Learn about the hottest technologies from NVIDIA experts–on-demand.
Connect With the Experts sessions at NVIDIA GTC give attendees a unique opportunity to meet with the people behind NVIDIA products and research.
Watch sessions on-demand to learn about NVIDIA technologies, including hot topics such as deep learning, accelerated computing, robotics, generative AI, metaverse applications, and more.
Join this interactive support session with Omniverse technical product managers, engineers, and solutions architects, where you can get direct help and surface your questions, issues, and ideas specific to your use case.
Do you want to write modern C++ on your GPU? Are you curious about C++ Standard Parallelism?
Come join NVIDIA's C++ library and standards team for a Q&A session on: C++ Standard Parallelism and NVC++, Thrust (CUDA C++'s high-productivity general-purpose library and parallel algorithms implementation), CUB (CUDA C++'s high-performance collective algorithm toolkit), and libcu++ (the CUDA C++ standard library).
Usage questions, feature requests, and bug reports are most welcome!
Developing robotic applications? Bring your questions and challenges to our robotics and simulation experts who will be on hand to discuss leveraging the NVIDIA Isaac™ robotics platform.
Learn about the latest optimizations in NVIDIA's image/signal processing libraries like CV-CUDA, NPP, nvJPEG, and DALI™—a fast, flexible data loading and augmentation library. We'll discuss how to use various data processing solutions spanning low-level image and signal-processing primitives in NPP through a library of easy-to-use building blocks CV-CUDA to define high-level, high-performance data processing workflows in DALI.
We'll talk about new libraries in our portfolio—CV-CUDA and nvTiff—as well as new functionalities in the existing ones (DALI, NPP, and nvJPEG).
After this short update, we'll have an open forum and Q&A session with the experts.
Join this session to discuss with experts everything related to inter-GPU communication through NVIDIA NVLink®, Infiniband, or other networks.
This session covers all communication libraries: NCCL, MPI, UCX/UCC and NVSHMEM. It’s also the perfect place to discuss performance benefits of GPU Direct, NVLink, Infiniband, and SHARP to accelerate your DL training workload or HPC application.
Join NVIDIA experts for a question-and-answer session on accelerating generative art with NVIDIA technologies such as Triton Inference Server™, TensorRT™, and Omniverse™. Generative AI is revolutionizing artist workflows and fascinating the artists and non-artists alike. We’ll discuss strategies for implementing and optimizing generative AI workflows on GPUs in the cloud and on desktops, considering features, performance, and compute cost to enable your solutions to scale and deliver high performance for users.
Our experts are highly experienced with moving AI Inference models from research to production environments and are happy to share these experiences, tools, and techniques with you, including topics such as:
- Moving from research to production
- Minimizing device memory usage
- Performance Optimization
- Integrating with existing code bases and end-to-end AI pipelines
Technologies include :
- TensorRT
- ONNX and DirectML
- CUDA and cuDNN
- Triton Inference Server
Imagine that you’ve trained your model with PyTorch, TensorFlow, or the framework of your choice, are satisfied with its accuracy, and are considering deploying it as a service. There are two important objectives to consider: maximizing model performance and building the infrastructure needed to deploy it as a service. Join us for a discussion about two key NVIDIA products that can address these two objectives: NVIDIA TensorRT, a high-performance deep learning inference, and the Triton Inference Server, an open-source inference-serving software that provides a single standardized inference platform.
If you’re new to either of these SDKs, we highly encourage you to refer to the following resources:
Triton Inference Server: https://www.youtube.com/watch?v=1kOaYiNVgFs
NVIDIA TensorRT: https://developer.nvidia.com/blog/speeding-up-deep-learning-inference-using-tensorrt-updated/
In this session, you'll get a chance to talk to the NVIDIA Developer Tools Team about the latest cutting-edge tools and how they can be used to optimize ray racing applications. We'll show you how NVIDIA Nsight systems can be used to determine if you’re GPU or CPU bound. You'll also learn about how Nsight Graphics can be used to debug and optimize GPU workloads in GPU-bound applications. Finally, you'll see how the Nsight Aftermath SDK and Nsight PerfSDK can be integrated into your application to help debug GPU crashes and analyze performance in real time.
