We are excited to invite all of you again to attend the third TECHNICAL TALK, TECH-TALK, in the INDUSTRY EXPOSURE SERIES.
We are hosting this event with Cerebras, https://cerebras.net/
Information about INTERNSHIP & FULL-TIME EMPLOYMENT OPPORTUNITIES
at the company will follow the event.
We will be giving out one of amazon(Canada) or UberEats(Canada) GIFT-CARDS (CAD 15 each) to the attending students who register and attend the event for more than 30 minutes.
Please find more information about the event below.
DATE : Thursday, Jun 10, 2021
TIME : 11 AM – 12 PM
REG. LINK : https://utoronto.zoom.us/meeting/register/tZUpfuCopjMqG91xCU3cZByrcHqHfwCc0yP2
Cerebras Systems: A Systems Approach to Deep Learning
The rise of Machine Learning workloads has spurred new interest in specialized hardware architectures, which offer significant improvements in performance and power efficiency. However, a substantial challenge faced by these architectures is providing a highly productive software interface, which also unlocks the hardware’s full performance.
In this talk, we will provide an overview of the software stack we’re developing at Cerebras to program the Wafer Scale Engine (WSE) 2. The WSE2 is the largest chip ever built, with 850,000 AI-optimized cores, and orders of magnitude more compute, memory, and interconnect bandwidth than single die offerings. We’ll focus on some of the challenging and interesting problems, which we’re solving to make the WSE2’s massive performance accessible and easy to use. We will also cover Machine Learning on the Wafer-Scale Engine.
Kevin E. Murray is a Member of Technical Staff at Cerebras Systems in Toronto. He received his PhD in Electrical and Computer Engineering from the University of Toronto in 2020. He was previously the lead developer of the Verilog to Routing (VTR) project, a visiting Research Assistant at Imperial College London, and has worked on digital design flows at Advanced Micro Devices (AMD). His research interests include Computer Aided Design (CAD) algorithms, and architecture for Machine Learning accelerators and FPGAs.
Natalia Vassilieva is the Director of Product at Cerebras. Her focus is machine learning and artificial intelligence, analytics, and application-driven software-hardware optimization and co-design. Previously, Natalia has been a Sr. Research Manager at Hewlett Packard Labs, where she led the Software and AI group and served as the head of HP Labs Russia from 2011 till 2015. Prior to HPE, she was an Associate Professor at St. Petersburg State University and worked as a software engineer for different IT companies. Natalia holds a PhD in computer science from St. Petersburg State University.
More Company Info.:
Info on 2nd gen product line here: https://www.anandtech.com/show/16626/cerebras-unveils-wafer-scale-engine-two-wse2-26-trillion-transistors-100-yield
Collaboration with AstraZeneca: https://larslynnehansen.medium.com/accelerating-drug-discovery-research-with-new-ai-models-a-look-at-the-astrazeneca-cerebras-b72664d8783