Advanced Methods of Nature-Inspired Optimisation and HPC Implementation for the Real-Life Applications

Czech title:Pokročilé metody nature-inspired optimalizačních algoritmů a HPC implementace pro řešení reálných aplikací
Research leader:Matoušek Radomil
Team leaders:Sekanina Lukáš
Team members:Bidlo Michal, Vašíček Zdeněk
Agency:Ministry of Education, Youth and Sports Czech Republic
Code:LTC18053
Start:2018-06-01
End:2020-02-29
Keywords:Nature-inspired optimization, evolutionary algorithm; computational intelligence, key enabling technologies; international cooperation
Annotation:
The scientific aim of the project is to design advanced evolutionary algorithms (EA) that are applicable in the up to date complex engineering optimizing and designing problems. Another objective is to adapt such algorithms for different user-defined platforms, e.g. for powerful GPU (Graphic Processing Unit) or, on the other hand, for low-power embedded systems. The project is divided into three solution phases called Work Packages (WP1-3). Within the first phase, new and hybrid evolutionary algorithms will be designed and evaluated. The implementations of HPC (High Performance Computing) and embedded systems will be realized in the second phase, where the pre-defined efficiency (computational performance, scalability, energy efficiency) will be emphasized. Within the third phase, the practical applications, referred to as the case studies consequently, will be elaborated. This final phase will prove the efficiency of the proposed algorithms and practical applicability w.r.t. the predefined real tasks. The integration objective of the project is to evolve the existing international co-operation and establish new collaboration of the research teams within BUT working on evolutionary algorithms with leading scientific institutions abroad. The aim is to present common publications containing new scientific results.

Publications

2019KOCNOVÁ Jitka and VAŠÍČEK Zdeněk. Towards a Scalable EA-based Optimization of Digital Circuits. In: Genetic Programming 22nd European Conference, EuroGP 2019. Cham: Springer International Publishing, 2019, pp. 81-97. ISBN 978-3-030-16669-4.
 KONČAL Ondřej and SEKANINA Lukáš. Cartesian Genetic Programming as an Optimizer of Programs Evolved with Geometric Semantic Genetic Programming. In: Genetic Programming 22nd European Conference, EuroGP 2019. Cham: Springer International Publishing, 2019, pp. 98-113. ISBN 978-3-030-16669-4.
2018GROCHOL David and SEKANINA Lukáš. Fast Reconfigurable Hash Functions for Network Flow Hashing in FPGAs. In: Proceedings of the 2018 NASA/ESA Conference on Adaptive Hardware and Systems. Edinburgh: Institute of Electrical and Electronics Engineers, 2018, pp. 257-263. ISBN 978-1-5386-7753-7.
 MRÁZEK Vojtěch, VAŠÍČEK Zdeněk and SEKANINA Lukáš. Design of Quality-Configurable Approximate Multipliers Suitable for Dynamic Environment. In: Proceedings of the 2018 NASA/ESA Conference on Adaptive Hardware and Systems. Edinburgh: Institute of Electrical and Electronics Engineers, 2018, pp. 264-271. ISBN 978-1-5386-7753-7.
 SEKANINA Lukáš, MRÁZEK Vojtěch and VAŠÍČEK Zdeněk. Design Space Exploration for Approximate Implementations of Arithmetic Data Path Primitives. In: 25th IEEE International Conference on Electronics Circuits and Systems (ICECS). Bordeaux: IEEE Circuits and Systems Society, 2018, pp. 377-380. ISBN 978-1-5386-9562-3.

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