Industry Spotlight: Path Towards Better Deep Learning Models and Implications for Hardware

This was our 4th SCV CLP Industry Spotlight session.

Presentation: Path Towards Better Deep Learning Models and Implications for Hardware

SPEAKER: Natalia Vassilieva, Sr. Technical Product Manager, Cerebras Systems
WEBINAR HELD: Monday, September 14, 2020, 7:30 AM PT (Pacific Timezone)
Webinar slides now available – CLICK HERE

Event title slide
ABSTRACT: Advances in Deep Learning over the past several years have demonstrated two paths to better models: scale and algorithmic innovation. Brute-force scaling of model parameter count increases model capacity, and when presented with enough training data, has shown better performance in many domains. But it requires more compute than can be delivered by a single traditional processor – clusters of 10s to even 1000s of general purpose processors are commonly used today for neural network training. This approach to scaling is not sustainable. We need algorithmic innovations to find more efficient neural network architectures and training methods. This requires more flexible hardware to develop and test novel approaches. In this presentation, we will look at the trends of recent deep learning models, discuss implications for hardware, and share how the Cerebras CS-1 addresses these requirements for both scale and flexibility of compute.

This talk is part of our series of presentations by industry experts at the IEEE Santa Clara Valley Section Corporate Liaison Program (CLP). If you have ideas for future speakers, please email the SCV CLP Chair.

SPEAKER: Natalia Vassilieva is a Sr. Technical Product Manager at Cerebras Systems, a computer systems company dedicated to accelerating deep learning. Her focus is machine learning, analytics, and application-driven software-hardware optimization and co-design. Most recently before joining Cerebras Natalia has been a Sr. Research Manager at Hewlett Packard Labs, where she led the Software and AI group in 2015-2019 and served as the head of HP Labs Russia in 2011-2015. In 2012-2015 Natalia also served as a part-time Associate Professor at St. Petersburg State University and a part-time lecturer at Computer Science Center, St. Petersburg, Russia. Before joining HP Labs Natalia worked as a Software Engineer for different IT companies in Russia from 1999 till 2007. Natalia holds a PhD in computer science from St. Petersburg State University.

Contact the Speaker:
Natalia Vassilieva on LinkedIn


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