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Title: Playlist | CUDA, Libraries and Dev Tools Conference Sessions

URL Source: https://www.nvidia.com/gtc/sessions/cuda-libraries-and-dev-tools/

Published Time: Tue, 11 Aug 2026 16:28:13 GMT

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## CUDA, Libraries and Dev Tools Conference Sessions

17 sessions

[39:33 ![Image 1: Architects of the Accelerated Age: How CUDA Builders Changed the World (and How You’re Next)](https://cdnsecakmi.kaltura.com/p/2935771/thumbnail/entry_id/1_ljhr8h2a/width/400)](https://www.nvidia.com/en-us/on-demand/session/gtc26-s82416?playlistId=gtc26-cuda-libraries-and-dev-tools)

Panel

[Architects of the Accelerated Age: How CUDA Builders Changed the World (and How You’re Next)](https://www.nvidia.com/en-us/on-demand/session/gtc26-s82416?playlistId=gtc26-cuda-libraries-and-dev-tools)

March 2026

paulius micikevicius, Software Engineer, Meta Superintelligence Labs

Kate Clark, Distinguished DevTech Engineer, NVIDIA

Joe Stam, Head of Research Technology, Core Strategies , Jump Trading

Stephen Jones (SW), CUDA Architect, NVIDIA

Wen-Mei Hwu, Sr. Distinguished Research Scientist, Senior Distinguished Research Scientist and Senior Research Director at NVIDIA

The world was changed by creators who wrote the first kernels and turned raw potential into reality. Now, they are sharing the blueprints. Join us for an unfiltered look at CUDA’s impact with prolific creators who have redefined the boundaries of…

[44:27 ![Image 2: CUDA: New Features and Beyond](https://cdnsecakmi.kaltura.com/p/2935771/thumbnail/entry_id/1_kbdc8erc/width/400)](https://www.nvidia.com/en-us/on-demand/session/gtc26-s81859?playlistId=gtc26-cuda-libraries-and-dev-tools)

Talk

[CUDA: New Features and Beyond](https://www.nvidia.com/en-us/on-demand/session/gtc26-s81859?playlistId=gtc26-cuda-libraries-and-dev-tools)

March 2026

Stephen Jones (SW), CUDA Architect, NVIDIA

The CUDA platform is the foundation of the GPU computing ecosystem. Every application and framework that uses the GPU does so through CUDA's libraries, compilers, runtimes and language—which means CUDA is growing as fast as its…

[](https://www.nvidia.com/en-us/on-demand/session/gtc26-cwes81535?playlistId=gtc26-cuda-libraries-and-dev-tools)

Connect With the Experts

[CUDA Developer Best Practices](https://www.nvidia.com/en-us/on-demand/session/gtc26-cwes81535?playlistId=gtc26-cuda-libraries-and-dev-tools)

March 2026

Bryce Lelbach, Principal Architect, NVIDIA

Ashwin Srinath, Senior Software Engineer, NVIDIA

Georgii Evtushenko, Sr. Software Engineer, NVIDIA

Jonathan Bentz, CUDA Technical Marketing Engineer, NVIDIA

Jonathan Dekhtiar, Sr. CUDA Python Engineer, NVIDIA

Jaydeep Marathe, Principal Software Engineer, NVIDIA

Jake Hemstad, Software Engineering Manager, NVIDIA

Leo Fang, Python CUDA Tech Lead, NVIDIA

Nader Al Awar, Senior Software Engineer, NVIDIA

Rafael Campana, Sr. Engineering Director of CUDA Developer Tools, NVIDIA

Trent Nelson, Principal Software Engineer, NVIDIA

Vyas Ramasubramani, Sr. Systems Software Engineer, NVIDIA

Join this live Q&A session with some of NVIDIA’s own CUDA developers to demystify the process of building real-world CUDA applications. From utilizing CUDA accelerated libraries, profilers, and debugging tools to setting up CI pipelines,…

[](https://www.nvidia.com/en-us/on-demand/session/gtc26-dliw82265?playlistId=gtc26-cuda-libraries-and-dev-tools)

Full-Day Workshop

[Fundamentals of GPU-Accelerated Workflows with CUDA Python](https://www.nvidia.com/en-us/on-demand/session/gtc26-dliw82265?playlistId=gtc26-cuda-libraries-and-dev-tools)

