Efficient VLSI routing optimization employing discrete differential evolution technique

Manna, Suvrajit; Chakrabarti, Tyajodeep; Sharma, Udit; Sarkar, Subir Kumar

doi:10.1109/retis.2015.7232923

Cited by 7 publications

(3 citation statements)

References 7 publications

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“…To verify the superiority of the proposed method in terms of robustness, statistical results of the proposed method compared with two well established population based techniques are shown in Tables XI-XII. These two compared population based techniques are a differential evolution(DE) technique in [27], and an artificial bee colony optimization technique (ABC) in [28]. The experimental results of Table XI and Table XII are based on the benchmark circuits ISP D.…”

Section: Statistical Results Of Several Population Based Techniquesmentioning

confidence: 99%

“…The minimum Steiner tree problem is a NP hard problem, so some evolutionary algorithms which have shown a good application prospect in solving NP hard problems were used to solve RSMT [25][26][27][28][29][30] and X-architecture architecture Steiner minimum tree (XSMT) problem [29,31]. As a swarm-based evolutionary method, particle swarm optimization (PSO) was introduced by Eberhart and Kennedy [18], which has been proved to be a global optimization algorithm.…”

Section: Related Workmentioning

confidence: 99%

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A novel particle swarm optimizer with multi-stage transformation and genetic operation for VLSI routing

Liu,

Zhuang,

Guo

et al. 2018

Preprint

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As the basic model for very large scale integration (VLSI) routing, the Steiner minimal tree (SMT) can be used in various practical problems, such as wire length optimization, congestion, and time delay estimation. In this paper, a novel particle swarm optimization (PSO) algorithm based on multistage transformation and genetic operation is presented to construct two types of SMT, including non-Manhattan SMT and Manhattan SMT. Firstly, in order to be able to handle two types of SMT problems at the same time, an effective edge-vertex encoding strategy is proposed. Secondly, a multistage transformation strategy is proposed to both expand the algorithm search space and ensure the effective convergence. We have tested three types from two to four stages and various combinations under each type to highlight the best combination. Thirdly, the genetic operators combined with union-find partition are designed to construct the discrete particle update formula for discrete VLSI routing. Moreover, in order to introduce uncertainty and diversity into the search of PSO algorithm, we propose an improved mutation operation with edge transformation. Experimental results show that our algorithm from a global perspective of multilayer structure can achieve the best solution quality among the existing algorithms. Finally, to our best knowledge, it is the first work to address both manhattan and non-manhattan routing at the same time.

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Section: Statistical Results Of Several Population Based Techniquesmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

A novel particle swarm optimizer with multi-stage transformation and genetic operation for VLSI routing

Liu,

Zhuang,

Guo

et al. 2018

Preprint

View full text Add to dashboard Cite

show abstract

“…Manna et al [69] described an improved DE for finding RSMT. The entire search space is represented by an n-by-n null matrix, where n is the dimension of search space.…”

Section: Application Of De 1) Applying De To Smt Constructionmentioning

confidence: 99%

A Survey of Swarm Intelligence Techniques in VLSI Routing Problems

et al. 2020

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Routing is a complex and critical stage in the physical design of Very Large Scale Integration (VLSI), minimizing interconnect length and delay to optimize overall chip performance. With the rapid development of modern technology, VLSI routing faces enormous challenges such as large delay, high congestion, and high-power consumption. As a rising optimization method, Swarm Intelligence (SI) inspired from collective intelligence behaviors through cooperation or interaction with the environment provides effectiveness and robustness for solving NP-hard problems. Many researchers have consequently used SI techniques to solve routing-related problems in VLSI. This paper reviews the application of several SI techniques to the VLSI routing filed. Firstly, five commonly used SI techniques and related models, and three classic routing problems are described: Steiner tree construction, global routing and detailed routing. Then an overview of the current state of this field is given according to the above categories, and the survey offers informative discussions from five aspects: 1) Steiner minimum tree construction; 2) wirelength-driven routing; 3) obstacle-avoiding routing; 4) timing-driven routing; 5) power-driven routing. Finally, under three new technology models: X-architecture, multiple dynamic supply voltage and via-pillar, the future development trends are pointed as follows: 1) suggesting suitable SI techniques to specific routing problems for advanced technology models; 2) exploring new and available SI techniques that have not yet been applied to VLSI routing.

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A unified algorithm based on HTS and self-adapting PSO for the construction of octagonal and rectilinear SMT

et al. 2019

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Efficient VLSI routing optimization employing discrete differential evolution technique

Cited by 7 publications

References 7 publications

A novel particle swarm optimizer with multi-stage transformation and genetic operation for VLSI routing

A novel particle swarm optimizer with multi-stage transformation and genetic operation for VLSI routing

A Survey of Swarm Intelligence Techniques in VLSI Routing Problems

A unified algorithm based on HTS and self-adapting PSO for the construction of octagonal and rectilinear SMT

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