVR XR application on a remote server--desktop, cloud, data center, or edge.

Compute Sanitizer is a functional correctness checking suite included in the CUDA toolkit. This suite contains multiple tools that can perform different type of checks. The memcheck tool is capable of precisely detecting and attributing out of bounds and misaligned memory access errors in CUDA applications. The tool can also report hardware exceptions encountered by the GPU. The racecheck tool can report shared memory data access hazards that can cause data races. The initcheck tool can report cases where the GPU performs uninitialized accesses to global memory. The synccheck tool can report cases where the application is attempting invalid usages of synchronization primitives. This document describes the usage of these tools.

The NVIDIA® CUDA® Toolkit provides a comprehensive development environment for C and C++ developers building GPU-accelerated applications. With the CUDA Toolkit, you can develop, optimize, and deploy your applications on GPU-accelerated embedded systems, desktop workstations, enterprise data centers, cloud-based platforms and HPC supercomputers. The toolkit includes GPU-accelerated libraries, debugging and optimization tools, a C/C++ compiler, and a runtime library to deploy your application.

The NVIDIA® CUDA Deep Neural Network (cuDNN) library is a GPU-accelerated library of primitives for deep neural networks. cuDNN provides highly tuned implementations for standard routines such as forward and backward convolution, pooling, normalization, and activation layers. Deep learning researchers and framework developers worldwide rely on cuDNN for high-performance GPU acceleration.

NVIDIA cuOpt is an Operations Research optimization API using AI to help developers create complex, real-time fleet routing workflows on NVIDIA GPUs.

The NVIDIA Data Loading Library (DALI) is a collection of highly optimized building blocks, and an execution engine, for accelerating the pre-processing of input data for deep learning applications. DALI provides both the performance and the flexibility for accelerating different data pipelines as a single library. This single library can then be easily integrated into different deep learning training and inference applications.

NVIDIA Data Center GPU drivers are used in Data Center GPU enterprise deployments for AI, HPC, and accelerated computing workloads. Documentation includes release notes, supported platforms, and cluster setup and deployment.

NVIDIA Data Center GPU Manager (DCGM) is a suite of tools for managing and monitoring NVIDIA Data Center GPUs in cluster environments.

NVIDIA Data Science Workbench is a productivity tool for GPU-enabled workstations to improve manageability, reproducibility, and usability for data scientists, data engineers, and AI developers. Users have fast and convenient access to a plethora of data science tools and CLIs while also benefiting from easy installation and updating stack software.

Deep Graph Library (DGL) is a framework-neutral, easy-to-use, and scalable Python library used for implementing and training Graph Neural Networks (GNN). Being framework-neutral, DGL is easily integrated into an existing PyTorch, TensorFlow, or an Apache MXNet workflow.

GPUs accelerate machine learning operations by performing calculations in parallel. Many operations, especially those representable as matrix multipliers will see good acceleration right out of the box. Even better performance can be achieved by tweaking operation parameters to efficiently use GPU resources. The performance documents present the tips that we think are most widely useful.

NVIDIA DGX is the integrated software and hardware system that supports the commitment to AI research with an optimized combination of compute power, software, and deep learning performance. It is purpose-built to meet the demands of enterprise AI and data science, delivering the fastest start in AI development, effortless productivity, and revolutionary performance—for insights in hours instead of months.

The NVIDIA Deep Learning GPU Training System (DIGITS) can be used to rapidly train highly accurate deep neural networks (DNNs) for image classification, segmentation, and object-detection tasks. DIGITS simplifies common deep learning tasks such as managing data, designing and training neural networks on multi-GPU systems, monitoring performance in real time with advanced visualizations, and selecting the best-performing model from the results browser for deployment.

Learn how to develop for NVIDIA DRIVE®, a scalable computing platform that enables automakers and Tier-1 suppliers to accelerate production of autonomous vehicles.

The NVIDIA EGX platform delivers the power of accelerated AI computing to the edge with a cloud-native software stack (EGX stack), a range of validated servers and devices, Helm charts, and partners who offer EGX through their products and services.

