Unconventional computing

2023/2024
Programme:
Computer Science and Mathematics, Second Cycle
Year:
1 in 2 year
Semester:
first
Kind:
optional
ECTS:
6
Language:
slovenian, english
Course director:

Miha Mraz

Hours per week – 1. semester:
Lectures
3
Seminar
1.33
Tutorial
0.67
Lab
0
Prerequisites

There are no prerequisites.

Content (Syllabus outline)

Basic topics:
I. Unconventional processing platforms:
quantum dot cellular automata,
quantum computing,
MEMS/NEMS devices,
Optical computing
DNA processing,
nanotubes, etc.
II. Unconventional processing approaches:
amorphous computing,
reversible computing,
multistate and analogous computing,
bio inspired computing, etc.

Readings
  1. M.Mraz: Iskanje procesne platforme prihodnosti. https://ucilnica.fri.uni-lj.si/course/view.php?id=91. (e-book, 2017)
  2. F.Lombardi, J.Huang: Design and test of digital circuits by quantum-dot cellular automata, Artech House Inc., 2008
  3. U.Alon: An introduction to systems biology : design principles of biological circuits, Chapman &, Hall / CRC, 2007
Objectives and competences

The main goal of the course is to present recent unconventional methods and platforms for computer processing needs. The motivation for the course comes from the restrictions in the field of minimization of classical computer structures. Other competences:
The ability to define, understand and solve creative professional challenges in computer and information science,
The ability to search knowledge sources and to search for resources and critically evaluate information.

Intended learning outcomes

After the completion of the course a student:

  • will be able to objectively analyse the existing processing platforms and methods,
  • will be able to understand the concept of logic functions reversibility,
  • will be familiar with the concepts of distributed systems, such as cellular automata and quantum-dot cellular automata,
  • will understand and will be able to apply the concepts of a many-valued logic and processing in practice,
  • will understand the concepts of biological computing,
  • will understand the concepts of quantum computing,
  • will be able to solve problems on the basis of alternative processing methods.
Learning and teaching methods

Lectures, practical lessons with seminar works, etc.

Assessment

Continuing (homework, midterm exams, project work or seminar paper)
Final (written exam)
grading: 5 (fail), 6-10 (pass) (according to the Statute of UL)

Lecturer's references

Pet najpomembnejših del:
LEBAR BAJEC, Iztok, ZIMIC, Nikolaj, MRAZ, Miha. Towards the bottom-up concept: extended quantum-dot cellular automata. Microelectron. eng.. [Print ed.], 2006, vol. 83, no. 4/9, str. 1826-1829, ilustr. [COBISS-SI-ID 5212244], [WoS, št. citatov do 7.8.09: 4, brez avtocitatov: 2, normirano št. citatov: 2] JCR IF: 1.398, SE (48/206), engineering, electrical &, electronic, x: 0.942, SE (18/32), nanoscience &, nanotechnology, x: 2.04, SE (20/55), optics, x: 1.239, SE (34/84), physics, applied, x: 1.846
LEBAR BAJEC, Iztok, ZIMIC, Nikolaj, MRAZ, Miha. The ternary quantum-dot cell and ternary logic. Nanotechnology (Bristol), 2006, vol. 17, no. 8, str. 1937-1942, ilustr. [COBISS-SI-ID 5201748], [WoS, št. citatov do 7.5.09: 5, brez avtocitatov: 3, normirano št. citatov: 4] JCR IF: 3.037, SE (2/66), engineering, multidisciplinary, x: 0.746, SE (5/32), nanoscience &, nanotechnology, x: 2.04, SE (22/175), materials science, multidisciplinary, x: 1.659, SE (9/84), physics, applied, x: 1.846
MOŠKON, Miha, MRAZ, Miha. Systematic approach to computational design of gene regulatory networks with information processing capabilities. IEEE/ACM transactions on computational biology and bioinformatics, ISSN 1545-5963. [Print ed.], 2014, vol. 11, no. 2
PETRONI, Mattia, ZIMIC, Nikolaj, MRAZ, Miha, MOŠKON, Miha. Stochastic simulation algorithm for gene regulatory networks with multiple binding sites. Journal of computational biology, ISSN 1557-8666. [Online ed.], 2014, vol. 21
STRAŽAR, Martin, MRAZ, Miha, ZIMIC, Nikolaj, MOŠKON, Miha. An adaptive genetic algorithm for parameter estimation of biological oscillator models to achieve target quantitative system response. Natural computing, ISSN 1567-7818, Mar. 2014, vol. 13, no. 1, str. 119-127.
Celotna bibliografija je dostopna na SICRISu:
http://sicris.izum.si/search/rsr.aspx?lang=slv&,id=8066.