ELE 523E

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| [[Media:ele523e-2016-fall-w2-emerging-computing.pptx | W2: Emerging Computing]]  ||  [[Media:ele523e-2016-fall-w6-probabilistic-computing.pptx | W6: Probabilistic Computing]]  ||  || [[Media:ele523e-2016-fall-hw-02.pdf | Homework 2]]  ||  
 
| [[Media:ele523e-2016-fall-w2-emerging-computing.pptx | W2: Emerging Computing]]  ||  [[Media:ele523e-2016-fall-w6-probabilistic-computing.pptx | W6: Probabilistic Computing]]  ||  || [[Media:ele523e-2016-fall-hw-02.pdf | Homework 2]]  ||  
 
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| [[Media:ele523e-2016-fall-w3-reversible-quantum-computing.pptx | W3: Reversible Quantum Computing]]  ||  [[Media:ele523e-2016-fall-w7-approximate-computing-and-Bayesian-networks.pptx | W7: Approximate Computing and Bayesian Networks]]  ||  || [[Media:ele523e-2016-fall-hw-03.pdf | Homework 3]] ||  
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| [[Media:ele523e-2016-fall-w3-reversible-quantum-computing.pptx | W3: Reversible Quantum Computing]]  ||  [[Media:ele523e-2016-fall-w7-approximate-computing-and-Bayesian-networks.pptx | W7: Approximate Computing & Bayesian Networks]]  ||  || [[Media:ele523e-2016-fall-hw-03.pdf | Homework 3]] ||  
 
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|  [[Media:ele523e-2016-fall-w4-molecular-computing.pptx | W4: Molecular Computing]]  ||    ||  ||  ||  
 
|  [[Media:ele523e-2016-fall-w4-molecular-computing.pptx | W4: Molecular Computing]]  ||    ||  ||  ||  
 
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Revision as of 22:57, 8 November 2016

Contents

Announcements

  • Oct. 30th The third homework has been posted that is due 21/11/2016 before 13:30.
  • Oct. 26th To see your grades click here.
  • Oct. 17th The second homework has been posted that is due 31/10/2016 before 13:30.
  • Oct. 2nd The first homework has been posted that is due 17/10/2016 before 13:30.
  • Sept. 19th The class is given in the room Z2 (ground floor), EEF.

Overview

As current CMOS based technologies are approaching their anticipated limits, emerging nanotechnologies are expected to replace their role in electronic circuits. This course overviews nanoelectronic circuits in a comparison with those of conventional CMOS-based. Deterministic and probobalistic emerging computing models 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 switches, reversible quantum gates, approximate circuits and systems, and emerging transistors.
  • Introduction of emerging computing models in circuit level.
  • Analysis and synthesis of deterministic and probabilistic models.
  • Performance of the computing models regarding area, power, speed, and accuracy.
  • Uncertainty and defects: defect tolerance techniques for permanent and transient errors.

Syllabus

ELE 523E: Computational Nanoelectronics, CRN: 15371, Mondays 13:30-16:30, Room: Z2 (Ground Floor-EEF), Fall 2016.
Instructor

Mustafa Altun

  • Email: altunmus@itu.edu.tr
  • Tel: 02122856635
  • Office hours: 14:00 – 15:00 on Tuesdays in Room:3005, EEF (or stop by my office any time)
Grading
  • Homework: 20%
    • 4 homeworks (5% each)
  • Midterm Exam: 20%
    • The midterm is during the lecture time on 6/12/2016.
  • Presentation: 20%
    • Presentations are made individually or in groups depending on class size.
    • Presentation topics will be posted.
  • Final Project: 40%
Reference Books
  • 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.
  • The midterm is in closed-notes and closed-books format.
  • Collaboration is not permitted for the final project.

Weekly Course Plan

Date
Topic
Week 1, 19/9/2016 Introduction
Week 2, 26/9/2016 Overview of emerging nanoscale devices and switches
Week 3, 3/10/2016 Reversible quantum computing, reversible circuit analysis and synthesis
Weeks 4, 10/10/2016 Molecular computing with individual molecules and DNA strand displacement
Weeks 5, 17/10/2016 Computing and logic synthesis with switching nano arrays
Week 6, 24/10/2016 Probabilistic/Stochastic computing with random bit streams and probabilistic switches
Weeks 7, 31/10/2016 Approximate computing and Bayesian networks
Week 8, 7/11/2016 HOLIDAY, no class
Week 9, 14/11/2016 Defects, faults, errors, and reliability in nanoelectronics
Weeks 10, 21/11/2016 Post-fabrication tolerance techniques for permanent defects
Week 11, 28/11/2016 In field tolerance techniques for transient faults
Week 12, 6/12/2016 MIDTERM
Weeks 13, 13/12/2016 Overview of the midterm, the presentation schedule, and the final project
Weeks 14, 20/12/2016 Student presentations
Weeks 15, 27/12/2016 Student presentations

Course Materials

Lecture Slides Lecture Slides Lecture Slides Homeworks Presentations & Exams & Projects
W1: Introduction W5: Nanoarray based Computing Homework 1
W2: Emerging Computing W6: Probabilistic Computing Homework 2
W3: Reversible Quantum Computing W7: Approximate Computing & Bayesian Networks Homework 3
W4: Molecular Computing
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