K. C. Shilpa ¹, C. Lakshmi Narayana ¹, Manoj Kumar Singh ²

Affiliations
1 Department of Electrical Engineering Science, BMSCE, Visvesvaraya Technological University, Bangalore - 560019, Karnataka, IN
2 Manuro Tech Research Pvt. Ltd, Bangalore - 560097, Karnataka, IN

Abstract

This paper is a comparative study for optimal scheduling in architectural level synthesis using five different strategies in Differential Evolution. In this paper the comparison is performed using Hardware Abstraction Layer (HAL) benchmark scheduling problem using Integer Linear Programming method. The paper implements adaptive scaling factor for mutation operation and variable cross over operation in differential evolution. The experiment results evaluate the performance parameters optimal resource schedule, convergence time among the five strategies are presented.

Keywords

Architectural Level Synthesis, Differential Evolution, Evolutionary Computation, Hardware Abstraction Layer, Integer Linear Programming, Very Large Scale Integration.

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K. C. Shilpa ¹, C. Lakshmi Narayana ¹, Manoj Kumar Singh ²

Affiliations
1 BMSCE, Department of Electrical Engineering Science, Visvesvaraya Technological University, Bangalore - 560019, Karnataka, IN
2 Manuro Tech Research Pvt. Ltd, Bangalore - 560097, Karnataka, IN

Abstract

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.

Keywords

Architectural Level Synthesis, Evolutionary Computation, Hardware Abstraction Layer, Resource Schedule.

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