Webinar: Closing the AI Memory Performance Gap

Webinar: Closing the AI Memory Performance Gap

Join us on Thursday, July 25, 2019 at 2PM ET for this LIVE webinar, presented by Rambus

Date: Thursday, July 25, 2019
Time: 2:00 PM Eastern Daylight Time
Sponsor: Rambus
Duration: 30 Minutes

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Summary:

Rapid advances in artificial intelligence have re-energized the semiconductor industry, with numerous companies developing AI-specific silicon aimed at providing ever-higher levels of performance and power efficiency. As our increasingly connected world evolves, AI continues to evolve as well. But several critical challenges await chip and system designers as our industry strives to meet the relentless demands for more performance and better power efficiency. Among the most critical of these challenges are memory system bottlenecks that serve as a stark reminder of the processor-memory gap that has impacted processor design for the last few decades. With Moore’s Law slowing and Dennard scaling finished, the industry has turned to domain-specific silicon to improve performance and power consumption. Utilizing a variety of techniques, specialized neural network processors have demonstrated tremendous improvements in performance and power efficiency on these workloads. But they have also exacerbated the decades-old processor memory gap, creating an “AI-memory gap” that threatens the continued progress of AI silicon.

In this webinar, we’ll discuss some of these challenges, as well as potential ways to support the continued progress of AI silicon.

Speaker:

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Steve Woo, Fellow and Distinguished Inventor, Rambus

Steven Woo is a Fellow and Distinguished Inventor at Rambus Inc., working in Rambus Labs on technology and business development efforts across the company. His current focus is on technology and memory systems for accelerators and modern computing infrastructures, including machine learning systems, data centers, and advanced computing systems. Since joining Rambus, Steve has worked in various roles leading architecture, technology, and performance analysis efforts, and in marketing, strategy, and product planning roles. Steve received PhD and MS degrees in Electrical Engineering from Stanford University, and Master of Engineering and BS Engineering degrees from Harvey Mudd College.

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TAGS: Webcasts