ELE 523E
From NANOxCOMP H2020 Project
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!Lecture Slides !! Lecture Slides !! Lecture Slides !! Homeworks !! Presentations & Exams & Projects | !Lecture Slides !! Lecture Slides !! Lecture Slides !! Homeworks !! Presentations & Exams & Projects | ||
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− | | [[Media:ele523e-2016-fall-w1-introduction.pptx | W1: Introduction]] || | + | | [[Media:ele523e-2016-fall-w1-introduction.pptx | W1: Introduction]] || [[Media:ele523e-2016-fall-w5-nano-array-based-computing.pptx | W5: Nanoarray based Computing]] || || [[Media:ele523e-2016-fall-hw-01.pdf | Homework 1]] || |
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| [[Media:ele523e-2016-fall-w2-emerging-computing.pptx | W2: Emerging Computing]] || || || || | | [[Media:ele523e-2016-fall-w2-emerging-computing.pptx | W2: Emerging Computing]] || || || || |
Revision as of 11:57, 17 October 2016
Contents |
Announcements
- 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
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Grading
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Reference Books
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Policies
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Weekly Course Plan
Date
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Topic
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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 |
Weeks 4, 10/10/2016 | Molecular computing |
Weeks 5, 17/10/2016 | Computing with switching nano arrays |
Week 6, 24/10/2016 | Stochastic/Probabilistic computing |
Weeks 7, 31/10/2016 | Performance optimization for stochastic computing |
Week 8, 7/11/2016 | HOLIDAY, no class |
Week 9, 14/11/2016 | Approximate computing |
Weeks 10, 21/11/2016 | Defects and reliability in nanoelectronics |
Week 11, 28/11/2016 | Defect/variance tolerance techniques |
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 |
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W1: Introduction | W5: Nanoarray based Computing | Homework 1 | ||
W2: Emerging Computing | ||||
W3: Reversible Quantum Computing | ||||
W4: Molecular Computing |