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  • Memristive Accelerators for Data Intensive Computing: From Machine Learning to High- Performance Linear Algebra

    Thu, Nov 30, 2017 @ 02:00 PM - 03:15 PM

    Ming Hsieh Department of Electrical and Computer Engineering

    Conferences, Lectures, & Seminars

    Speaker: Engin Ipek, University of Rochester

    Talk Title: Memristive Accelerators for Data Intensive Computing: From Machine Learning to High- Performance Linear Algebra

    Abstract: DRAM is facing severe scalability challenges due to precise charge placement and sensing hurdles in deep-submicron geometries. Resistive memories, such as phase-change memory (PCM), resistive RAM (RRAM), and spin-torque transfer magnetoresistive RAM (STT-MRAM), hold the potential to scale well beyond DRAM and are promising DRAM replacements. Although the near term application of these technologies will likely be in main memory and storage, their electrical properties also make it possible to design qualitatively new methods of accelerating important classes of workloads.

    In this talk, I will examine high-performance memristive compute engines that combine two powerful capabilities: in-situ data processing and analog computing. Implementations of these engines using PCM, RRAM, and STT-MRAM will be introduced, and their application to machine learning, combinatorial optimization, and scientific computing workloads will be presented. The talk will conclude with a discussion of the novel error correction techniques that are necessary to make the reliability and precision of memristive accelerators competitive with digital systems.

    Biography: Engin Ipek is an Associate Professor of Electrical & Computer Engineering and of Computer Science at the University of Rochester. His research interests are in energy-efficient architectures, high-performance memory systems, and the application of emerging technologies to computer systems. Prof. Ipek received his BS (2003), MS (2007), and Ph.D. (2008) degrees from Cornell University, all in Electrical and Computer Engineering. Prior to joining the University of Rochester, he was a researcher in the computer architecture group at Microsoft Research (2007-2009). His work has been recognized by the 2014 IEEE Computer Society TCCA Young Computer Architect Award, an HPCA 2016 distinguished paper award, three IEEE Micro Top Picks awards, an ASPLOS 2010 best paper award, an NSF CAREER award, and an invited Communications of the ACM research highlights article.

    Host: Xuehai Qian, x04459, xuehai.qian@usc.edu

    Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132

    Audiences: Everyone Is Invited

    Contact: Gerrielyn Ramos


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