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Learn about the newest release of CUDA and its exciting features and capabilities in this webinar and live Q&A. We will pay particular focus on release compatibility, the lazy loading feature, and how we uniquely support the new NVIDIA Hopper and Ada Lovelace GPU architectures. CUDA 12.0 toolkit release: https://nvda.ws/3FLUn3B 00:00 - Introduction 03:39 - CUDA Dynamic Parallelism 09:55 - Hopper DPX Instructions 12:06 - Lazy Loading 16:10 - OS Support Updates 17:26 - CUDA Compiler Updates 33:47 - Math Libraries 37:53 - Compatibility Updates 49:47 - Thank You and Q&A Additional resources: CUDA Dynamic Parallelism: https://developer.nvidia.com/blog/introduction-cuda-dynamic-parallelism/ CUDA Programming Model for Hopper Architecture: https://www.nvidia.com/en-us/on-demand/session/gtcfall22-a41095/?playlistId=playList-b5be3b9b-cc52-48ed-b83d-4352b108e766 Join our developer program: https://nvda.ws/3BEFldp About our presenters: Rob Armstrong, is a principal technical product manager for the CUDA toolkit. For over 20 years he has focused on accelerating software with heterogeneous hardware platforms, and has particular interest in computer architecture and hardware/software interaction. Rob Nertney is a senior technical product manager for CUDA. He has spent nearly 15 years architecting the features and deployment of accelerator hardware into hyperscale environments for both internal and external use by developers. He has several patents in processor design relating to secure solutions that are in production today. In his spare time, he loves golfing when the weather is nice, and gaming (on RTX hardware of course!) when the weather isn’t. Arthy Sundaram is a technical product manager for the CUDA platform. She holds an MS in computer science from Columbia University. Her areas of interest are operating systems, compilers, and computer architecture. Matthew Nicely joined NVIDIA in March 2019, having previously worked at the U.S. Army Aviation and Missile Research Development and Engineering Center, Huntsville, AL, USA. There, he focused on CUDA algorithm development and optimizations on the Jetson series. At NVIDIA, he has worked in the Federal segment assisting with CUDA development and optimizations, along with education and proof of concepts for customers on various NVIDIA tool sets, before recently transitioning to math libraries product manager. In 2019, he received his Ph.D. degree in computer engineering, focusing on algorithm optimizations on GPUs. Join the NVIDIA Developer Program: https://nvda.ws/3OhiXfl Read and subscribe to the NVIDIA Technical Blog: https://nvda.ws/3XHae9F

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