March 2026

Bryce Lelbach, Principal Architect, NVIDIA

Katrina Riehl, Principal Technical Product Manager, NVIDIA

This course delivers a hands-on introduction to GPU-accelerated computing in Python, empowering developers to build fast, scalable applications using NVIDIA’s CUDA ecosystem. Through guided notebooks, participants master CuPy for array…

[](https://www.nvidia.com/en-us/on-demand/session/gtc26-cwes81549?playlistId=gtc26-cuda-libraries-and-dev-tools)

Connect With the Experts

[What's in Your Developer Toolbox? CUDA, AI, and Graphics Profiling, Optimization, and Debugging…](https://www.nvidia.com/en-us/on-demand/session/gtc26-cwes81549?playlistId=gtc26-cuda-libraries-and-dev-tools)

March 2026

Aurelio Reis, Director of Graphics Developer Tools, NVIDIA

Gaoyan Xie, Sr. Manager of Software Engineering, NVIDIA

Holly Wilper, Manager, System Software Tools, NVIDIA

Jackson Marusarz, Technical Product Manager, NVIDIA

Magnus Strengert, Software Engineering Manager, NVIDIA

Rafael Campana, Sr. Engineering Director of CUDA Developer Tools, NVIDIA

Victor da Cruz Ferreira, Senior Software Engineer, NVIDIA

Zbigniew Kondolewicz, Senior Software Developer, NVIDIA

Several experts from the tools development and management teams will be available to talk about getting started, best practices, and advanced techniques for application debugging and optimization with NVIDIA developer tools. You can ask…

[39:18 ![Image 3: Accelerated Building Blocks for Next-Generation AI+HPC Workloads](https://cdnsecakmi.kaltura.com/p/2935771/thumbnail/entry_id/1_06y0mmhk/width/400)](https://www.nvidia.com/en-us/on-demand/session/gtc26-s81792?playlistId=gtc26-cuda-libraries-and-dev-tools)

Talk

[Accelerated Building Blocks for Next-Generation AI+HPC Workloads](https://www.nvidia.com/en-us/on-demand/session/gtc26-s81792?playlistId=gtc26-cuda-libraries-and-dev-tools)

March 2026

Heidi Poxon, Director of Product, HPC Software, NVIDIA

Embracing next-generation technology like AI-infused scientific workflows involves blending familiar building blocks with innovation, timeliness, and purpose. Whether it's models pre-trained on petabyte-scale data for common forecasting tasks, or…

[](https://www.nvidia.com/en-us/on-demand/session/gtc26-cwes81771?playlistId=gtc26-cuda-libraries-and-dev-tools)

Connect With the Experts

[How to Run and Optimize Your Workloads on the NVIDIA Grace and Vera CPUs](https://www.nvidia.com/en-us/on-demand/session/gtc26-cwes81771?playlistId=gtc26-cuda-libraries-and-dev-tools)

March 2026

Holly Wilper, Manager, System Software Tools, NVIDIA

Hans Mortensen, Grace Product Specialist – NVIDIA Solutions Architecture, NVIDIA

Lukas Alt, DevTech Engineer, NVIDIA

Mathias Wagner, Sr. Developer Technology Engineer, NVIDIA

Matthias Langer, Sr. AI and Developer Technology Engineer, NVIDIA

Yuzhong Wen, Sr. DevTech Engineer, NVIDIA

Join us to explore how NVIDIA's latest generation of ARM-based CPUs can boost data center performance and energy efficiency. We'll help you optimize your applications for the current NVIDIA Grace architecture while providing insights into…

[36:55 ![Image 4: Accelerate Open Science: Incorporating CUDA Into the SciPy Ecosystem](https://cdnsecakmi.kaltura.com/p/2935771/thumbnail/entry_id/1_u9l7jeg1/width/400)](https://www.nvidia.com/en-us/on-demand/session/gtc26-s82113?playlistId=gtc26-cuda-libraries-and-dev-tools)

Panel

[Accelerate Open Science: Incorporating CUDA Into the SciPy Ecosystem](https://www.nvidia.com/en-us/on-demand/session/gtc26-s82113?playlistId=gtc26-cuda-libraries-and-dev-tools)

March 2026

Gaël Varoquaux, Co-Founder, :probabl.

