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DDECS 2021 - April 7-9 2021
Vienna, Austria

24th International Symposium on Design and Diagnostics of Electronic Circuits and Systems

The International Symposium on Design and Diagnostics of Electronic Circuits and Systems (DDECS’2021) provides a forum for exchanging ideas, discussing research results, and presenting practical applications in the areas of design, test, and diagnosis of microelectronic digital, analog, and mixed-signal circuits and systems. The 24th symposium will be hosted as an online event by TU Wien in Vienna, Austria.

Announcements

Keynotes

We are pleased to announce that the keynotes at DDECS'2021 will be given by Prof. Kaushik Roy (Purdue University, US), Prof. Yiorgos Makris (UT Dallas, US) and Rob Aitken (Fellow & Director of Technology, ARM).

Re-Engineering Computing with Neuro-Inspired Learning: Devices, Circuits, and Systems
Prof. Kaushik Roy, Purdue University, US

Abstract - Advances in machine learning, notably deep learning, have led to computers matching or surpassing human performance in several cognitive tasks including vision, speech and natural language processing. However, implementation of such neural algorithms in conventional "von-Neumann" architectures are several orders of magnitude more area and power expensive than the biological brain. Hence, we need fundamentally new approaches to sustain exponential growth in performance at high energy-efficiency beyond the end of the CMOS roadmap in the era of ‘data deluge’ and emergent data-centric applications. Exploring the new paradigm of computing necessitates a multi-disciplinary approach: exploration of new learning algorithms inspired from neuroscientific principles, developing network architectures best suited for such algorithms, new hardware techniques to achieve orders of improvement in energy consumption, and nanoscale devices that can closely mimic the neuronal and synaptic operations of the brain leading to a better match between the hardware substrate and the model of computation. In this talk, I will focus on our recent works on neuromorphic computing with spike based learning and the design of underlying hardware that can lead to quantum improvements in energy efficiency with good accuracy.

Speaker Biography - Kaushik Roy received B.Tech. degree in electronics and electrical communications engineering from the Indian Institute of Technology, Kharagpur, India, and Ph.D. degree from the electrical and computer engineering department of the University of Illinois at Urbana-Champaign in 1990. He was with the Semiconductor Process and Design Center of Texas Instruments, Dallas, where he worked on FPGA architecture development and low-power circuit design. He joined the electrical and computer engineering faculty at Purdue University, West Lafayette, IN, in 1993, where he is currently Edward G. Tiedemann Jr. Distinguished Professor. He also the director of the center for brain-inspired computing (C-BRIC) funded by SRC/DARPA. His research interests include neuromorphic and emerging computing models, neuro-mimetic devices, spintronics, device-circuit-algorithm co-design for nano-scale Silicon and non-Silicon technologies, and low-power electronics. Dr. Roy has published more than 700 papers in refereed journals and conferences, holds 25 patents, supervised 90 PhD dissertations, and is co-author of two books on Low Power CMOS VLSI Design (John Wiley & McGraw Hill). Dr. Roy received the National Science Foundation Career Development Award in 1995, IBM faculty partnership award, ATT/Lucent Foundation award, 2005 SRC Technical Excellence Award, SRC Inventors Award, Purdue College of Engineering Research Excellence Award, Humboldt Research Award in 2010, 2010 IEEE Circuits and Systems Society Technical Achievement Award (Charles Desoer Award), Distinguished Alumnus Award from Indian Institute of Technology (IIT), Kharagpur, Fulbright-Nehru Distinguished Chair, DoD Vannevar Bush Faculty Fellow (2014-2019), Semiconductor Research Corporation Aristotle award in 2015, and best paper awards at 1997 International Test Conference, IEEE 2000 International Symposium on Quality of IC Design, 2003 IEEE Latin American Test Workshop, 2003 IEEE Nano, 2004 IEEE International Conference on Computer Design, 2006 IEEE/ACM International Symposium on Low Power Electronics & Design, and 2005 IEEE Circuits and system society Outstanding Young Author Award (Chris Kim), 2006 IEEE Transactions on VLSI Systems best paper award, 2012 ACM/IEEE International Symposium on Low Power Electronics and Design best paper award, 2013 IEEE Transactions on VLSI Best paper award. Dr. Roy was a Purdue University Faculty Scholar (1998-2003). He was a Research Visionary Board Member of Motorola Labs (2002) and held the M. Gandhi Distinguished Visiting faculty at Indian Institute of Technology (Bombay) and Global Foundries visiting Chair at National University of Singapore. He has been in the editorial board of IEEE Design and Test, IEEE Transactions on Circuits and Systems, IEEE Transactions on VLSI Systems, and IEEE Transactions on Electron Devices. He was Guest Editor for Special Issue on Low-Power VLSI in the IEEE Design and Test (1994) and IEEE Transactions on VLSI Systems (June 2000), IEE Proceedings -- Computers and Digital Techniques (July 2002), and IEEE Journal on Emerging and Selected Topics in Circuits and Systems (2011). Dr. Roy is a fellow of IEEE.