FLARE (Federated Learning Active Runtime Environment) is Nvidia’s open source extensible SDK that allows researchers and data scientists to adapt existing ML/DL workflow to a privacy preserving federated paradigm. FLARE makes it possible to build robust, generalizable AI models without sharing data.

NVIDIA Fleet Command brings secure edge AI to enterprises of any size. Transform NVIDIA-certified servers into secure edge appliances and connect them to the cloud in minutes. From the cloud, deploy and manage applications from the NGC Catalog or your NGC Private Registry, update system software over-the-air and manage systems remotely with nothing but a browser and internet connection.

Documentation for GameWorks-related products and technologies, including libraries (NVAPI, OpenAutomate), code samples (DirectX, OpenGL), and developer tools (Nsight, NVIDIA System Profiler).

The GeForce NOW Developer Platform is an SDK and toolset empowering integration of, interaction with, and testing on the NVIDIA cloud gaming service.

NVIDIA GPUDirect Storage (GDS) enables the fastest data path between GPU memory and storage by avoiding copies to and from system memory, thereby increasing storage input/output (IO) bandwidth and decreasing latency and CPU utilization.

NVIDIA GVDB Voxels is a new framework for simulation, compute and rendering of sparse voxels on the GPU.

NVIDIA Highlights enables automatic video capture of key moments, clutch kills, and match-winning plays, ensuring gamers’ best gaming moments are always saved. Once a Highlight is captured, gamers can simply share it directly to Facebook, YouTube, or Weibo right from GeForce Experience’s in-game overlay. Additionally, they can also clip their favorite 15 seconds and share as an animated GIF - all without leaving the game!

The NVIDIA HPC SDK is a comprehensive suite of compilers, libraries, and development tools used for developing HPC applications for the NVIDIA platform.

NVIDIA IndeX is a 3D volumetric interactive visualization SDK that allows scientists and researchers to visualize and interact with massive data sets, make real-time modifications, and navigate to the most pertinent parts of the data, all in real-time, to gather better insights faster. IndeX leverages GPU clusters for scalable, real-time, visualization and computing of multi-valued volumetric data together with embedded geometry data.

NVIDIA Isaac is a developer toolbox for accelerating the development and deployment of AI-powered robots. The SDK includes Isaac applications, GEMs (robot capabilities), a Robot Engine, and NVIDIA Isaac Sim.

The NVIDIA JetPack SDK, which is the most comprehensive solution for building AI applications, along with L4T and L4T Multimedia, provides the Linux kernel, bootloader, NVIDIA drivers, flashing utilities, sample filesystem, and more for the Jetson platform.

NVIDIA LaunchPad is a free program that provides users short-term access to a large catalog of hands-on labs. Now enterprises and organizations can immediately tap into the necessary hardware and software stacks to experience end-to-end solution workflows in the areas of AI, data science, 3D design collaboration and simulation, and more.

ibcu++, the NVIDIA C++ Standard Library, provides a C++ Standard Library for your entire system which can be used in and between CPU and GPU code.

NVIDIA® License System is used to serve a pool of floating licenses to NVIDIA licensed products. The NVIDIA License System is configured with licenses obtained from the NVIDIA Licensing Portal.

NVIDIA MAGNUM IO™ software development kit (SDK) enables developers to remove input/output (IO) bottlenecks in AI, high performance computing (HPC), data science, and visualization applications, reducing the end-to-end time of their workflows. Magnum IO covers all aspects of data movement between CPUs, GPUsns, DPUs, and storage subsystems in virtualized, containerized, and bare-metal environments.

The NVIDIA Material Definition Language (MDL) is a programming language for defining physically based materials for rendering. The MDL SDK is a set of tools to integrate MDL support into rendering applications. It contains components for loading, inspecting, editing of material definitions as well as compiling MDL functions to GLSL, HLSL, Native x86, PTX and LLVM-IR. With the NVIDIA MDL SDK, any physically based renderer can easily add support for MDL and join the MDL eco-system.

NVIDIA Maxine is a GPU-accelerated SDK with state-of-the-art AI features for developers to build virtual collaboration and content creation applications such as video conferencing and live streaming. Maxine’s AI SDKs, such as Video Effects, Audio Effects, and Augmented Reality (AR) are highly optimized and include modular features that can be chained into end-to-end pipelines to deliver the highest performance possible on GPUs, both on PCs and in data centers.