Katrina Riehl, Principal Technical Product Manager, NVIDIA

Ianna Osborne, Research Software Engineer, Princeton University

Leo Fang, Python CUDA Tech Lead, NVIDIA

Travis Oliphant, CEO, OpenTeams

As GPUs become central to scientific Python workloads, SciPy-ecosystem projects—including NumPy, SciPy, and scikit-learn—face the challenge of adopting CUDA without sacrificing usability, portability, or community values. This panel brings…

[](https://www.nvidia.com/en-us/on-demand/session/gtc26-cwes82212?playlistId=gtc26-cuda-libraries-and-dev-tools)

Connect With the Experts

[Boost Data Science Pipelines With Accelerated Libraries](https://www.nvidia.com/en-us/on-demand/session/gtc26-cwes82212?playlistId=gtc26-cuda-libraries-and-dev-tools)

March 2026

Bobby Evans, Distinguished Software Engineer, NVIDIA

Alexandria Barghi, Senior Software Engineer, NVIDIA

Greg Kimball, Software Engineering Manager, NVIDIA

Divye Gala, Senior Software Engineer, NVIDIA

Vyas Ramasubramani, Sr. Systems Software Engineer, NVIDIA

Drop into these walk-up office hours to meet the experts building NVIDIA’s CUDA-X data science libraries and talk through your end-to-end pipeline needs. ​Get practical guidance on where cuDF, cuML, cuGraph, and GPU-accelerated Spark can boost…

[38:07 ![Image 5: Accelerate Engineering Simulations with NVIDIA cuDSS](https://cdnsecakmi.kaltura.com/p/2935771/thumbnail/entry_id/1_0uhrzy90/width/400)](https://www.nvidia.com/en-us/on-demand/session/gtc26-s81824?playlistId=gtc26-cuda-libraries-and-dev-tools)

Talk

[Accelerate Engineering Simulations with NVIDIA cuDSS](https://www.nvidia.com/en-us/on-demand/session/gtc26-s81824?playlistId=gtc26-cuda-libraries-and-dev-tools)

March 2026

Azi Riahi, Principal Product Manager, NVIDIA

NVIDIA CUDA Direct Sparse Solver (cuDSS) is increasingly being adopted in large-scale simulations for engineering and design, such as those pertinent to electronic engineering automation (EDA) and computer-aided engineering (CAE). In this…

[40:36 ![Image 6: Accelerate GPU Scientific Computing With nvmath-python](https://cdnsecakmi.kaltura.com/p/2935771/thumbnail/entry_id/1_f78xjv77/width/400)](https://www.nvidia.com/en-us/on-demand/session/gtc26-s81581?playlistId=gtc26-cuda-libraries-and-dev-tools)

Talk

[Accelerate GPU Scientific Computing With nvmath-python](https://www.nvidia.com/en-us/on-demand/session/gtc26-s81581?playlistId=gtc26-cuda-libraries-and-dev-tools)

March 2026

Aart Bik, Distinguished Engineer, NVIDIA

Sergey Maydanov, Sr. Software Engineering Manager, NVIDIA

In 2024, NVIDIA unveiled nvmath-python, a library designed to bridge the gap between Python scientific community and NVIDIA CUDA-X math libraries, and it’s now generally available. You’ll learn what makes nvmath-python a useful addition…

[36:34 ![Image 7: Real-Time Science and Engineering With AI Physics and Kit-CAE](https://cdnsecakmi.kaltura.com/p/2935771/thumbnail/entry_id/1_tl7k6a5t/width/400)](https://www.nvidia.com/en-us/on-demand/session/gtc26-s81781?playlistId=gtc26-cuda-libraries-and-dev-tools)

Talk

[Real-Time Science and Engineering With AI Physics and Kit-CAE](https://www.nvidia.com/en-us/on-demand/session/gtc26-s81781?playlistId=gtc26-cuda-libraries-and-dev-tools)

March 2026

Jeff Larkin, HPC Architect, NVIDIA

Physical engineering is moving from static reports and siloed workflows to real‑time, interactive insight. This session shows how AI physics meets simulation‑driven engineering by putting NVIDIA’s GPU‑accelerated libraries and NVIDIA Omniverse…

[36:45 ![Image 8: cuEST: Accelerating Quantum Chemistry on GPUs](https://cdnsecakmi.kaltura.com/p/2935771/thumbnail/entry_id/1_zek933kl/width/400)](https://www.nvidia.com/en-us/on-demand/session/gtc26-s81770?playlistId=gtc26-cuda-libraries-and-dev-tools)

Talk

[cuEST: Accelerating Quantum Chemistry on GPUs](https://www.nvidia.com/en-us/on-demand/session/gtc26-s81770?playlistId=gtc26-cuda-libraries-and-dev-tools)

March 2026

Anders Blom, Technical Product Manager, Synopsys

Robert Parrish, Sr. Engineering Manager, NVIDIA

Gaussian-basis quantum chemistry on NVIDIA GPUs is primed to change the world. Join this session to learn about new technologies and offerings from NVIDIA that help accelerate this paradigm shift. 

