ELE 523E: Computational Nanoelectronics

Announcements

• Dec. 6th Presentation rules and schedule have been posted.
• Dec. 12th The fourth homework has been posted that is due 28/12/2020 before 13:30.
• Nov. 30th The third homework has been posted that is due 14/12/2020 before 13:30.
• Nov. 16th The second homework has been posted that is due 30/11/2020 before 13:30.
• Nov. 2nd The first homework has been posted that is due 16/11/2020 before 13:30.
• Oct. 19th Lectures are given online using Zoom that can be accessed via Ninova.

Overview

As current CMOS based technologies are approaching their anticipated limits, emerging nanotechnologies and new computing paradigms are expected to be used in future electronic circuits. This course overviews nanoelectronic circuits in a comparison with those of conventional CMOS-based. Deterministic and probobalistic emerging computing models as well as related algorithms and CAD tools are investigated. Regarding the interdisciplinary nature of emerging technologies, this course is appropriate for graduate students in different majors including electronics engineering, control engineering, computer science, applied physics, and mathematics. No prior course is required; only basic (college-level) knowledge in circuit design and mathematics is assumed. Topics that are covered include:

• Circuit elements and devices in computational nanoelectronics (in comparison with CMOS) including nano-crossbar and memristor switches, reversible quantum gates, approximate circuits and systems, and emerging transistors.
• Introduction of emerging computing models and algorithms in circuit level.
• Analysis and synthesis of deterministic and probabilistic computing paradigms.
• Performance of the computing models regarding area, power, speed, and accuracy.
• Uncertainty and faults: fault analysis and tolerance techniques for permanent and transient faults.

Syllabus

ELE 523E: Computational Nanoelectronics, CRN: 13449, Mondays 13:30-16:30, Online using Zoom via Ninova, Fall 2020.

Instructor	Mustafa Altun Email: altunmus@itu.edu.tr Tel: 02122856635 Office hours: 14:00 – 15:00 on Wednesdays in Room:3005, EEF (or stop by my office any time)
Grading	Homework: 40% 4 homeworks (10% each) Presentation: 20% Presentations are made individually or in groups depending on class size. Presentation topics will be posted. Final Project: 40%
Reference Books	Adamatzky, A. (Ed.). (2016). Advances in Unconventional Computing: Volume 1: Theory (Vol. 22). Springer. Waser, R. (2012). Nanoelectronics and information technology. John Wiley & Sons. Iniewski, K. (2010). Nanoelectronics: nanowires, molecular electronics, and nanodevices. McGraw Hill Professional. Stanisavljević, M., Schmid, M, Leblebici, Y. (2010). Reliability of Nanoscale Circuits and Systems: Methodologies and Circuit Architectures, Springer. Adamatzky, A., Bull, L., Costello, B. L., Stepney, S., Teuscher, C. (2007). Unconventional Computing, Luniver Press. Zomaya, Y. (2006). Handbook of Nature-Inspired and Innovative Computing: Integrating Classical Models with Emerging Technologies, Springer. Yanushkevich, S., Shmerko, V., Lyshevski, S. (2005). Logic Design of NanoICs, CRC Press.
Policies	Homeworks are due at the beginning of class. Late homeworks will be downgraded by 20% for each day passed the due date. Collaboration is permitted and encouraged for homeworks, but each collaborator should turn in his/her own answers. Collaboration is not permitted for the final project.

Weekly Course Plan

Date	Topic
Week 1, 19/10/2020	Introduction
Week 2, 26/10/2020	Overview of emerging nanoscale devices and switches
Week 3, 2/11/2020	Reversible quantum computing, reversible circuit analysis and synthesis
Week 4, 9/11/2020	Molecular computing with individual molecules and DNA strand displacement
Week 5, 16/11/2020	Computing and logic synthesis with switching nano arrays including memristor arrays
Week 6, 23/11/2020	Probabilistic/Stochastic and approximate computing
Week 7, 30/11/2020	Probabilistic/Stochastic and approximate computing
Week 8, 7/12/2020	Defects, faults, errors, and their analysis and tolerance
Week 9, 14/12/2020	Overview of presentation schedule
Week 10, 21/12/2020	Student presentations
Week 11, 28/12/2020	Student presentations
Week 12, 4/1/2021	Student presentations
Week 13, 11/1/2021	Student presentations
Week 14, 18/1/2021	Final project questions and answers

Course Materials

Lecture Slides	Lecture Slides	Homeworks	Presentations & Exams & Projects
W1: Introduction	W5: Nanoarray based Computing	Homework 1	Presentation Rules and Topics
W2: Emerging Computing	W6-W7: Probabilistic and Approximate Computing	Homework 2
W3: Reversible Quantum Computing	W8-W9: Fault Analysis and Tolerance	Homework 3
W4: Molecular Computing		Homework 4