Mon, Oct 14, 2019 @ 11:00 AM - 12:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Akhilesh Jaiswal, Senior Research Engineer, GLOBALFOUNDRIES Worldwide Research Division
Talk Title: Engineering Nano-electronics for Enabling Ubiquitous Intelligence
Abstract: The science of Artificial Intelligence (AI) is built upon multi-disciplinary areas of research such as Nano-, Bio-electronics, and computational engineering. Despite its meticulous design, the underlying hardware fabrics fueling AI systems are based on decades-old computing principles using Boolean transistor switches. Although transistors have scaled from planar to 3D, the basic synchronous digital computing paradigm based on von-Neumann architecture has remained unaltered. Moreover, transistor scaling, which has been the driving force behind the ever-improving performance of traditional digital systems is approaching its imminent demise. These factors have led to multiple bottlenecks in terms of memory-wall, energy-efficiency, throughput, and security concerns. As such, the vision of enabling \'Ubiquitous Intelligence\' cannot be achieved without mitigating the challenges mentioned above and embedding intelligent computations across high-end servers down to resource-constrained edge devices. In this talk, I will present two solutions to mitigate energy- and throughput- bottleneck based on emerging non-volatile technologies and also CMOS SRAM. In particular, I will discuss 1) voltage-controlled spin dynamics to achieve massively parallel in-memory Boolean computing, 3) embedding three terminal spin Hall device into standard SRAM cell to enable in-situ checkpointing and restore operations for intermittently powered devices 3) digital 8 transistor-SRAM bit-cells as multi-bit-analog dot product engine for AI acceleration. I will conclude the talk by presenting future research directions for beyond Moore-era AI computing.
Biography: Akhilesh Jaiswal is currently a Senior Research Engineer for GLOBALFOUNDRIES Worldwide Research Division. As a Senior Engineer he is responsible for 1) developing compact device model for MRAM based AI in-memory circuits 2) 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 under supervision of Prof. Kaushik Roy and Master\'s degree from University of Minnesota in May 2014. As a part of 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. Akhilesh was an intern with GF Differentiating Technology Lab, Malta, in summer of 2017 and with ARM Devices-Circuits-System Research Group, Austin, in summer 2018. He has authored over 25+ articles in journals and conferences and has 2 issued patents and 13 pending patents under USPTO.
Host: Professor Richard Leahy, firstname.lastname@example.org
Audiences: Everyone Is Invited
Contact: Mayumi Thrasher