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.

Developer documentation for Megatron Core covers API documentation, quickstart guide as well as deep dives into advanced GPU techniques needed to optimize LLM performance at scale.

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 Aerial™ is a suite of accelerated computing platforms, software, and services for designing, simulating, and operating wireless networks. Aerial contains hardened RAN software libraries for telcos, cloud service providers (CSPs), and enterprises building commercial 5G networks. Academic and industry researchers can access Aerial on cloud or on-premises setups for advanced wireless and AI/machine learning (ML) research for 6G.

NVIDIA AI Enterprise is an end-to-end, cloud-native software platform that accelerates data science pipelines and streamlines development and deployment of production-grade co-pilots and other generative AI applications. Easy-to-use microservices provide optimized model performance with enterprise-grade security, support, and stability to ensure a smooth transition from prototype to production for enterprises that run their businesses on AI.

A simulation platform that allows users to model data center deployments with full software functionality, creating a digital twin. Transform and streamline network operations by simulating, validating, and automating changes and updates.

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.

Your guide to NVIDIA APIs including NIM and CUDA-X microservices.

The NVIDIA Attestation Suite enhances Confidential Computing by providing robust mechanisms to ensure the integrity and security of devices and platforms. The suite includes NVIDIA Remote Attestation Service (NRAS), the Reference Integrity Manifest (RIM) Service, and the NDIS OCSP Responder.

NVIDIA Base Command Manager streamlines cluster provisioning, workload management, and infrastructure monitoring. It provides all the tools you need to deploy and manage an AI data center. NVIDIA Base Command Manager Essentials comprises the features of NVIDIA Base Command Manager that are certified for use with NVIDIA AI Enterprise.

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

NVIDIA Base OS implements the stable and fully qualified operating systems for running AI, machine learning, and analytics applications on the DGX platform. It includes system-specific configurations, drivers, and diagnostic and monitoring tools and is available for Ubuntu, Red Hat Enterprise Linux, and Rocky Linux.

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

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.

Serverless API to deploy and manage AI workloads on GPUs at planetary scale.

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 NVIDIA CUDA® Deep Neural Network (cuDNN) 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, attention, matmul, pooling, and normalization.

NVIDIA cuOpt™ is a GPU-accelerated solver that uses heuristics and metaheuristics to solve complex vehicle routing problem variants with a wide range of constraints.

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.

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 Cloud is an AI platform for enterprise developers, optimized for the demands of generative AI.

Built from the ground up for enterprise AI, the NVIDIA DGX platform incorporates the best of NVIDIA software, infrastructure, and expertise in a modern, unified AI development and training solution. Every aspect of the DGX platform is infused with NVIDIA AI expertise, featuring world-class software, record-breaking NVIDIA-accelerated infrastructure in the cloud or on-premises, and direct access to NVIDIA DGXPerts to speed the ROI of AI for every enterprise.

Deployment and management guides for NVIDIA DGX SuperPOD, an AI data center infrastructure platform that enables IT to deliver performance—without compromise—for every user and workload. DGX SuperPOD offers leadership-class accelerated infrastructure and agile, scalable performance for the most challenging AI and high-performance computing (HPC) workloads, with industry-proven results.

System documentation for the DGX AI supercomputers that deliver world-class performance for large generative AI and mainstream AI workloads.

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.

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.

NVIDIA’s accelerated computing, visualization, and networking solutions are expediting the speed of business outcomes. NVIDIA’s experts are here for you at every step in this fast-paced journey. With our expansive support tiers, fast implementations, robust professional services, market-leading education, and high caliber technical certifications, we are here to help you achieve success with all parts of NVIDIA’s accelerated computing, visualization, and networking platform.

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.

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.

Grace is NVIDIA’s first datacenter CPU. Comprising 72 high-performance Arm v9 cores and featuring the NVIDIA-proprietary Scalable Coherency Fabric (SCF) network-on-chip for incredible core-to-core communication, memory bandwidth and GPU I/O capabilities, Grace provides a high-performance compute foundation in a low-power system-on-chip.

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!

NVIDIA Holoscan is a hybrid computing platform for medical devices that combines hardware systems for low-latency sensor and network connectivity, optimized libraries for data processing and AI, and core microservices to run surgical video, ultrasound, medical imaging, and other applications anywhere, from embedded to edge to cloud.

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

NVIDIA IGX Orin™ is an industrial-grade platform that combines enterprise-level hardware, software, and support. As a single, holistic platform, IGX allows companies to focus on application development and realize the benefits of AI faster.

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 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.

NVIDIA cuOpt™ is a GPU-accelerated solver that uses heuristics and metaheuristics to solve complex vehicle routing problem variants with a wide range of constraints.

Discover a faster, easier way to build advanced AI robotics applications with the NVIDIA Isaac™ ROS collection of accelerated computing packages and AI models, bringing NVIDIA-acceleration to ROS developers everywhere.

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.