Automated Synthesis of Commutative Approximate Arithmetic Operators
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- @InProceedings{vasicek:2024:CEC,
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author = "Zdenek Vasicek",
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title = "Automated Synthesis of Commutative Approximate
Arithmetic Operators",
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booktitle = "2024 IEEE Congress on Evolutionary Computation (CEC)",
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year = "2024",
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editor = "Bing Xue",
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address = "Yokohama, Japan",
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month = "30 " # jun # " - 5 " # jul,
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publisher = "IEEE",
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keywords = "genetic algorithms, genetic programming, cartesian
genetic programming, Power demand, Neural networks,
Evolutionary computation, Libraries, Logic, Adders,
approximate circuit design, approximate arithmetic
circuits",
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isbn13 = "979-8-3503-0837-2",
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DOI = "doi:10.1109/CEC60901.2024.10612202",
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abstract = "Approximate computing, leveraging the inherent
resilience to errors, emerges as a promising strategy
for reducing power consumption in digital systems. The
primary objective of this paper is to introduce an
efficient method based on Cartesian Genetic Programming
for designing approximate arithmetic circuits with
commutative property. Specifically, this work focuses
on the design of 8-bit approximate multipliers and
32-bit approximate adders, both serving as foundational
components for hardware accelerators in neural
networks. We have identified that while the design of
commutative approximate adders poses no issues for
evolution, the design of commutative approximate
multipliers represents a challenging problem causing
the commonly used CGP stuck at highly sub-optimal
solutions. In response to this challenge, we propose a
novel application-specific mutation operator. This
operator significantly enhances the efficiency of the
search process, enabling the discovery of solutions
that were previously unreachable. The achieved results
revealed that imposing the requirement for a
commutative property does not substantially compromise
the quality-error trade-offs of the obtained
approximate circuits, making the resulting Pareto front
comparable to that of unconstrained designs.",
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notes = "also known as \cite{10612202}
WCCI 2024",
- }
Genetic Programming entries for
Zdenek Vasicek
Citations