A survey on an optimal solution for VLSI circuit partitioning in physical design using DPSO & DFFA algorithms

Author(s):  
P. Rajeswari ◽  
S Theodore Chandra
VLSI Design ◽  
2011 ◽  
Vol 2011 ◽  
pp. 1-9 ◽  
Author(s):  
I. Hameem Shanavas ◽  
Ramaswamy Kannan Gnanamurthy

Minimizing the wirelength plays an important role in physical design automation of very large-scale integration (VLSI) chips. The objective of wirelength minimization can be achieved by finding an optimal solution for VLSI physical design components like partitioning and floorplanning. In VLSI circuit partitioning, the problem of obtaining a minimum delay has prime importance. In VLSI circuit floorplanning, the problem of minimizing silicon area is also a hot issue. Reducing the minimum delay in partitioning and area in floorplanning helps to minimize the wirelength. The enhancements in partitioning and floorplanning have influence on other criteria like power, cost, clock speed, and so forth. Memetic Algorithm (MA) is an Evolutionary Algorithm that includes one or more local search phases within its evolutionary cycle to obtain the minimum wirelength by reducing delay in partitioning and by reducing area in floorplanning. MA applies some sort of local search for optimization of VLSI partitioning and floorplanning. The algorithm combines a hierarchical design technique like genetic algorithm and constructive technique like Simulated Annealing for local search to solve VLSI partitioning and floorplanning problem. MA can quickly produce optimal solutions for the popular benchmark.


2014 ◽  
Vol 2014 ◽  
pp. 1-15 ◽  
Author(s):  
I. Hameem Shanavas ◽  
R. K. Gnanamurthy

In Optimization of VLSI Physical Design, area minimization and interconnect length minimization is an important objective in physical design automation of very large scale integration chips. The objective of minimizing the area and interconnect length would scale down the size of integrated chips. To meet the above objective, it is necessary to find an optimal solution for physical design components like partitioning, floorplanning, placement, and routing. This work helps to perform the optimization of the benchmark circuits with the above said components of physical design using hierarchical approach of evolutionary algorithms. The goal of minimizing the delay in partitioning, minimizing the silicon area in floorplanning, minimizing the layout area in placement, minimizing the wirelength in routing has indefinite influence on other criteria like power, clock, speed, cost, and so forth. Hybrid evolutionary algorithm is applied on each of its phases to achieve the objective. Because evolutionary algorithm that includes one or many local search steps within its evolutionary cycles to obtain the minimization of area and interconnect length. This approach combines a hierarchical design like genetic algorithm and simulated annealing to attain the objective. This hybrid approach can quickly produce optimal solutions for the popular benchmarks.


2004 ◽  
Vol 12 (3) ◽  
pp. 327-353 ◽  
Author(s):  
Shawki Areibi ◽  
Zhen Yang

Combining global and local search is a strategy used by many successful hybrid optimization approaches. Memetic Algorithms (MAs) are Evolutionary Algorithms (EAs) that apply some sort of local search to further improve the fitness of individuals in the population. Memetic Algorithms have been shown to be very effective in solving many hard combinatorial optimization problems. This paper provides a forum for identifying and exploring the key issues that affect the design and application of Memetic Algorithms. The approach combines a hierarchical design technique, Genetic Algorithms, constructive techniques and advanced local search to solve VLSI circuit layout in the form of circuit partitioning and placement. Results obtained indicate that Memetic Algorithms based on local search, clustering and good initial solutions improve solution quality on average by 35% for the VLSI circuit partitioning problem and 54% for the VLSI standard cell placement problem.


2007 ◽  
Vol 33 (4) ◽  
pp. 233-248 ◽  
Author(s):  
Stephen Coe ◽  
Shawki Areibi ◽  
Medhat Moussa

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