1. Comparison of Swarm Optimization and Memetic Algorithm for Systolic Mapping of Texture Analysis
- Author
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Bagavathi C, Dinesh P, Dhivya devi R, and Siddharthraju K
- Subjects
Computer science ,business.industry ,0202 electrical engineering, electronic engineering, information engineering ,Swarm behaviour ,Memetic algorithm ,020206 networking & telecommunications ,020201 artificial intelligence & image processing ,Pattern recognition ,02 engineering and technology ,Artificial intelligence ,business ,Texture (geology) - 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.
- Published
- 2020
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