NVIDIA Merlin™ empowers data scientists, machine learning engineers, and researchers to build high-performing recommenders at scale. Merlin includes tools that democratize the building of deep learning recommenders by addressing common extract, transform, load (ETL), training, and inference challenges. Each stage of the pipeline is optimized to support hundreds of terabytes of data, all accessible through easy-to-use APIs. With Merlin, better predictions and increased click-through rates are within reach

NVIDIA® Clara™ is an open, scalable computing platform that enables developers to build and deploy medical imaging applications into hybrid (embedded, on-premises, or cloud) computing environments to create intelligent instruments and automate healthcare workflows.

Warp and Blend are interfaces exposed in NVAPI for warping (image geometry corrections) and blending (intensity and black level adjustment) a single display output or multiple display outputs.

NVIDIA Highlights enables automatic video capture of key moments, clutch kills, and match-winning plays, ensuring gamers’ best gaming moments are always saved. Once a Highlight is captured, gamers can simply share it directly to Facebook, YouTube, or Weibo right from GeForce Experience’s in-game overlay. Additionally, they can also clip their favorite 15 seconds and share as an animated GIF - all without leaving the game!

NVIDIA PhysX is a scalable multi-platform physics simulation solution supporting a wide range of devices, from smartphones to high-end multicore CPUs and GPUs. The powerful SDK brings high-performance and precision accuracy to industrial simulation use cases from traditional VFX and game development workflows, to high-fidelity robotics, medical simulation, and scientific visualization applications.

NVIDIA Networking Solutions Labs is glad to provide a set of Reference Deployment Guides (RDGs), HOW-TOs and Configuration manuals. These documents allow for easy experimentation with and deployment of advanced data center workloads, such as Machine Learning, Big Data, Cloud and Containerized workloads, Telecom and others using NVIDIA Networking cutting edge technologies. Our RDGs cover all aspects of the solution including Bill of Materials, SW/HW/Network components design, step by step installation and configuration, application deployment, and performance benchmarks.

Compute Sanitizer is a functional correctness checking suite included in the CUDA toolkit. This suite contains multiple tools that can perform different type of checks. The memcheck tool is capable of precisely detecting and attributing out of bounds and misaligned memory access errors in CUDA applications. The tool can also report hardware exceptions encountered by the GPU. The racecheck tool can report shared memory data access hazards that can cause data races. The initcheck tool can report cases where the GPU performs uninitialized accesses to global memory. The synccheck tool can report cases where the application is attempting invalid usages of synchronization primitives. This document describes the usage of these tools.

NVIDIA Triton Inference Server (formerly TensorRT Inference Server) provides a cloud inferencing solution optimized for NVIDIA GPUs. The server provides an inference service via an HTTP or gRPC endpoint, allowing remote clients to request inferencing for any model being managed by the server.

NVIDIA Maxine is a GPU-accelerated SDK with state-of-the-art AI features for developers to build virtual collaboration and content creation applications such as video conferencing and live streaming. Maxine’s AI SDKs, such as Video Effects, Audio Effects, and Augmented Reality (AR) are highly optimized and include modular features that can be chained into end-to-end pipelines to deliver the highest performance possible on GPUs, both on PCs and in data centers.

NVIDIA LaunchPad is a free program that provides users short-term access to a large catalog of hands-on labs. Now enterprises and organizations can immediately tap into the necessary hardware and software stacks to experience end-to-end solution workflows in the areas of AI, data science, 3D design collaboration and simulation, and more.

The GeForce NOW Developer Platform is an SDK and toolset empowering integration of, interaction with, and testing on the NVIDIA cloud gaming service.

VRWorks™ is a comprehensive suite of APIs, libraries, and engines that enable application and headset developers to create amazing virtual reality experiences. VRWorks enables a new level of presence by bringing physically realistic visuals, sound, touch interactions, and simulated environments to virtual reality.

