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Detailed information for the next webinar

Next Talk: 7/November/2022, 4-5:30pm CET

Link: https://tuwien.zoom.us/j/95094634063
4pm Central European time is (usually) 7am Pacific time and 11pm Beijing time

Accelerating Visual Analytics across the Memory and Storage Stack

Prof. Vijay Narayanan, Pennsylvania State University


First, I will present a Look-Up Table (LUT) based Processing-In-Memory (PIM) technique with the potential for running Neural Network inference tasks. The proposed LUT-based PIM methodology exploits substantial parallelism using look-up tables that preserve the bit-cell and peripherals of the existing SRAM monolithic arrays in processor caches. Next, I will present GaaS-X, a graph analytics accelerator that inherently supports sparse graph data representations using in-situ compute-enabled crossbar memory architectures. The proposed design alleviates the overheads of redundant writes, sparse to dense conversions, and redundant computations on the invalid edges that are present in other state-of-the-art crossbar-based PIM accelerators. Finally, I will present an in-SSD key-value database that uses the embedded CPU core, and DRAM memory on the SSD to support various queries with predicates and reduce the data movement between SSD and host processor significantly. Vijay Narayanan


Vijaykrishnan Narayanan is the A. Robert Noll Chair Professor of Computer Science & Engineering and Electrical Engineering at the Pennsylvania State University. Vijay received his Bachelors in Computer Science & Engineering from University of Madras, India in 1993 and his Ph.D. in Computer Science & Engineering from the University of South Florida, USA, in 1998. He is a co-director of the Microsystems Design Lab. He is a Fellow of the National Academy of Inventors, IEEE and ACM.


Prof. Narasimha Reddy

Texas A&M University

Narasimha Reddy Narasimha Reddy received a B.Tech. degree in Electronics and Electrical Communications Engineering from the Indian Institute of Technology, Kharagpur, India in August 1985, and M.S. and Ph.D. degrees in Computer Engineering from the University of Illinois at Urbana-Champaign in May 1987 and August 1990, respectively Reddy’s research interests are in Computer Networks, Storage Systems, Multimedia Systems, and Computer Architecture. During 1990-1995, he was a Research Staff Member at IBM Almaden Research Center in San Jose where he worked on projects related to disk arrays, multiprocessor communication, hierarchical storage systems and video servers. Reddy holds five patents and and was awarded a technical accomplishment award while at IBM. He received an NSF Career Award in 1996. He was a Faculty Fellow of the College of Engineering at Texas A&M during 1999-2000. His honors include an Outstanding Professor award by the IEEE student branch at Texas A&M during 1997-1998, an Outstanding Faculty award by the Department of Electrical and Computer Engineering during 2003-2004, a Distinguished Achievement award for teaching from the Former Students Association of Texas A&M University, and a citation “for one of the most influential papers from the 1st ACM Multimedia Conference”. Reddy is a Fellow of IEEE Computer Society and is a member of ACM.

Dr. Akhilesh Jaiswal

Univeristy of Southern California

Akhilesh Jaiswal Dr. Akhilesh Jaiswal is a Research Assistant Professor of Electrical and Computer Engineering at USC’s Viterbi School of Engineering. He also serves as a computer scientist with ASIC Lab at the Information Sciences Institute. His current research interest includes device-circuit co-design using existing and alternate state variables for future electronic systems. Prior to USC/ISI, Dr. Jaiswal served as a Senior Research Engineer for Technology Solutions Group at GLOBALFOUNDRIES. As a Senior Engineer, he worked on developing a compact device model for MRAM-based AI in-memory compute circuits and enabling AI acceleration through hybrid photonic-electronic neuro-mimetic devices. Akhilesh received his Ph.D. degree in Nano-electronics from Purdue University in May 2019 and his Master’s degree from the University of Minnesota in May 2014. As a part of the doctoral program, his research focused on 1) Exploration of bio-mimetic devices and circuits using emerging non-volatile technologies for Neuromorphic computing. 2) CMOS based analog and digital in-memory and near-memory computing using standard memory bit-cells for beyond von-Neumann AI/ML acceleration. Dr. Jaiswal has authored some of the initial pioneering works on Processing-in-Pixel and SRAM based in-memory computing.