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This session covers the foundational knowledge of GPUs, including their architecture, functionality, and applications in computing. It provides an introduction to GPU computing through the lens of the Marlowe SuperPod and prepares learners for advanced topics such as GPU-accelerated data science and machine learning.
Location: CoDa W401

This session covers the foundational knowledge of GPUs, including their architecture, functionality, and applications in computing. It provides an introduction to GPU computing through the lens of the Marlowe SuperPod and prepares learners for advanced topics such as GPU-accelerated data science and machine learning.
Location: CoDa W401
For 9/23 and 10/7 only, sessions are at the David Packard Electrical Engineering Building, Room 101. Each session features a different Stanford speaker; talk titles are announced by the organizers.

For 9/23 and 10/7 only, sessions are at the David Packard Electrical Engineering Building, Room 101. Each session features a different Stanford speaker; talk titles are announced by the organizers.
Speaker: Emma Brunskill, Associate Professor of Computer Science, Stanford University
The logistics details for each seminar will be provided to registered participants. Sign up here to be included on the mailing list and learn about future events.
This talk is co-sponsored by USF's Master's in Applied Economics and the Stanford Causal Science Center. For additional information and abstracts from past talks, please click here
6:30 – 7:00 PM: Networking Reception
7:00 – 8:30 PM: Speaker Presentation followed by Q&A
This event brings together graduate-trained economists and other quantitative social scientists from academia, policy, or the private sector who are interested in the tech economy and methods for analyzing it. Each seminar will feature a guest speaker who will present on their work and research, with discussion and questions encouraged throughout. This broadly defined space also offers an opportunity to make connections with others in the field.