After this session, you should have a better understanding of NVIDIA tools and have your questions answered.
NVIDIA GPUs accelerate the most important applications in quantum chemistry (such as Gaussian, VASP, Quantum ESPRESSO, GAMESS, NWChem, and CP2K) and molecular dynamics (such as GROMACS, NAMD, LAMMPS, and Amber) that 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.
Meet with experts from NVIDIA Omniverse and CloudXR teams to learn about Omniverse Create XR, the latest virtual reality functionality in Omniverse Kit. The Omniverse Create XR application enables engineers, designers, and creators to experience, review, and approve ray-traced high-fidelity 3D scenes at human scale. Developers can also use this Omniverse Kit-based app to build VR extensions and services into their own ecosystems. NVIDIA CloudXR is integrated into Omniverse Kit, allowing users to take advantage of CloudXR’s streaming solution to deliver graphics-intensive applications to mobile, untethered devices.
Connect with NVIDIA experts to learn how enterprises are using AI to help detect and prevent security threats as they happen. Find out how developers can take advantage of NVIDIA technologies such as the NVIDIA Morpheus cybersecurity framework to build solutions that run on NVIDIA-Certified servers accelerated by NVIDIA GPUs and DPUs. These solutions can help companies identify and act on threats on a scale that was previously impossible.
In this session, attendees will have the ability to connect with the NVIDIA experts in retail/CPG on topics like data science, RecSys, search, and computer vision/video analytics.
NVIDIA DRIVE Infrastructure is a complete workflow platform addressing many areas of the autonomous vehicle (AV) development life cycle, including data ingestion, curation, labeling, training, and validation through simulation, replay, and synthetic data generation (SDG). In this Connect with Experts, we talk about how NVIDIA DGX SuperPOD accelerates end-to-end AV development in this rapidly evolving market. Synthetic data generation is also a key component in the AV development life cycle. Based on our physics-based simulation and collaboration platform NVIDIA Omniverse, we will cover the concept of physically accurate synthetic sensor data generated from the NVIDIA DRIVE Replicator simulation tool. Finally, learn how NVIDIA DRIVE Sim delivers a comprehensive simulation suite for end-to-end AV development and validation.
NVIDIA Jetson is the world's leading computing platform for AI at the edge. High in performance and low in power consumption, it's ideal for compute-intensive embedded applications like robots, drones, mobile medical imaging, and intelligent video analytics. Manufacturers, independent developers, startups, students, and enthusiasts can use Jetson developer kits and modules to explore the future of embedded computing and artificial intelligence. NVIDIA engineers and Jetson experts will be available to discuss the platform capabilities, SDKs, and development tools, and answer questions to help you rapidly deploy AI at the edge.
Healthcare and life sciences demand accelerated and optimized workflows for genomics, radiology, pathology, medical devices, and in silico drug discovery. With NVIDIA, data scientists, bioinformaticians, and developers can harness the power of artificial intelligence and high performance computing to provide better care for patients and better understand proteins, DNA/RNA, and small molecules. We're living in a time of great breakthroughs and novel discoveries in GPU/CPU/DPU technology, AI model architectures, and solutions that can help researchers kick-start their AI model development, deployment, and scaling. Please join us alongside our technical experts in computational chemistry, computational biology, data science, bioinformatics, medical devices, computer vision, picture archiving and communication systems, natural language processing, radiology, pathology, and genomics.
Come talk to experts in GPU programming and code optimization, share your experience with them, and get guidance on how to achieve maximum performance on NVIDIA's platform.
Developing solutions for vision, autonomous machines, or robotics? Share your challenges with our experts in embedded edge AI development, the NVIDIA Jetson™ platform, and SDKs including Isaac, DeepStream, and TLT.
Come and chat with our experts about how to deploy various workflows on top of a vGPU infrastructure, questions on Licensing and NLS, or how to use NVAIE: Virtualization for AI. We’ll explore topics concerning Omniverse on an NVIDIA RTX® workstation, a workgroup server, or large group collaboration on cloud servers.