Get answers to your most pressing questions from NVIDIA technology experts.
Connect With the Experts sessions at GTC 2024 are a unique opportunity to meet in person with the people behind NVIDIA products and research to get your questions answered at an interactive area of the San Jose Convention Center.
Each 50-minute session will give you a chance to ask questions and learn about the latest NVIDIA technologies, including generative AI, LLMs, deep learning, accelerated computing, robotics, data center and cloud, industrial digitalization, and more.
NVIDIA Isaac™ is an autonomous robotics platform built on innovative technologies spanning from the cloud to edge. Bring your questions and challenges to our robotics, simulation, and AI experts, who will be on hand to discuss how Isaac can save time and money on your robotics development.
Stop by to chat with NVIDIA specialists on digital transformation in the automotive industry. Explore how the NVIDIA Omniverse™ platform, coupled with cutting-edge AI technology, can unlock valuable insights driving the evolution of every aspect of the automotive lifecycle. Join us for an open discussion on autonomous vehicle development and simulation, factory digital twins, and AI for design.
Connect directly with NVIDIA experts to get answers to all of your questions on GPU programming and code optimization, share your experience, and get guidance on how to achieve maximum performance on NVIDIA's platform.
Meet with experts from the NVIDIA Omniverse Spatial team and learn about improvements coming to the immersive rendering tools in Omniverse Kit. With the Omniverse spatial framework, developers can visualize their OpenUSD data and immersive scenes with incredible NVIDIA RTX™ ray tracing in an XR device. Developers and power users can use the spatial framework to start building their own XR extensions and services tailored to their use cases in Omniverse. This includes designing custom UI's with Omni.UI and streaming to Open XR devices using NVIDIA CloudXR™, while also being further extendable with Python. Come chat with us and meet other developers working with the spatial framework.
MatX provides an open-source, easy-to-use C++ numerical computing library with an interface similar to Python. It gives you near-native NVIDIA® CUDA® performance while increasing productivity using a higher-layer syntax. In this session, you can ask the MatX developers any questions you have about usage, optimization, and getting started writing GPU-accelerated code.
Visit us and discuss ways to get started or deepen your understanding of NVIDIA tools that support vision AI applications. Our topic experts are offering 1:1 dialogue on topics related to building, training, and deploying AI models. Ask about NVIDIA Metropolis, DeepStream, TAO Toolkit, TensorRT™, Triton™ Inference Server, pretrained models, Jetson™, synthetic data generation, fleet command, and more.
Graph analysis is the backbone to many workloads and having algorithms that are both fast and scalable is critical. NVIDIA RAPIDS™ cuGraph provides a robust set of algorithms that scale from small graphs on a single GPU to multi-trillion edge graphs across thousands of GPUs, all with record performance. RAPIDS cuGraph uses both software and hardware acceleration tools to get these results. Our software is built around graph primitives (algorithm building blocks), communication libraries like NCCL and UCX, memory pools, and functionality found in cuDF and Dask cuDF. Join this interactive support session with technical product managers, engineers, and solutions architects to get direct help, ask questions, raise issues, discuss future needs, or dive into your specific graph use case.
NVIDIA GPUs accelerate the most important applications in quantum chemistry (like Gaussian, VASP, Quantum ESPRESSO, GAMESS, NWChem, and CP2K) and molecular dynamics (like GROMACS, NAMD, LAMMPS, and Amber), which are also very popular in materials science, biophysics, drug discovery, and other domains. We'll answer your questions about how to get the best performance for your specific workload or figure out how you can benefit from accelerated computing and AI.
Do you want to learn how to get started accelerating LLMs? Join this interactive support session with the cuDNN engineering staff to get direct help and surface your questions, issues, and ideas specific to your use case.
Do you have questions on how to get the best performance out of NVIDIA Grace Hopper™? Then this CWE provides a unique opportunity to address all your questions. The experts at this session can cover memory management, NUMA management, Grace CPU best practices and Hopper GPU techniques for the Grace Hopper superchip.
Are you interested in the potential of harnessing GPU power in cloud-based virtual machines, specifically tailored to elevate your graphics-intensive tasks, yet unsure about the right instance types and configurations? Join an engaging and interactive session featuring NVIDIA's cloud-focused solution architects. They will guide you in selecting the perfect GPU-enabled cloud instance, fine-tuned for exceptional graphics performance across your preferred cloud provider. Take this opportunity to not only gain expert insights into tailored GPU recommendations, but also to openly discuss your specific workloads, challenges, and innovative ideas pertaining to your current graphical workloads.
Join this interactive support session with NVIDIA technical product managers, engineers, and solutions architects. You'll learn about best practices for using large language models (LLMs) and retrieval augmented generation (RAG) to connect generative AI to resources in the enterprise knowledgebase.
Discuss with experts everything related to inter-GPU communication through NVIDIA NVLink™, Infiniband, or other networks. We'll cover all communication libraries: NCCL, MPI, UCX/UCC, and NVSHMEM. This is the perfect place to discuss performance benefits of GPUDirect®, NVLink®, Infiniband, and SHARP to accelerate your deep learning training workload or your HPC application.
Engage with NVIDIA specialists in the field of autonomous vehicle development. Discuss challenges and the potential of simulation technology for facilitating extensive testing and validation of autonomous vehicles at scale. Also, ask questions about generative AI advancements and discuss its application in creating different driving scenarios and generating synthetic data to expedite the progress of autonomous vehicle development.