Combined approach for VLSI placement problem
- DOI
- 10.2991/itsmssm-17.2017.11How to use a DOI?
- Keywords
- VLSI placement, annealing simulation, genetic algorithm, combined approach.
- Abstract
The work discusses a stage of electronic computing equipment automated design - VLSI fragments placement. This task belongs to the NP-complex class of problems. The paper presents the statement of the VLSI placement problem. It is proposed an "evolution" - "search" strategy. A new search architecture based on the proposed strategy is constructed. The principal difference of this approach is the division of the search process into two stages and the application of different methods on each of them. At the first search stage it is used a genetic algorithm. At the second search stage an annealing simulation algorithm is proposed, which allows to improve the result found by the genetic algorithm. Based on this approach, a combined algorithm has been developed. A computational experiment was carried out on test examples (benchmarks). The quality of the obtained placement is on average 3.5% higher than the placement results obtained by using the well-known Dragon 2.23 algorithm. Series of tests and experiments were carried out and showed the promise of this approach. Time complexity of the developed algorithm is represented as O (n3).
- Copyright
- © 2017, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Vladimir Kureichik AU - Liliya Kureichik AU - Vladimir Kureichik Jr AU - Dmitrii Leschanov PY - 2017/12 DA - 2017/12 TI - Combined approach for VLSI placement problem BT - Proceedings of the IV International research conference "Information technologies in Science, Management, Social sphere and Medicine" (ITSMSSM 2017) PB - Atlantis Press SP - 46 EP - 49 SN - 2352-538X UR - https://doi.org/10.2991/itsmssm-17.2017.11 DO - 10.2991/itsmssm-17.2017.11 ID - Kureichik2017/12 ER -