Documentation for GameWorks-related products and technologies, including libraries (NVAPI, OpenAutomate), code samples (DirectX, OpenGL), and developer tools (Nsight, NVIDIA System Profiler).

End-to-end networking solutions with smart adapters, switches, cables, and management software that reduce latency, increase efficiency, enhance security, and simplify data center automation so applications run faster.

NVIDIA cuOpt is an Operations Research optimization API using AI to help developers create complex, real-time fleet routing workflows on NVIDIA GPUs.

NVIDIA Data Center GPU Manager (DCGM) is a suite of tools for managing and monitoring NVIDIA Data Center GPUs in cluster environments.

NVIDIA Neural Modules (NeMo) is a flexible, Python-based toolkit enabling data scientists and researchers to build state-of-the-art speech and language deep learning models composed of reusable building blocks that can be safely connected together for conversational AI applications.

NVIDIA GVDB Voxels is a new framework for simulation, compute and rendering of sparse voxels on the GPU.

NVIDIA AI Enterprise is a software suite that enables organizations to harness the power of AI, even if they don’t have AI expertise today. Optimized to streamline AI development and deployment, NVIDIA AI Enterprise includes proven, open-sourced containers and frameworks which are certified to run on common data center platforms from VMware and Red Hat, NVIDIA Certified servers configured with GPUs or CPU only, and on the public cloud.

NVIDIA Optimized Frameworks such as Kaldi, NVIDIA Optimized Deep Learning Framework (powered by Apache MXNet), NVCaffe, PyTorch, and TensorFlow (which includes DLProf and TF-TRT) offer flexibility with designing and training custom (DNNs for machine learning and AI applications.

NVIDIA MAGNUM IO™ software development kit (SDK) enables developers to remove input/output (IO) bottlenecks in AI, high performance computing (HPC), data science, and visualization applications, reducing the end-to-end time of their workflows. Magnum IO covers all aspects of data movement between CPUs, GPUsns, DPUs, and storage subsystems in virtualized, containerized, and bare-metal environments.

NVIDIA DGX is the integrated software and hardware system that supports the commitment to AI research with an optimized combination of compute power, software, and deep learning performance. It is purpose-built to meet the demands of enterprise AI and data science, delivering the fastest start in AI development, effortless productivity, and revolutionary performance—for insights in hours instead of months.

The NVIDIA® CUDA® Toolkit provides a comprehensive development environment for C and C++ developers building GPU-accelerated applications. With the CUDA Toolkit, you can develop, optimize, and deploy your applications on GPU-accelerated embedded systems, desktop workstations, enterprise data centers, cloud-based platforms and HPC supercomputers. The toolkit includes GPU-accelerated libraries, debugging and optimization tools, a C/C++ compiler, and a runtime library to deploy your application.

Whether you want to see your work across multiple displays or project your ideas in 4K, you can with NVIDIA Mosaic™ multi-display technology. With NVIDIA Mosaic, you can easily span any application across up to 16 high-resolution panels or projectors from a single system, conveniently treating the multiple displays as a single desktop, without application software changes or visual artifacts.

The integration of NVIDIA RAPIDS into the Cloudera Data Platform (CDP) provides transparent GPU acceleration of data analytics workloads using Apache Spark. This documentation describes the integration and suggested reference architectures for deployment.

NVIDIA GPUDirect Storage (GDS) enables the fastest data path between GPU memory and storage by avoiding copies to and from system memory, thereby increasing storage input/output (IO) bandwidth and decreasing latency and CPU utilization.

The NVIDIA TAO Toolkit eliminates the time-consuming process of building and fine-tuning DNNs from scratch for IVA applications.

The NVIDIA Collective Communications Library (NCCL) is a library of multi-GPU collective communication primitives that are topology-aware and can be easily integrated into applications. Collective communication algorithms employ many processors working in concert to aggregate data. NCCL is not a full-blown parallel programming framework; rather, it’s a library focused on accelerating collective communication primitives.

Manuals of NIC Drivers, FW, Accelerators, Switch OS, Management, Tools for Networking.

NVIDIA Morpheus is an open AI application framework that provides cybersecurity developers with a highly optimized AI pipeline and pre-trained AI capabilities and allows them to instantaneously inspect all IP traffic across their data center fabric.

