Trustworthy Genetic Programming-Based Synthesis of Analog Circuit Topologies Using Hierarchical Domain-Specific Building Blocks

This paper presents MOJITO, a system that performs structural synthesis of analog circuits, returning designs that are trustworthy by construction. The search space is defined by a set of expert-specified, trusted, hierarchically-organized analog building blocks, which are organized as a parameteriz...

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Published inIEEE transactions on evolutionary computation Vol. 15; no. 4; pp. 557 - 570
Main Authors McConaghy, T., Palmers, P., Steyaert, M., Gielen, G. G. E.
Format Journal Article
LanguageEnglish
Published New York, NY IEEE 01.08.2011
Institute of Electrical and Electronics Engineers
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
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Abstract This paper presents MOJITO, a system that performs structural synthesis of analog circuits, returning designs that are trustworthy by construction. The search space is defined by a set of expert-specified, trusted, hierarchically-organized analog building blocks, which are organized as a parameterized context-free grammar. The search algorithm is a multiobjective evolutionary algorithm that uses an age-layered population structure to balance exploration versus exploitation. It is validated with experiments to search across >;100 000 different one-stage and two-stage opamp topologies, returning human-competitive results. The runtime is orders of magnitude faster than open-ended systems, and unlike the other evolutionary algorithm approaches, the resulting circuits are trustworthy by construction. The approach generalizes to other problem domains which have accumulated structural domain knowledge, such as robotic structures, car assemblies, and modeling biological systems.
AbstractList This paper presents MOJITO, a system that performs structural synthesis of analog circuits, returning designs that are trustworthy by construction. The search space is defined by a set of expert-specified, trusted, hierarchically-organized analog building blocks, which are organized as a parameterized context-free grammar. The search algorithm is a multiobjective evolutionary algorithm that uses an age-layered population structure to balance exploration versus exploitation. It is validated with experiments to search across >;100 000 different one-stage and two-stage opamp topologies, returning human-competitive results. The runtime is orders of magnitude faster than open-ended systems, and unlike the other evolutionary algorithm approaches, the resulting circuits are trustworthy by construction. The approach generalizes to other problem domains which have accumulated structural domain knowledge, such as robotic structures, car assemblies, and modeling biological systems.
This paper presents MOJITO, a system that performs structural synthesis of analog circuits, returning designs that are trustworthy by construction. The search space is defined by a set of expert-specified, trusted, hierarchically-organized analog building blocks, which are organized as a parameterized context-free grammar. The search algorithm is a multiobjective evolutionary algorithm that uses an age-layered population structure to balance exploration versus exploitation. It is validated with experiments to search across > 100000 different one-stage and two-stage opamp topologies, returning human-competitive results. The runtime is orders of magnitude faster than open-ended systems, and unlike the other evolutionary algorithm approaches, the resulting circuits are trustworthy by construction. The approach generalizes to other problem domains which have accumulated structural domain knowledge, such as robotic structures, car assemblies, and modeling biological systems.
This paper presents MOJITO, a system that performs structural synthesis of analog circuits, returning designs that are trustworthy by construction. The search space is defined by a set of expert-specified, trusted, hierarchically-organized analog building blocks, which are organized as a parameterized context-free grammar. The search algorithm is a multiobjective evolutionary algorithm that uses an age-layered population structure to balance exploration versus exploitation. It is validated with experiments to search across [Formula Omitted] different one-stage and two-stage opamp topologies, returning human-competitive results. The runtime is orders of magnitude faster than open-ended systems, and unlike the other evolutionary algorithm approaches, the resulting circuits are trustworthy by construction. The approach generalizes to other problem domains which have accumulated structural domain knowledge, such as robotic structures, car assemblies, and modeling biological systems.
Author Steyaert, M.
Gielen, G. G. E.
McConaghy, T.
Palmers, P.
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Issue 4
Keywords Analog circuit
Motor car
Evolutionary algorithm
Multiobjective programming
Optimization
Robotics
multiobjective optimization
Confidence
Age
Automation
Operational amplifier
evolutionary algorithm (EA)
Topology
Experimental study
Population balance
Search algorithm
design automation
Genetic algorithm
Analog
Integrated circuit
Context free grammar
Circuit synthesis
Hierarchical system
integrated circuit (IC)
Molecular biology
Heterostructures
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Snippet This paper presents MOJITO, a system that performs structural synthesis of analog circuits, returning designs that are trustworthy by construction. The search...
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SubjectTerms Analog
Analog circuits
Applied sciences
Artificial intelligence
Automation
Computer science; control theory; systems
Construction
Design automation
Electronics
evolutionary algorithm (EA)
Evolutionary algorithms
Exact sciences and technology
Grammar
integrated circuit (IC)
Integrated circuit modeling
Integrated circuits
Integrated circuits by function (including memories and processors)
Manufacturing engineering
multiobjective optimization
Searching
Semiconductor electronics. Microelectronics. Optoelectronics. Solid state devices
Semiconductor process modeling
Solid modeling
Synthesis
Topology
Title Trustworthy Genetic Programming-Based Synthesis of Analog Circuit Topologies Using Hierarchical Domain-Specific Building Blocks
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