Tutorial: Evolutionary Design Methods in Electronic Design Automation
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- @InProceedings{Sekanina:2024:ICCD,
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author = "Lukas Sekanina",
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title = "Tutorial: Evolutionary Design Methods in Electronic
Design Automation",
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booktitle = "2024 IEEE 42nd International Conference on Computer
Design (ICCD)",
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year = "2024",
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pages = "689--690",
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month = nov,
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keywords = "genetic algorithms, genetic programming, Surveys,
Filters, Scalability, Design methodology, Neural
networks, Tutorials, Performance gain, Integrated
circuit modelling, Formal verification, accelerator,
approximate circuit, electronic design automation,
machine learning",
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ISSN = "2576-6996",
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DOI = "
doi:10.1109/ICCD63220.2024.00110",
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abstract = "The use of evolutionary algorithms (EAs) for the
automated design of programs, electronic circuits,
neural networks, and other computational structures has
become a fruitful approach in the last two decades. The
advantage of EAs is that they can handle the design
process in a holistic, multi-objective way and create
solutions with unique properties. This tutorial surveys
the key ingredients of EAs and focuses mainly on
genetic programming. It presents several techniques
(such as incorporating formal verification methods and
surrogate models) to improve the scalability of the
method. Examples of evolved solutions (approximate
arithmetic circuits, neural network architectures, and
image filters) that show unique properties compared to
conventional designs are presented and discussed.",
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notes = "Also known as \cite{10818214}",
- }
Genetic Programming entries for
Lukas Sekanina
Citations