NVIDIA Data Center GPU drivers are used in Data Center GPU enterprise deployments for AI, HPC, and accelerated computing workloads. Documentation includes release notes, supported platforms, and cluster setup and deployment.

NVIDIA SDK Manager is an all-in-one tool that bundles developer software and provides an end-to-end development environment setup solution for NVIDIA SDKs. Learn about the prerequisite hardware and software to get started with NVIDIA SDK Manager. See the latest features and updates.

UCF is a fully accelerated framework for developing real-time edge AI applications.

NVIDIA’s program that enables enterprises to confidently deploy hardware solutions that optimally run accelerated workloads—from desktop to data center to edge.

NVIDIA Ansel is a revolutionary way to capture in-game shots and share the moment. Compose your screenshots from any position, adjust them with post-process filters, capture HDR images in high-fidelity formats, and share them in 360 degrees using your mobile phone, PC, or VR headset.

InfiniBand and Ethernet switch solutions for accelerating the data center, HPC, AI, industrial and scientific applications.

NVIDIA Omniverse is a cloud-native, multi-GPU, real-time simulation and collaboration platform for 3D production pipelines based on Pixar's Universal Scene Description (USD) and NVIDIA RTX.

NVIDIA® License System is used to serve a pool of floating licenses to NVIDIA licensed products. The NVIDIA License System is configured with licenses obtained from the NVIDIA Licensing Portal.

FLARE (Federated Learning Active Runtime Environment) is Nvidia’s open source extensible SDK that allows researchers and data scientists to adapt existing ML/DL workflow to a privacy preserving federated paradigm. FLARE makes it possible to build robust, generalizable AI models without sharing data.

Transformer Engine (TE) is a library for accelerating Transformer models on NVIDIA GPUs to provide better performance with lower memory utilization in both training and inference, and an FP8 automatic-mixed-precision-like API that can be used seamlessly with your model code.

Create block-compressed textures and write custom asset pipelines using NVTT 3, an SDK for CUDA-accelerated texture compression and image processing.

The NVIDIA BlueField® data processing unit (DPU) ignites unprecedented innovation for modern data centers and supercomputing infrastructures. By offloading, accelerating, and isolating a broad range of advanced networking, storage, and security services, BlueField DPUs provide a secure and accelerated infrastructure for any workload, in any environment, from cloud to data center to edge.

NVIDIA cloud-native technologies enable developers to build and run GPU-accelerated containers using Docker and Kubernetes.

NVIDIA Base Command Platform is a world-class infrastructure solution for businesses and their data scientists who need a premium AI development experience.

NVIDIA Topology-Aware GPU Selection (NVTAGS) intelligently and automatically assigns GPUs to MPI processes, which reduces overall GPU-to-GPU communication time for Message Passing Interface (MPI) applications.

Unique IP-based solution that boosts video and data streaming performance. Rivermax together with NVIDIA GPU accelerated computing technologies unlocks innovation for a wide range of applications in Media and Entertainment (M&E), Broadcast, Healthcare, Smart Cities and more.

The NVIDIA Virtual Reality Capture and Replay (VCR) SDK enables developers and users to accurately capture and replay VR sessions for performance testing, scene troubleshooting, and more.

NVIDIA Nsight Developer Tools is a comprehensive tool suite spanning across desktop and mobile targets which enable developers to build, debug, profile, and develop class-leading and cutting-edge software that utilizes the latest visual computing hardware from NVIDIA.

OpenACC is a directive-based programming model designed to provide a simple yet powerful approach to accelerators without significant programming effort. With OpenACC, a single version of the source code will deliver performance portability across the platforms. OpenACC offers scientists and researchers a quick path to accelerated computing with less programming effort. By inserting compiler “hints” or directives into your C11, C++17 or Fortran 2003 code, with the NVIDIA OpenACC compiler you can offload and run your code on the GPU and CPU.

NVIDIA NGC is the hub for GPU-optimized software for deep learning, machine learning, and HPC that provides containers, models, model scripts, and industry solutions so data scientists, developers and researchers can focus on building solutions and gathering insights faster.