Učni načrt predmeta

Predmet:

Napredne računalniške strukture in sistemi

Course:

Advanced Computer Structures and Systems

Študijski program in stopnja / Study programme and level	Študijska smer / Study field	Letnik / Academic year	Semester / Semester
Informacijske in komunikacijske	Računalniške strukture in sistemi	1	1
Information and Communication	Computer Structures and Systems	1	1

Vrsta predmeta / Course type

Izbirni / Elective

Univerzitetna koda predmeta / University course code:

IKT3-703

Predavanja Lectures	Seminar Seminar	Vaje Tutorial	Klinične vaje work	Druge oblike študija	Samost. delo Individ. work	ECTS
30	30			30	210	10

*Navedena porazdelitev ur velja, če je vpisanih vsaj 15 študentov. Drugače se obseg izvedbe kontaktnih ur sorazmerno zmanjša in prenese v samostojno delo. / This distribution of hours is valid if at least 15 students are enrolled. Otherwise the contact hours are linearly reduced and transfered to individual work.

Nosilec predmeta / Course leader:

izr. prof. dr. Gregor Papa

Sodelavci / Lecturers:

prof. dr. Peter Korošec

Jeziki / Languages:

Predavanja / Lectures:

Slovenščina, angleščina / Slovenian, English

Vaje / Tutorial:

Pogoji za vključitev v delo oz. za opravljanje študijskih obveznosti:

Prerequisites:

Zaključen študij druge stopnje s področja informacijskih ali komunikacijskih tehnologij ali zaključen študij druge stopnje na drugih področjih z znanjem osnov s področja predmeta. Potrebna so tudi osnovna znanja matematike, računalništva in informatike.

Completed second cycle studies in information or communication technologies or completed second cycle studies in other fields with knowledge of fundamentals in the field of this course. Basic knowledge of mathematics, computer science and informatics is also requested.

Vsebina:

Content (Syllabus outline):

Rekonfigurabilno računalništvo:
Komponente, arhitekture, upravljanje rekonfiguriranja, sinteza rekonfigurabilnih sistemov.

Zanesljivost rekonfigurabilnih sistemov:
Izvedba sprotnega samodejnega testiranja, samopopravljivi sistemi.

Vzporedne računalniške arhitekture:
Topologije, deljen in porazdeljen način procesiranja, večjedrni procesorji, gruče, omrežja.

Grafične procesne enote:
Namen uporabe, izvedbe, specifičnost programske opreme.

Večprocesorski sistemi v čipu:
Arhitekture, snovanje energijsko varčnih sistemov, visokonivojsko snovanje, analiza zmogljivosti, načrtovalska okolja.

Reconfigurable computing:
Devices, architectures, reconfiguration management, reconfigurable system synthesis.

Reliability of reconfigurable computing systems: On-line built-in self-test implementation, self repairable systems.

Parallel computer architectures:
Topologies, shared and distributed processing, multi-core processors, clusters, grids.

Graphics Processor Units:
Usage, implementation variations, software specifics.

Multiprocessor systems-on-chips:
Architectures, energy aware design techniques, high-level system synthesis, performance analysis, design environments.

Temeljna literatura in viri / Readings:

Izbrana poglavja iz naslednjih knjig: / Selected chapters from the following books:
- P.R. Schaumont, A Practical Introduction to Hardware/Software Codesign. Springer, 2013, ISBN: 978-1-4614-3736-9.
- R. Skhiri, V. Fresse, J.P. Jamont, B. Suffran, J. Malek, From FPGA to Support Cloud to Cloud of FPGA: State of the Art, International Journal of Reconfigurable Computing, ISSN: 1687-7195, Vol. 2019, doi: 10.1155/2019/8085461
- W. Stallings, Computer Organization and Architecture: Designing for Performance, 9 edition. Prentice Hall, 2012. ISBN: 978-0132936330.
- M. Wolf, Computers as Components. Academic Press, 2012. ISBN 978-0123884367.
- P. Marwedel, Embedded System Design. Springer, 2011. ISBN: 978-94-007-0257-8.

