Towards a Scalable EA-based Optimization of Digital Circuits
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F19%3APU132057" target="_blank" >RIV/00216305:26230/19:PU132057 - isvavai.cz</a>
Result on the web
<a href="https://www.fit.vut.cz/research/publication/11858/" target="_blank" >https://www.fit.vut.cz/research/publication/11858/</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-030-16670-0_6" target="_blank" >10.1007/978-3-030-16670-0_6</a>
Alternative languages
Result language
angličtina
Original language name
Towards a Scalable EA-based Optimization of Digital Circuits
Original language description
Scalability of fitness evaluation was the main bottleneck preventing adopting the evolution in the task of logic circuits synthesis since early nineties. Recently, various formal approaches have been introduced to this field to overcome this issue. This made it possible to optimize complex circuits consisting of hundreds of inputs and thousands of gates. Unfortunately, we are facing to the another problem - scalability of representation. The efficiency of the evolutionary optimization applied at the global level deteriorates with the increasing complexity. In this paper, we propose to apply the concept of local resynthesis. Resynthesis is an iterative process based on extraction of smaller sub-circuits from a complex circuit that are optimized locally and implanted back to the original circuit. When applied appropriately, this approach can mitigate the problem of scalability of representation. Our evaluation on a set of nontrivial real-world benchmark problems shows that the proposed method provides better results compared to global evolutionary optimization. In more than 60% cases, substantially higher number of redundant gates was removed while keeping the computational effort at the same level.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/LTC18053" target="_blank" >LTC18053: Advanced Methods of Nature-Inspired Optimisation and HPC Implementation for the Real-Life Applications</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach
Others
Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Genetic Programming 22nd European Conference, EuroGP 2019
ISBN
978-3-030-16669-4
ISSN
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e-ISSN
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Number of pages
17
Pages from-to
81-97
Publisher name
Springer International Publishing
Place of publication
Cham
Event location
Leipzig
Event date
Apr 24, 2019
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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