Applications of Machine Learning in Test: Fallacies, Pitfalls and Marching Orders
Prof. Yiorgos Makris, Electrical and Computer Engineering Department, UT Dallas

Abstract - While many applications of machine learning in various semiconductor manufacturing and test tasks have been heavily researched over the last two decades, few have actually seen the light of day in a real production environment. Recently, the popularity of contemporary artificial intelligence methods, such as deep learning, has reignited the enthusiasm and reinvigorated the discussion regarding the potential of statistical and machine learning-based solutions toward reducing test cost, increasing test quality, improving yield and test floor logistics, as well as providing guidance to designers and process engineers alike. In this presentation, I will discuss the lessons we have learned during 15 years of interactions between academia and industry in developing machine learning-based semiconductor manufacturing and test solutions and I will review the key challenges that we have encountered both in demonstrating and in transitioning such solutions from a research to a production environment. Organized around various fallacies that are prevalent in the community regarding the application of traditional or contemporary machine learning methods in this context, as well as the pitfalls that have given rise to these fallacies, the ultimate intention of this presentation is to draw attention to the true operational challenges involved and to suggest efforts which can enable and expedite industrial deployment.

Speaker Biography - Yiorgos Makris received the Diploma of Computer Engineering from the University of Patras, Greece, in 1995 and the M.S. and Ph.D. degrees in Computer Engineering from the University of California, San Diego, in 1998 and 2001, respectively. After spending a decade on the faculty of Yale University, he joined UT Dallas where he is now a Professor of Electrical and Computer Engineering, the Co-Founder and Site-PI of the NSF Industry University Cooperative Research Center on Hardware and Embedded System Security and Trust (NSF CHEST I/UCRC), as well as the Leader of the Safety, Security and Healthcare Thrust of the Texas Analog Center of Excellence (TxACE) and the Director of the Trusted and RELiable Architectures (TRELA) Research Laboratory. His research focuses on applications of machine learning and statistical analysis in the development of trusted and reliable integrated circuits and systems, with particular emphasis in the analog/RF domain. He serves as an Associate Editor of the IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems and has served as an Associate Editor for the IEEE Information Forensics and Security and the IEEE Design & Test of Computers Periodical, as a guest editor for the IEEE Transactions on Computers and the IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems. He also served as the 2016-2017 general chair and the 2013-2014 program chair of the IEEE VLSI Test Symposium. He is a recipient of the 2006 Sheffield Distinguished Teaching Award, Best Paper Awards from the 2013 IEEE/ACM Design Automation and Test in Europe (DATE'13) conference and the 2015 IEEE VLSI Test Symposium (VTS'15), as well as Best Hardware Demonstration Awards from the 2016 and the 2018 IEEE Hardware-Oriented Security and Trust Symposia (HOST'16 and HOST'18) and a recipient of the 2020 Faculty Research Award from the Erik Jonsson School of Engineering and Computer Science at UT Dallas.

