An efficient evolutionary approach to placing VLSI elements based on multithread CUDA programming

In this paper, we present an evolutionary algorithm to place VLSI elements based on evolutionary computing with multi-chromosomes. In addition, we present possible software implementation of the algorithm based on multithread CUDA programming, and report some experimental results of the suggested al...

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Published in:2016 5th International Conference on Informatics, Electronics and Vision (ICIEV) pp. 1153 - 1156
Main Authors: Korovin, Iakov, Khisamutdinov, Maxim, Schaefer, Gerald, Kalyaev, Anatoly
Format: Conference Proceeding
Language:English
Published: IEEE 01.05.2016
Subjects:
Algorithm design and analysis
Biological cells
CUDA
evolutionary computing
Genetic algorithms
Graphics processing units
optimisation
Sociology
Statistics
Very large scale integration
VLSI design
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Abstract In this paper, we present an evolutionary algorithm to place VLSI elements based on evolutionary computing with multi-chromosomes. In addition, we present possible software implementation of the algorithm based on multithread CUDA programming, and report some experimental results of the suggested algorithm implementation.
AbstractList In this paper, we present an evolutionary algorithm to place VLSI elements based on evolutionary computing with multi-chromosomes. In addition, we present possible software implementation of the algorithm based on multithread CUDA programming, and report some experimental results of the suggested algorithm implementation.
Author Kalyaev, Anatoly
Khisamutdinov, Maxim
Schaefer, Gerald
Korovin, Iakov
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  surname: Korovin
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  organization: Southern Fed. Univ., Rostov-on-Don, Russia
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  givenname: Maxim
  surname: Khisamutdinov
  fullname: Khisamutdinov, Maxim
  organization: Southern Fed. Univ., Rostov-on-Don, Russia
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  givenname: Gerald
  surname: Schaefer
  fullname: Schaefer, Gerald
  organization: Loughborough Univ., Loughborough, UK
– sequence: 4
  givenname: Anatoly
  surname: Kalyaev
  fullname: Kalyaev, Anatoly
  organization: Southern Fed. Univ., Rostov-on-Don, Russia
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Snippet In this paper, we present an evolutionary algorithm to place VLSI elements based on evolutionary computing with multi-chromosomes. In addition, we present...
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StartPage 1153
SubjectTerms Algorithm design and analysis
Biological cells
CUDA
evolutionary computing
Genetic algorithms
Graphics processing units
optimisation
Sociology
Statistics
Very large scale integration
VLSI design
Title An efficient evolutionary approach to placing VLSI elements based on multithread CUDA programming
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