Scaling AI-Enabled Robotics Development Workloads with NVIDIA OSMO Summary NVIDIA OSMO is a cloud-native managed service designed to simplify and scale complex robotics development workflows. It allows developers to orchestrate and manage multi-stage, multi-container workflows across heterogeneous compute resources, significantly reducing development cycle times from months to less than a week. This article explores how NVIDIA OSMO can accelerate humanoid robot development by streamlining robot training and simulation workflows. The Challenge of Robotics Development Robotics development is an iterative process involving data generation, model training, and deployment....

Unlocking AI Expertise: NVIDIA GTC 2024 Workshops and Certifications Summary NVIDIA GTC 2024 offers a comprehensive range of workshops and certifications designed to elevate AI expertise. This year’s event includes hands-on technical workshops, training labs, and professional certifications in generative AI and large language models. Here’s a detailed look at what’s new and how you can benefit. New Workshops and Certification NVIDIA GTC 2024 is set to revolutionize AI learning with its latest lineup of workshops and certifications....

Unlocking the Power of CUDA 11.4: Enhanced Performance and Programming Model Summary NVIDIA’s CUDA 11.4 release brings significant improvements to the programming model and performance of CUDA applications. This article delves into the key features and enhancements of CUDA 11.4, including improved CUDA graph launch performance, multi-process service features, and asynchronous programming model updates. Enhanced Programming Model CUDA 11.4 focuses on enhancing the programming model to make it more efficient and user-friendly....

Summary Distributed deep learning has become a crucial aspect of modern data processing pipelines. With the release of Apache Spark 3.4, users now have access to built-in APIs for both distributed model training and model inference at scale. This article explores how Spark 3.4 simplifies distributed deep learning, making it easier to integrate deep learning models into large-scale data processing workflows. Simplifying Distributed Deep Learning with Spark 3.4 Distributed deep learning is a critical component of many modern data processing pipelines....

Migrating to GPU Trace: A Guide to Better Graphics Performance Summary NVIDIA Nsight Graphics offers a powerful toolset for debugging and profiling graphics applications. One of its key features is GPU Trace, a frame-level profiler that provides detailed insights into GPU performance. This article guides developers through the process of migrating from Range Profiler to GPU Trace, highlighting the benefits and improvements of the latter. Introduction Graphics development is becoming increasingly complex, with the need for high-performance rendering and detailed profiling....

Understanding Retrieval-Augmented Generation (RAG): A Comprehensive Guide Summary Retrieval-Augmented Generation (RAG) is a powerful technique that enhances the capabilities of large language models (LLMs) by integrating external knowledge sources. This approach improves the accuracy and relevance of generated responses by grounding them in authoritative data. In this article, we will delve into the basics of RAG, its importance, and how it works, providing a comprehensive understanding of this innovative AI framework....

Summary Harnessing powerful shader insights is crucial for graphics developers aiming to create high-quality visuals. NVIDIA Nsight Graphics offers a robust toolset for debugging and profiling shaders, enabling developers to pinpoint and solve issues efficiently. This article explores how to use shader debug info with NVIDIA Nsight Graphics to gain deeper insights into shader performance. Unlocking Shader Secrets with NVIDIA Nsight Graphics Introduction In the world of graphics development, shaders play a pivotal role in creating stunning visuals....

Unlocking the Future of Computing: Quantum-Accelerated Supercomputing Explained Summary: Quantum-accelerated supercomputing is a revolutionary approach that combines the power of quantum computing with classical high-performance computing to solve complex problems that are beyond the reach of traditional computers. This article provides an in-depth look at the concept, its applications, and the latest advancements in the field. What is Quantum-Accelerated Supercomputing? Quantum-accelerated supercomputing is a hybrid approach that integrates quantum processing units (QPUs) with classical high-performance computing (HPC) systems....

Summary: NVIDIA Holoscan for Media is a software-defined, AI-enabled platform designed to streamline live media application development. It allows developers to build and deploy applications on repurposable, NVIDIA-accelerated, commercial-off-the-shelf hardware, providing a cloud-native architecture that isn’t constrained by dedicated hardware, environments, or locations. This article explores the key benefits and features of NVIDIA Holoscan for Media, highlighting its potential to revolutionize live media production. Building the Future of Live Media NVIDIA Holoscan for Media is transforming the way live media applications are developed and deployed....

Summary Video quality assessment is crucial for ensuring that video content meets the required standards. Traditional metrics like PSNR and SSIM have limitations, leading to the development of more comprehensive metrics like VMAF. This article explores how NVIDIA GPUs can accelerate VMAF calculations using CUDA, significantly improving performance and efficiency. Understanding Video Quality Metrics Video quality metrics are essential tools for evaluating the fidelity of video content. They provide a quantitative measurement to assess the performance of encoders and ensure that video content meets the required standards....