[01:39:45 ![Image 9: How to use NVIDIA Warp to Build GPU-Accelerated Computational Physics Simulations](https://cdnsecakmi.kaltura.com/p/2935771/thumbnail/entry_id/1_t7koy8pb/width/400)](https://www.nvidia.com/en-us/on-demand/session/gtc26-dlit81837?playlistId=gtc26-cuda-libraries-and-dev-tools)

Training Lab

[How to use NVIDIA Warp to Build GPU-Accelerated Computational Physics Simulations](https://www.nvidia.com/en-us/on-demand/session/gtc26-dlit81837?playlistId=gtc26-cuda-libraries-and-dev-tools)

March 2026

Eric Shi, Sr. Engineering Manager, NVIDIA

Mohammad Mohajerani, Sr. Product Manager, NVIDIA

Sheel Nidhan, Sr. Technical Marketing Engineer, NVIDIA

Discover how NVIDIA Warp enables the next generation of GPU-accelerated physics, geometry processing, and differentiable programming. This training lab introduces Warp’s core capabilities and modules, then moves into a hands-on notebook where…

[37:53 ![Image 10: Accelerating Industrial Engineering: From Product Design to Manufacturing in the AI Supercomputing Era](https://cdnsecakmi.kaltura.com/p/2935771/thumbnail/entry_id/1_zf8ln5u8/width/400)](https://www.nvidia.com/en-us/on-demand/session/gtc26-s82017?playlistId=gtc26-cuda-libraries-and-dev-tools)

Talk

[Accelerating Industrial Engineering: From Product Design to Manufacturing in the AI…](https://www.nvidia.com/en-us/on-demand/session/gtc26-s82017?playlistId=gtc26-cuda-libraries-and-dev-tools)

March 2026

Christoph Meyer, Chief Program Officer, McLaren Automotive

Neil Ashton, Distinguished Engineer, NVIDIA

Accelerated computing and AI supercomputing are redefining industrial engineering, spanning computational engineering (CAE) to semiconductor design and manufacturing. Together, these fields drive how the world conceives, simulates,…

[36:55 ![Image 11: Python All the Way Down: Speed-of-Light CUDA Without Leaving Python](https://cdnsecakmi.kaltura.com/p/2935771/thumbnail/entry_id/1_0lwxnq03/width/400)](https://www.nvidia.com/en-us/on-demand/session/gtc26-s81531?playlistId=gtc26-cuda-libraries-and-dev-tools)

Talk

[Python All the Way Down: Speed-of-Light CUDA Without Leaving Python](https://www.nvidia.com/en-us/on-demand/session/gtc26-s81531?playlistId=gtc26-cuda-libraries-and-dev-tools)

March 2026

Ashwin Srinath, Senior Software Engineer, NVIDIA

Ianna Osborne, Research Software Engineer, Princeton University

How would you write a Python library that uses CUDA today? Most Python GPU libraries—PyTorch, CuPy, RAPIDS, and others—still build on CUDA C++ because many core CUDA building blocks have only ever existed in C++. That’s now changing. New…

[](https://www.nvidia.com/en-us/on-demand/session/gtc26-qa81741?playlistId=gtc26-cuda-libraries-and-dev-tools)

Q&A With NVIDIA Experts

[Ask the Experts: Applications Built for Scale With cuPyNumeric](https://www.nvidia.com/en-us/on-demand/session/gtc26-qa81741?playlistId=gtc26-cuda-libraries-and-dev-tools)

March 2026

Bo Dong, Principal Technical Product Manager, NVIDIA

Andy Terrel, CUDA Python Product Lead, NVIDIA

Irina Demeshko, Sr. Software Engineer, NVIDIA

Manolis Papadakis, Software Engineering Manager, Legate Framework, NVIDIA

Shriram Jagannathan, Engineer, NVIDIA

Quynh Nguyen, HPC and AI Alliance Manager, NVIDIA

Want to understand how Python scales efficiently across GPUs and clusters? Join NVIDIA experts for a live, classroom-style Q&A on cuPyNumeric, the technology that extends NumPy to distributed GPU environments. In this session, you’ll have the…

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