Inside NVIDIA’s AI Infrastructure for Self-driving Cars

Clement Farabet and Nicolas Koumchatzky, NVIDIA

Abstract: 

We'll discuss Project MagLev, NVIDIA's internal end-to-end AI platform for developing its self-driving car software, DRIVE. We'll explore the platform that supports continuous data ingest from multiple cars producing TB of data per hour. We'll also cover how the platform enables autonomous AI designers to iterate training of new neural network designs across thousands of GPU systems and validate the behavior of these designs over multi PB-scale data sets. We will talk about our overall architecture for everything from data center deployment to AI pipeline automation, as well as large-scale AI dataset management, AI training, and testing.

Clement Farabet, NVIDIA

Clement Farabet is vice president of AI infrastructure at NVIDIA. He received a Ph.D. from Universite Paris-Est in 2013, co-advised by Laurent Najman and Yann LeCun. His thesis focused on real-time image understanding, introducing multi-scale convolutional neural networks and a custom hardware architecture for deep learning. Clement co-founded Madbits, a startup working on web-scale image understanding that was sold to Twitter in 2014. He is also cofounder of Twitter Cortex, a team focused on building Twitter's deep learning platform for recommendations, search, spam, NSFW content, and ads.

Nicolas Koumchatzky, NVIDIA

Nicolas Koumchatzky is a Director of AI Infrastructure at NVIDIA. He is currently managing an organization building a cloud AI platform to power the development of Autonomous Vehicles. Previously, he was managing Twitter’s centralized AI Platform team Twitter Cortex.

OpML '20 Open Access Sponsored by NetApp

BibTeX
@conference {256676,
author = {Clement Farabet and Nicolas Koumchatzky},
title = {Inside NVIDIA{\textquoteright}s {AI} Infrastructure for Self-driving Cars},
year = {2020},
publisher = {{USENIX} Association},
month = jul,
}

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