Cilji in kompetence:

Objectives and competences:

Cilj tega predmeta je poglobiti znanje o rekonfigurabilnih in večprocesorskih računalniških sistemih.

Študenti se seznanijo in so sposobni uporabljati v raziskovalnem delu sintezo rekonfigurabilnih sistemov in večprocesorskih sistemov ter z njimi povezane optimizacijske probleme.

The goal of the course is to improve the knowledge on reconfigurable and multiprocessor computing systems.

Students get acquainted with and are able to use in their research work reconfigurable and multiprocessor system synthesis and associated optimization problems.

Predvideni študijski rezultati:

Intendeded learning outcomes:

Študenti bodo z uspešno opravljenimi obveznostmi tega predmeta pridobili:
- znanstveno védenje o formuliranju in analizi rekonfigurabilnih ter večprocesorskih sistemov
- znanstvene aktivnosti, kot je zmožnost optimiziranja programske opreme ob upoštevanju značilnosti dane računalniške arhitekture
- sposobnost uporabe obstoječih metod na drugih področjih, kjer so potrebni pristopi načrtovanja in analize sistemov

Students successfully completing this course will acquire:
- Scientific knowledge on formulating and analysing reconfigurable and multiprocessor systems
- Scientific activities, such as ability to optimize programs by considering specifics of given computer architecture
- The ability to apply existing methods to other fields that require efficient system synthesis and analysis approaches

Metode poučevanja in učenja:

Learning and teaching methods:

Predavanja, seminar, konzultacije, individualno
delo.

Lectures, seminar, consultations, individual work.

Načini ocenjevanja:

Delež v % / Weight in %

Assesment:

Seminarska naloga

50 %

Seminar work

Ustni zagovor seminarske naloge

50 %

Oral defense of seminar work

Reference nosilca / Lecturer's references:

1.	RAUT, Gopal, BIASIZZO, Anton, DHAKAD, Narendra, GUPTA, Neha, PAPA, Gregor, VISHVAKARMA, Santosh Kumar. Data multiplexed and hardware reused architecture for deep neural network accelerator. Neurocomputing. [Print ed.]. 2022, vol. 486, pp. 147-159, DOI: 10.1016/j.neucom.2021.11.018.
2.	KRIVEC, Tadej, PAPA, Gregor, KOCIJAN, Juš. Simulation of variational Gaussian process NARX models with GPGPU. ISA transactions. 2021, vol. 109, pp. 141-151, DOI: 10.1016/j.isatra.2020.10.011.
3.	VREČA, Jure, IVANOV, Iva, PAPA, Gregor, BIASIZZO, Anton. Detecting network intrusion using binarized neural networks. In: 2021 IEEE 7th World Forum on Internet of Things (WF-IoT), hibrid event, virtual and in person, 14 June-31 July 2021, New Orleans, LA, USA. IEEE, 2021. pp. 622-627. ISBN 978-1-6654-4431-6, ISBN 978-1-6654-4432-3, DOI: 10.1109/WF-IoT51360.2021.9595961.
4.	PETELIN, Gašper, LEHNIGK, Ronald, KELLING, Jeffrey, PAPA, Gregor, SCHLEGEL, Fabian. GPU-based accelerated computation of coalescence and breakup frequencies for polydisperse bubbly flows. In: NENE 2021: 30th International Conference Nuclear Energy for New Europe: September 6-9, Bled, Slovenia : NENE 2021. 2021. pp. 602.1-602.8.
5.	EFTIMOV, Tome, PETELIN, Gašper, KOROŠEC, Peter. DSCTool : a web-service-based framework for statistical comparison of stochastic optimization algorithms. Applied soft computing. 2020, vol. 87, pp. 105977-1-105977-11, DOI: 10.1016/j.asoc.2019.105977.