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Sessions run Wednesdays from 4:30–5:30 PM in CoDa E160. Each session features a different Stanford speaker; talk titles are announced by the organizers.
Sessions run Wednesdays from 4:30–5:30 PM in CoDa E160. Each session features a different Stanford speaker; talk titles are announced by the organizers.
A eureka moment is a two-step process: discovering something new and surprising, and establishing that it is correct. Drawing on her work at Axiom, Carina will discuss the transition from solving mathematical benchmarks to contributing to research, and from proving individual theorems to formalizing mathematical theories in Lean.
A eureka moment is a two-step process: discovering something new and surprising, and establishing that it is correct. Drawing on her work at Axiom, Carina will discuss the transition from solving mathematical benchmarks to contributing to research, and from proving individual theorems to formalizing mathematical theories in Lean.
This session explores how to efficiently run and monitor large workloads in hyper-scalars and the kind of telemetry data we can monitor from the Infra and workload side. We will review various tools offered by NVIDIA to monitor the performance of a workload and how they improve stability with increasing scale.
Aparnaa Ramani is an AI Solution Architect working closely with leading AI labs. She collaborates closely with them on optimizing workloads and data center bring-ups with the latest NVIDIA architecture. Before joining NVIDIA, she worked as a GPU kernel developer at Qualcomm. Aparnaa has a Master's degree from Georgia Tech with focus on statistical ML and Advanced DSP.