Dependable Computing in an Era of Unreliable Devices
Rob Aitken, Fellow & Director of Technology, ARM

Abstract - After a half century of CMOS, designers understand the inherent tradeoffs between dependability and resilience on one hand and performance, power and area on the other. As Moore’s law slows down, new devices and technologies are being proposed as alternatives to CMOS in both logic and memory design, and many of these have inherent dependability challenges. This talk looks at existing approaches in light of these new challenges and discusses possible ways forward.

Speaker Biography - Rob Aitken is an Arm Fellow and Director of Technology for Arm Research. His responsibilities include developing Arm’s research agenda, including identifying disruptive technologies, monitoring the global technology landscape, and coordinating research efforts within and outside of Arm. His research interests include emerging technologies, memory design, design for variability, resilient computing, and statistical design. He has published over 100 technical papers on a wide range of topics and holds over 40 US patents. Dr. Aitken joined Arm as part of its acquisition of Artisan Components in 2004. He holds a Ph.D. from McGill University in Canada. Dr. Aitken is an IEEE Fellow.

Special Sessions

Deep Learning 2.0: an Approximate way to Efficient, Secure and Reliable solutions

organized by
Alberto Bosio, University of Lyon, France

In the recent years, Approximate Computing (AxC) has become a major field of research to improve both speed and energy consumption in embedded and high-performance systems. By relaxing the need for fully precise or completely deterministic operations, approximate computing substantially improves energy efficiency. Convolutional Neural Networks (CNNs) show inherent resilience to insignificant errors due to their iterative nature and learning process. Therefore, an intrinsic tolerance to inexact computation is evidenced, and using the approximate computing paradigm to improve power and delay characteristics is therefore relevant. Indeed, CNNs lend well with AxC techniques. However, whereas AxC is widely adopted for achieving energy efficiency, its use for safety-critical applications has been investigated by only few recent works. The non-trivial question that this special session intends to answer is “How introducing errors during computation can indeed lead to a more secure and reliable application?”. The session will thus present different applications of AxC to design and implement efficient, secure and reliable high computing demanding applications such as the case of Deep Learning.

Logic synthesis and verification for emerging technologies

organized by
Petr Fiser, Czech Technical University in Prague, Czech Republic

Not many years ago, logic synthesis seemed to be an already resolved topic, and it appeared that no significant progress could be made in this field anymore. However, things have changed when “emerging technologies” came to play. Novel technology nodes with their unique properties are inexorably being discovered every year, encouraging researchers to devise novel synthesis algorithms tailored to these technologies. Logic primitives like XOR or majority gates, which used to be prohibitive because of their size in CMOS, now become of increasing interest because of their efficient implementation in nanotechnologies. Memristors have been successfully manufactured in the recent past, bringing an entirely new view on logic synthesis. This special session is focused on logic synthesis and verification algorithms, intended especially (but not only) for such technologies.

