ELE 523E

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| [[Media:ele523e-2021-fall-w2-emerging-computing.pptx | W2: Emerging Computing]]  ||  [[Media:ele523e-2021-fall-w6-probabilistic-approximate-computing.pptx | W6-W7: Probabilistic and Approximate Computing]]  ||  [[Media:ele523e-2021-fall-hw-02.pdf | Homework 2]]  ||   
 
| [[Media:ele523e-2021-fall-w2-emerging-computing.pptx | W2: Emerging Computing]]  ||  [[Media:ele523e-2021-fall-w6-probabilistic-approximate-computing.pptx | W6-W7: Probabilistic and Approximate Computing]]  ||  [[Media:ele523e-2021-fall-hw-02.pdf | Homework 2]]  ||   
 
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| [[Media:ele523e-2021-fall-w3-reversible-quantum-computing.pptx | W3: Reversible Quantum Computing]]  ||    ||  [[Media:ele523e-2021-fall-hw-03.pdf | Homework 3]]  ||
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| [[Media:ele523e-2021-fall-w3-reversible-quantum-computing.pptx | W3: Reversible Quantum Computing]]  ||    ||  [[Media:ele523e-2021-fall-hw-03.pdf | Homework 3]]  ||   [[Media:ele523e-2021-fall-w8-fault-analysis-tolerance.pptx | W8-W9: Fault Analysis and Tolerance]]
 
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| [[Media:ele523e-2021-fall-w4-molecular-computing.pptx | W4: Molecular Computing]]  ||    ||    ||   
 
| [[Media:ele523e-2021-fall-w4-molecular-computing.pptx | W4: Molecular Computing]]  ||    ||    ||   
 
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Revision as of 09:01, 29 November 2021

Contents

Announcements

  • Nov. 15th The third homework has been posted that is due 29/11/2020 before 13:30.
  • Oct. 31st The second homework has been posted that is due 15/11/2020 before 13:30.
  • Oct. 18th The first homework has been posted that is due 1/11/2021 before 13:30.
  • Oct. 7th The class is given in the room 5103 (first floor), EEF.

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: 12840, Mondays 13:30-16:30, Room: EEB 5103, Fall 2021.
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, 4/10/2021 Introduction
Week 2, 11/10/2021 Overview of emerging nanoscale devices and switches
Week 3, 18/10/2021 Reversible quantum computing, reversible circuit analysis and synthesis
Week 4, 25/10/2021 Molecular computing with individual molecules and DNA strand displacement
Week 5, 1/11/2021 Computing and logic synthesis with switching nano arrays including memristor arrays
Week 6, 8/11/2021 Probabilistic/Stochastic and approximate computing
Week 7, 15/11/2021 Probabilistic/Stochastic and approximate computing
Week 8, 22/11/2021 HOLIDAY!
Week 9, 29/11/2021 Defects, faults, errors, and their analysis and tolerance
Week 10, 6/12/2021 Overview of presentation schedule
Week 11, 13/12/2021 Student presentations
Week 12, 20/12/2021 Student presentations
Week 13, 27/12/2021 Student presentations
Week 14, 3/1/2022 Student presentations
Week 15, 10/1/2022 Final project questions and answers

Course Materials

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