Nvidia GTC 2025 Recap + AI Model Performance Tips + AI Systems Engg Tricks

Zoom link: https://us02web.zoom.us/j/82308186562

Talk #0: Introductions and Meetup Updates
by Chris Fregly and Antje Barth

Talk #1: AI Model Performance Optimizations for Beginners (and More Than Beginners) by Chaim Rand
Modern AI model training often relies on powerful and expensive machinery like GPUs. Performance optimization is a key tool in accelerating model convergence and reducing development costs. Fortunately, you do not need to be a CUDA expert in order to introduce meaningful improvements to your training efficiency. In this talk, we will motivate the inclusion of performance analysis and optimization in your AI model development and demonstrate a few simple tricks and techniques for accelerating your model.

Bio: With a twelve-year background in Computer Vision and Artificial Intelligence, Chaim Rand is a strong advocate for Machine Learning developers assuming responsibility for the runtime performance and associated expense of their code. Be sure to see his blog page on TowardsDataScience where he demonstrates the importance and accessibility of analyzing and optimizing machine learning workloads.

Talk #2: Nvidia GTC 2025 Recap and AI Systems Performance Engineering Book Overview by Chris Fregly
Recap of Nvidia GTC 2025 and overview of the new book.

Zoom link: https://us02web.zoom.us/j/82308186562

Related Links
O'Reilly Book: https://www.amazon.com/Systems-Performance-Engineering-Optimizing-Algorithms/dp/B0F47689K8/
YouTube: https://www.youtube.com/@AIPerformanceEngineering
Generative AI Free Course on DeepLearning.ai: https://bit.ly/gllm