Abstract
With the growing complexity in semiconductor technology, the design and optimization of VLSI circuits are automated with a high degree of reliability and precision. There are many applications of VLSI circuits and systems that require solving optimization problems of large-scale degrees. While analytical methods may suffer from slow convergence and the curse of dimensionality, metaheuristics-based swarm intelligence algorithms are proven to be an efficient alternative. This chapter presents the applications of emerging swarm intelligence-based techniques for the optimization of VLSI circuits and systems. In this chapter, the recent advances in particle swarm optimization algorithms are used to solve the optimization problem encountered in the VLSI industry. The efficacy of these algorithms is illustrated using two practical case studies. The first case study is related to the design of a 2.4 GHz CMOS LC tank oscillator, and the second one is optimizing a practical power delivery network. A comparative analysis of the performances of these algorithms is presented. This study helps the reader to choose an appropriate PSO optimization algorithm for their required application.
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Hemaram, S., Chordia, A., Tripathi, J.N. (2024). A Comprehensive Analysis of Emerging Variants of Swarm Intelligence for Circuits and Systems. In: Agrawal, Y., Mummaneni, K., Sathyakam, P.U. (eds) Interconnect Technologies for Integrated Circuits and Flexible Electronics. Springer Tracts in Electrical and Electronics Engineering. Springer, Singapore. https://doi.org/10.1007/978-981-99-4476-7_8
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