Committee

Organizing Committee

General Chair

Muhammad Shafique, NYU Abu Dhabi, UAE

General Vice Chairs

Andreas Steininger, TU Wien, Austria

Goran Stojanović, University of Novi Sad, Serbia

Program Chairs

Lukáš Sekanina, Brno University of Technology, Czech Republic

Miloš Krstić, IHP and University Potsdam, Germany

Publication Chair

Vojtěch Mrázek, Brno University of Technology, Czech Republic

Topic Chairs

Adrijan Barić, University of Zagreb, Croatia

Matthias Függer, CNRS & LSV, ENS Paris-Saclay & Inria, France

Jie Han, University of Alberta, Canada

Mottaqiallah Taouil, TU Delft, Netherlands

Finance Chair

Jürgen Maier, TU Wien, Austria

Registration Chair

Traude Sommer, TU Wien, Austria

Local Arrangements Chairs

Florian Huemer, TU Wien, Austria

Florian Kriebel, TU Wien, Austria

Program Committee

Adrijan Baric, University of Zagreb, Croatia

Cristiana Bolchini, Politecnico di Milano, Italy

Alberto Bosio, University of Lyon, France

Luca Cassano, Politecnico di Milano, Italy

Maciej Ciesielski, Univ. of Massachusetts, USA

Gyorgy Cserey, Pazmany Peter Catholic University, Hungary

Mirjana Damnjanovic, University of Novi Sad, Serbia

Martin Danek, daiteq s.r.o., Czech Republic

Stanisław Deniziak, Kielce University of Technology, Poland

Manfred Dietrich, Dikuli Unternehmensberatung, Germany

Rolf Drechsler, University of Bremen/DFKI, Germany

Milos Drutarovsky, Technical University of Kosice, Slovakia

Peeter Ellervee, Tallinn University of Technology, Estonia

Marius Enachescu, University Politehnica Bucharest, Romania

Goerschwin Fey, TU Hamburg, Germany

Petr Fiser, Czech Technical University in Prague, Czech Republic

Matthias Fuegger, CNRS & LSV, ENS Paris-Saclay

Tomasz Garbolino, Silesian University of Technology, Poland

Patrick Girard, LIRMM/CNRS, France

Jie Han, University of Alberta, Canada

Sybille Hellebrand, Paderborn University, Germany

Katarina Jelemenska, FIIT STU Bratislava, Slovakia

Maksim Jenihhin, Tallinn University of Technology, Estonia

Dominik Kasprowicz, Warsaw University of Technology, Poland

Martin Keim, Mentor, A Siemens Business

Milos Krstic, IHP, Germany

Hana Kubatova, CTU in Prague, Czech Republic

Wieslaw Kuzmicz, Warsaw University of Technology, Poland

Erik Larsson, Lund University, Sweden

Gildas Leger, Universidad de Sevilla, Spain

Regis Leveugle, Grenoble INP, France

Dominik Macko, Slovak University of Technology, Slovakia

Paolo Maistri, TIMA, France

Hans Manhaeve, Ridgetop Europe, Belgium

Tetsuya Matsumura, Nihon University, Japan

Liviu-Cristian Miclea, Technical University of Cluj-Napoca, Romania

Farshad Moradi, Aarhus University, DK

Lukas Nagy, Slovak University of Technology, Slovakia

Ondrej Novak, TU Liberec, Czech Republic

Marco Ottavi, University of Rome Tor Vergata, Italy

Andras Pataricza, Budapest University of Technology and Economics, Hungary

Zebo Peng, Linkoping University, Sweden

Laurence Pierre, University Grenoble Alpes, France

Stanislaw J. Piestrak, University de Lorraine - Institut Jean Lamour, France

Witold Pleskacz, Warsaw University of Technology, Poland

Thomas Polzer, UAS Technikum Wien, Austria

Michele Portolan, INP Grenoble, France

Paolo Prinetto, Politecnico di Torino, Italy

Zbynek Raida, Brno University of Technology, Czech Republic

Jaan Raik, Tallinn University of Technology, Estonia

Bruno Rouzeyre, University Montpellier, France

Richard Ruzicka, Brno University of Technology, Czech Republic

Sebastian M. Sattler, Friedrich-Alexander-University Erlangen-Nuremberg, Germany

Mario Schölzel, University of Applied Science Nordhausen, Germany

Lukas Sekanina, Brno University of Technology, Czech Republic

Muhammad Shafique, NYU, UAE

Matteo Sonza Reorda, Politecnico di Torino, Italy

Janusz Sosnowski, Warsaw University of Technology, Poland

Zoran Stamenkovic, IHP - Leibniz-Institut für Innovative Mikroelektronik, Germany

Andreas Steininger, Vienna University of Technology, Austria

Goran Stojanovic, University of Novi Sad, Serbia

Viera Stopjakova, Slovak University of Technology, Slovakia

Ondrej Subrt, ASICentrum, Czech Republic

Kalle Tammemae, Tallinn University of Technology, Estonia

Mottaqiallah Taouil, Delft University of Technology, Netherlands

Paulo Teixeira, INESC.ID Lisboa, Portugal

Raimund Ubar, Tallinn University of Technology, Estonia

Mihai Udrescu, University Politehnica of Timisoara, Romania

Markus Ulbricht, IHP, Germany

Elena Ioana Vatajelu, TIMA/CNRS de Grenoble-Alpes, France

Diego Vazquez, Instituto de Microelectr¢nica de Sevilla / Universidad de Sevilla, Spain

