Bagavathi C, Department of ECE, Sri Krishna College of Engineering and Technology,India
Siddharthraju K and Dhivya devi R, Department of ECE, KPR Institute of Engineering and Technology, India
Dinesh P, Managing Partner, SAI Incubation Centre, India
Online First : 30 December 2020
Publisher Name : IJAICT India Publications, India.
Print ISBN : 978-81-950008-0-7
Online ISBN : 978-81-950008-1-4
Page :393-400
Abstract
Systolic processors offer a hardware design which can accommodate more functions in a small footprint. Hardware utilization efficiency can be enhanced by appropriately designating the intended hardware with a task in space and time through parallel computing platforms. Regular algorithms known for their computational complexity can be mapped to systolic array by dependence graphs, which allot hardware to the design data. Manual mapping techniques tend to be tedious with more inaccuracy and calls for efficient mapping techniques, automated through algorithmic procedures. Texture Analysis marks the preliminary progression of image analysis and interpretation. Automotive systems, Robotics, Industrial processing and similar automated applications can be simplified through texture analysis. This work deals with employing evolutionary algorithms for mapping texture analysis onto systolic architecture. Memetic Algorithms (MA) and Particle Swarm Optimization (PSO) algorithms were comparatively studied and the efficiency of designing a parallel architecture through systolic array is analyzed through cost function and processing time.
Keywords
Systolic arrays, Parallel computing, Mapping Texture Analysis, Memetic algorithm, Particle swarm algorithm
Cite this article
Bagavathi C Dhivya devi R, Siddharthraju K and Dinesh P, “Comparison of Swarm Optimization and Memetic Algorithm for Systolic Mapping of Texture Analysis”, Innovations in Information and Communication Technology, pp. 393-400, December 2020.
Copyright
© 2020 Bagavathi C Dhivya devi R, Siddharthraju K and Dinesh P. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
