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ICSRL

Integrated Circuits & Systems Research Lab
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Research

 

The overall research goal in ICSRL is to comprehend the mathematical and physical models that govern nature and our interactions with it. Engineering, has always been the application of man’s understanding of natural sciences to design systems that enable a better tomorrow. In our lab, we endeavor to explore such models of information processing and computation, as well as to design hardware solutions to physically realize them.

Energy-efficient Hardware for Autonomous Systems, Machine Learning and Smart Sensing

We explore mixed-signal hardware that can enable the next generation of autonomy in intelligent systems. We have pioneered computational data-converters that can perform in-situ classification on voltage as well as time-based ADCs. Our current work encompasses hardware solutions for voltage and process scalability, memory-centric processing and low-cost interconnect technologies for supervised, unsupervised and reinforcement based learning. We collaborate with device and technology researchers to understand how post-CMOS devices can enable next-generation of autonomous and intelligent systems. We have demonstrated world’s first hardware for reinforcement learning at sub-1mW targeted for autonomous robots. Our work on “always-on” smart cameras has been widely covered by media outlets including Wired, Engadget and TechCrunch.

Key Publications: [ISSCC 2018][Symp. of VLSI Technology 2017][ASSCC 2017][BioCAS 2017][TCAS-I 2017][TCAS-II 2016][IEDM 2014]

Design of Voltage Regulators, Adaptive Clocking, and Power Management

This project explores the design of on-die power management circuits with novel voltage-regulator architectures that are suited for digital logic. The focus of the work is to develop control architectures and corresponding hardware implementations that provide stability and performance across wide dynamic ranges of operation. Our principle interests are in linear and switched capacitor regulator topologies that are compact, low overhead and highly efficient.

Key Publications: [JSSC 2018][ESSCIRC 2016][ESSCIRC 2016][ISSCC 2015][JSSC 2014][Symp. on VLSI Circuits 2012]

Computation with Non-linear Dynamical Systems

While Boolean, Von-Neumann machines have fueled the technology revolution over the last three decades, it is well recognized that brain-inspired computational models are well suited for tasks such as data classification and recognition. Our current work is at the interface of non-linear dynamics exhibited by correlated electron devices and the computational models that are made possible by such complex systems. We are engaged in active research in the “information processing” capabilities of non-linear dynamical systems where the dynamics of synchronous oscillators are stimulated, controlled and observed; and can be shown to perform tasks such as associative matching. Our work on non-linear dynamical systems that connect dynamics with algebraic graph theory has been widely covered by media outlets including Phys.Org, Engadget and TechCrunch.

Key Publications: [Nature SR 2017][Journal of Applied Physics 2015][IEDM 2014][Nature 2017] [JETCAS 2014][DAC 2014]

Energy vs Accuracy: Computational Models and Hardware for Sensors, Sensor Interfaces and Signal Processing

Designing CMOS based sensors, sensor interfaces and low-power processing of sensor data is of interest not only for environmental sensing but also for advanced human-machine interfaces. We are interested in the design and applications of on-chip sensors like temperature, voltage, and current sensors as well as in building platform sensors (audio and video) that will enable seamless interaction of human and machines. Currently, we are exploring novel hardware concepts in compressive sensing, random sampling and processing in reduced dimensions with a focus towards approximate computation. This includes understanding and exploring mathematical models as well as physical realization of such models in digital and mixed signal domains.

Key Publications: [ISSCC 2009] [JSSC 2009] [CICC 2012]

Spintronics: Beyond Charge Based Computation and Storage

Prof. Raychowdhury is an expert on device modeling, compact modeling, circuit design, and test architectures for Spin-Transfer-Torque based Magnetic RAMs (STT-MRAMs). Our research group is exploring improved device models for fast evaluation of process parameter variation in STT-MRAM with a focus towards different failure models. Current work includes identifying circuit architectures and test generation methods for designing and characterizing robust STT-RAM arrays in embedded designs. More recently, we have been exploring the application of Spintronic devices in analog and mixed signal computation.

Key Publications: [IEDM 2009] [IEDM 2010] [IEDM 2011] [TED 2011]

Design of Low-Power Digital and Mixed-Signal Circuits with Emphasis on Adaptability and Resiliency

We are interested in exploiting the limits of low energy design with adaptation and resiliency against dynamic variations and errors. The aim is to minimize design guard-bands to ensure error free operation with a need for error detection and correction in case of rare failure events. We study circuits and architecture for both logic and embedded memory.

Key Publications: [JSSC 2011] [ISSCC 2011] [Symp. on VLSI Circuits 2010]

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ICSRL Highlights

Jan’19 – ICSRL to present two papers at CICC 2019. Congratulations to Insik and Muya!

Jan’19 – ICSRL received funding from Samsung Labs to research transfer learning on energy-constrained autonomous devices.

Dec’18 – Anvesha Amaravati successfully defends his thesis. Congratulations, Anvesha!! Anvesha join’s Qualcomm’s Corporate Research Devision upon graduation.

Dec’18 – Congratulations to Aqeel Anwar Malik for winning the Best Paper Award at M2VIP (Mechatronics and Machine Vision in Practice)! Aqeel’s paper is entitled: “NAVREN-RL: Learning to fly in real environment via end-to-end deep reinforcement learning using monocular images”.