Federico Venini, Xilinx, USA

Arnaud Virazel, LIRMM, France

Robert Wille, Johannes Kepler University Linz, Austria

Hans-Joachim Wunderlich, University of Stuttgart, Germany

Mustafa Berke Yelten, Istanbul Technical University, Turkey

Yervant Zorian, Synopsys, USA

Call for Papers

DDECS’2021 provides a forum for exchanging ideas, discussing research results, and presenting practical applications in the areas of design, test, and diagnosis of microelectronic digital, analog, and mixed-signal circuits and systems. The topics include the following but are not limited to:

  • Emerging Technologies
  • Wireless Communication Systems
  • Embedded Systems
  • Dependable Systems
  • Embedded Hardware for AI
  • Approximate Computing
  • Formal Methods in System Design
  • Hardware/Software Co-Design
  • IP-Based Design
  • ASIC/FPGA Design
  • Internet-of-Things Design and Test
  • SoC and NoC Design and Test
  • Digital Circuits Design and Test
  • RF, Analog, and Mixed-Signal Circuits Design and Test
  • Memory Design and Test
  • MEMS Design and Test

  • On-Line Testing
  • Built-in Self-Test and Self-Repair
  • Design for Testability and Diagnosis
  • Defect/Fault Tolerance and Reliability
  • Design and Test in Nano-Technologies
  • ATE Hardware and Software
  • Physical Failure Analysis
  • Debug and Diagnosis
  • Hardware Security and Trust
  • Flexible and Printed Electronics
  • Automotive Electronics
  • Medical Electronics
  • AI in Design and Test of Circuits
  • Stretchable and Textile Electronics
  • Sensors and Transducers
  • Integrated Passive Components
  • Microfluidic Electronic Devices

Download PDF Version

Author Information

You may now submit a contribution for DDECS'2021. Please select a type of contribution. Remember to click the "Complete Submission" button on the second screen! Accepted papers will be included in the Symposium Proceedings. Accepted papers will be submitted for inclusion into IEEE Xplore subject to meeting IEEE Xplore’s scope and quality requirements.

Types of Submissions

Regular Paper

A paper presenting an original and novel scientific content (maximum 6 pages in the IEEE two-column format).

Industrial Paper

The paper is submitted from an industrial sector, possibly as a joint work with research institutes and it has the character of industrial results, e.g. a real chip design, fabrication defects analysis, a new design and/or test technique used in company, design and/or test problems that need to be solved, etc. The paper should have at most 6 pages in the IEEE two-column format.

Student Paper

A paper presenting results of a student's PhD or master work. In order to be eligible as a student paper, the first author has to be the student (or more than one student in case of joint work), and the second author the advisor. The accepted paper has to be presented by the student. The paper should have at most 4 pages in the IEEE two-column format.

Embedded Tutorial

Accepted tutorials will be embedded into the program. Authors should submit their proposal in the form of an extended abstract together with a short CV (max. 3 pages).

Work-in-progress Paper

A paper presenting a new research in progress, evolving ideas, novel research directions, and/or experimental research, early results. The paper should have at most 4 pages in the IEEE two-column format. The accepted papers will not be included in IEEE Xplore.

Format and Paper Template

All papers for DDECS'2021 must be submitted in English and use the two-column format template for conferences provided by the IEEE (link).
Each paper submitted to a special session has to be a Regular Paper. Please add a short comment “This paper is submitted to Special Session on [special_session_title]” to the “Remarks on This Contribution” field on the submission page.

Student Grants

Student grants will be available. Details about how to apply will be available soon.

Important Dates

Abstract Registration

January 11, 2021
January 20, 2021
February 5, 2021

Paper Submission

January 18, 2021
January 31, 2021
February 5, 2021

Notification of Acceptance

March 21, 2021

Publication Ready Version Submission

TBA ...

Submit a Paper

Our Sponsors

Contact/Impressum

Institute of Computer Engineering - TU Wien
Embedded Computing Systems Group [link]
Treitlstasse 3, 2nd floor, A-1040 Wien (Austria) [Google Maps]
Phone: +43(1)58801-18203
Email: info@ddecs2021.wien