Title
Ant Colony Optimization for multicore re-configurable architecture.
Abstract
The emergence of Multi Processor System on Chip (MPSoC) architectures with reconfigurable options is revolutionizing general purpose processing. Reconfigurable architectures give us the opportunity to allocate system resources with respect to specific application requirements. Reconfigurable architectures can provide high throughput and low energy consumption in a variety of applications. Resource utilization in these systems can be further optimized by using optimization algorithms. Early research in using optimization algorithms (i.e. Genetic Algorithm) for reconfigurable architecture has shown optimistic results for minimum energy consumption while taking limited Cache sizes, number of cores, CPU frequency, etc. In this paper, we have proposed an Ant Colony Optimization (ACO) based technique for reconfigurable architecture for various benchmark applications. We have also shown that the proposed ACO results in a convergent behaviour for all of the design space parameters variations. The ACO based design space exploration engine (ACODSEE) is aimed at minimizing energy consumption while considering throughput as a constraint. Unlike existing models we have arranged our design space in different clusters sets like the generalized travelling salesman problem. The design space is explored by ACODSEE using various SPLASH-2 benchmarks and results show a significant reduction in energy consumption without affecting throughput.
Year
DOI
Venue
2016
10.3233/AIC-160708
AI COMMUNICATIONS
Keywords
Field
DocType
Multi-objective optimization,Ant Colony Optimization,reconfigurable MPSoC
Ant colony optimization algorithms,Architecture,Computer architecture,Computer science,Artificial intelligence,Multi-core processor
Journal
Volume
Issue
ISSN
29
5
0921-7126
Citations 
PageRank 
References 
0
0.34
19
Authors
5
Name
Order
Citations
PageRank
Ishfaq Hussain112.38
Ayaz Ahmad215117.66
Muhammad Yasir Qadri3397.85
N. N. Qadri49813.35
Jameel Ahmed574.52