Soft Computing Approach for VLSI Mincut Partitioning: The State of the Arts

Autor:	Ujjwal Maulik, Debasree Maity, Indrajit Saha, Dariusz Plewczynski
Rok vydání:	2014
Předmět:	Very-large-scale integration Soft computing Vlsi system design Computer architecture Computer science Power consumption Genetic algorithm Netlist State (computer science) Parallel computing
Zdroj:	Advances in Intelligent Systems and Computing ISBN: 9788132216018 SocProS
DOI:	10.1007/978-81-322-1602-5_95
Popis:	Recent research shows that the partitioning of VLSI-based system plays a very important role in embedded system designing. There are several partitioning problems that can be solved at all levels of VLSI system design. Moreover, rapid growth of VLSI circuit size and its complexity attract the researcher to design various efficient partitioning algorithms using soft computing approaches. In VLSI netlist is used to optimize the parameters like mincut, power consumption, delay, cost, and area of the partitions. Hence, the Genetic Algorithm is a soft computational meta-heuristic method that has been applied to optimize these parameters over the past two decades. Here in this paper, we have summarized important schemes that have been adopted in Genetic Algorithm for optimizing one particular parameter, called mincut, to solve the partitioning problem.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::0eb2f2802feeef1ae9e4db89139520b0 https://doi.org/10.1007/978-81-322-1602-5_95 Zobrazit plný text záznamu