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Optimal Resource Schedule in Architectural Level Synthesis using Evolutionary Computations
Objectives: This paper aims to find optimal resource schedule in Architectural level synthesis using Evolutionary Computation. Methods and Statistical Analysis: The paper is a comparative study of four Evolutionary Computations Algorithm: Differential Evolution (DE), Genetic Algorithm (GA), Evolutionary Programming (EP) and Particle Swarm Optimization (PSO). The problem area chosen is Hardware Abstraction Layer (HAL) benchmark scheduling problem using Integer Linear Programming method. Findings: The nature inspired computation algorithms should satisfy the Latency constrained Schedule, simulation results are implemented using MATLAB software. Conclusion/Application: The performance with respect to optimal resource schedule, number of generations, convergence time is compared among the four optimized algorithm are presented. The results prove Differential Evolution is better among the other optimized algorithm.
Architectural Level Synthesis, Evolutionary Computation, Hardware Abstraction Layer, Resource Schedule.
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