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Chia-Lin Yang, National Taiwan University, ONLINE

Event Date: December 7, 2020 10:0


In-Memory Computing for AI

SFB876 Gast

Abstract:

In-memory computing provides a promising solution to improve the energy efficiency of AI algorithms. ReRAM-based crossbar architecture has gained a lot of attention recently. A few studies have shown the successful tape out of CIM ReRAM macros. In this talk, I will introduce ReRAM-based DNN accelerator designs, with emphasis on the system-level simulation method and techniques to exploit sparsity.

Short bio:

Chia-Lin Yang is a Professor in the Department of Computer Science and Information Engineering at NTU. Her research is in the area of computer architecture and system with focuses on storage/NVM architecture and AI-enabled edge computing. She was the General Co-chair for ISLPED 2017/Micro 2016, and the Program Co-Chair for ISLPED 2016. Dr. Yang is currently serving as an Associate Editor for IEEE Transaction on Computer-Aided Design, IEEE Computer Architecture Letter and in the editorial board for IEEE Design & Test. She has also served on the technical program committees of several IEEE/ACM conferences, such as ISCA, ASPLOS, HPCA, ISLPED, IPDPS, ICCD, DAC, ICCAD, ISSS+CODES, CASES, Date, ASP-DAC. She received the best paper award of ISLPED 2009, the 2005 and 2010 IBM Faculty Award´╝î2014 NTU EECS Academic Contribution Award, and 2019 Distinguished Electrical Engineering Professor, Chinese Inst. of Electrical Engineering.



https://www.csie.ntu.edu.tw/~yangc/

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