Dec’18 – Congratulations to Brian Crafton for co-authoring a paper on FeFET-based neuromorphic computing at the International Electron Device Meeting (IEDM). The paper is based on collaborative work with the research groups of Prof. Asif Khan and Prof. Suman Datta.

Nov’18 – Anvesha’s paper on mixed-signal Reinforcement Leaning chip to appear on the Journal of Solid State Circuits (JSSC).

Oct’18 – ICSRL to present two papers at the International Solid State Circuits Conference (ISSCC), 2019. Congratulations to Ningyuan and Muya! One of the papers is based on joint work with Qualcomm.

Jun’18 – ICSRL wins research grant from SRC and DARPA to investigate hardware-aware machine learning algorithms!

Jul’18 – Dr. Raychowdhury has received the IEEE/ACM Design Automation Conference’s Innovator Under 40 Award for his contributions to the semiconductor industry. More specifically, Dr. Raychowdhury’s contribution to analog front-end circuits for Asymmetric DSL (at Texas Instruments Inc.) and Always-on Sensing Technologies (at Intel Corp.) have been recognized.

April'18 – Congratulations to Abhinav Parihar for winning the Chih Foundation Graduate Research Award!

March'18 – Dr. Raychowdhury has won the Georgia Tech Outstanding Faculty Award, 2018. Thanks to all the ICSRL team members (past and present) and congratulations to all the winners!

March'18 – Our paper on stochastic models for artificial IMT neurons is now accepted for publication in the Frontiers of Neurosciences. Congratulations to all the authors!

March'18 – Our paper on a reconfigurable LDO is accepted for publication in the IEEE Transactions on Circuits and Systems-II. Congratulations to all the authors!

March'18 – We have papers in the Transactions on Circuits and Systems-I and the Transactions on Industrial Electronics on hardware-assisted Machine Learning and Security for Edge Devices. Congratulations to all the authors!

Feb’18 – Our paper at ISSCC is covered by Electronicsweekly!

Feb’18 – We presented a paper and a demo at ISSCC 2018 on: “A 55nm Time-Domain Mixed-Signal Neuromorphic Accelerator with Stochastic Synapses and Embedded Reinforcement Learning for Autonomous Micro-Robots“. This is the first demonstration of RL in hardware at sub-1mW for edge-nodes. Congratulations to all the authors!

Dec’17 – Saad and Samantak successfully defend their theses. Congratulations!

Oct and Nov'17 - We will present three papers (A. Amravati and N. Cao) on energy-efficient machine learning hardware at the edge of the cloud at ASSCC, BioCAS and IEEE Sensors

Aug'17 - Prof. Arijit Raychowdhury wins the Best Paper Award for IEEE Transactions on Multi-Scale Computing Systems

Jul'17 - ISCRL wins multiple research grants from Qualcomm Inc., Semiconductor Research Corporation, AFOSR and National Science Foundation

Jun '17 - Our work on synthesizing dynamical systems to solve combinatorial optimization problems is published in Nature Scientific Reports and featured in ECE NEWS, PHYS.ORG, SCIENCE DAILY, ECN, SCIENTIFIC COMPUTING

Jun’17 – Ningyuan presents at the International Microwave Symposium (IMS)

May’17 – Saad wins the best paper award at the IEEE International Symposium on Hardware Oriented Security and Trust (HOST)

May, Jun, Jul ’17 – Multiple papers in IEEE Transactions on CAS (I and II) and Transactions on Computer Aided Design.

May '17 - Our CICC paper on a novel LDO technique resulting from collaborative research with our partners at Qualcomm's Research Lab draws widespread attention from industry researchers.

Feb'17 - Saad Bin Nasir wins the prestigious IEEE Solid State Circuits Society's Pre-Doctoral Research Award

Feb'17 - Samantak Gangopadhyay wins the IEEE Solid State Circuits Society's Travel Grant Award for ISSCC

Aug'16 - "Always On", Light-Powered, Gesture Recognizing Camera featured in WIRED, DIGITAL TRENDS, TECHCRUNCH, ENGADGET, YAHOO, NSF

Aug'16 - Two papers on Embedded Power Management to be presented at the European Solid State circuits Conference in Switzerland.

Sept'15 - Arijit Raychowdhury wins INTEL EARLY CAREER FACULTY AWARD.

Sept'15 - A. Amravati wins Best Paper Award in Analog/Mixed-Signal Track in IEEE VLSI-SoC Conference.

Dec'14 - S. Gangopadhyay and S. Nasir have entered the Finals of the Qualcomm Innovation Fellowship.

Dec'14 - Vision chip exploiting non-linear dynamics presented at IEDM 2014 (Joint work with Penn State).

Nov'14 - ICSRL receives research funding from Intel to work on control strategies for embedded voltage regulators

Oct'14 - Paper on all-digital LDOs accepted at ISSCC 2015.

Sep'14 - ICSRL receives research funding from Intel to work on Low Power Camera Systems

Jul'14 - Prof. Arijit Raychowdhury attended Microsoft Faculty Summit in Seattle

Jun'14 - Press coverage on Nature Scientific Report - Radio Interview and Press Release

May'14 - Collaborative work with Penn State and Cornell Universities published in "Nature Scientific Reports"

Mar'14 - ICSRL receives research funding from Qualcomm to work on Adaptive Control on VRs

Mar'14 - Paper presented at ISQED 2014

Mar'14 - Paper presented at DATE 2014

Feb'14 - SRC program on embedded VRs started

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