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A MULTI-OBJECTIVE HW–SW CO-SYNTHESIS ALGORITHM BASED ON QUANTUM-INSPIRED EVOLUTIONARY ALGORITHM

Nature Inspired Computation and Applications Laboratory, University of Science and Technology of China, Hefei 230026, China

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BIN LI

Nature Inspired Computation and Applications Laboratory, University of Science and Technology of China, Hefei 230026, China

Corresponding author.

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YI ZOU

Nature Inspired Computation and Applications Laboratory, University of Science and Technology of China, Hefei 230026, China

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WENCONG ZHANG

Nature Inspired Computation and Applications Laboratory, University of Science and Technology of China, Hefei 230026, China

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, and

ZHENQUAN ZHUANG

Nature Inspired Computation and Applications Laboratory, University of Science and Technology of China, Hefei 230026, China

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https://doi.org/10.1142/S146902680800220XCited by:2 (Source: Crossref)

Abstract

Hardware–Software (HW–SW) co-synthesis is one of the key steps in modern embedded system design. Generally, HW–SW co-synthesis is to optimally allocate processors, assign tasks to processors, and schedule the processing of tasks to achieve a good balance among performance, cost, power consumption, etc. Hence, it is a typical multi-objective optimization problem. In this paper, a new multi-objective HW–SW co-synthesis algorithm based on the quantum-inspired evolutionary algorithm (MQEAC) is proposed. MQEAC utilizes multiple quantum probability amplitude vectors to model the promising areas of solution space. Meanwhile, this paper presents a new crossover operator to accelerate the convergence to the Pareto front and introduces a PE slot-filling strategy to improve the efficiency of scheduling. Experimental results show that the proposed algorithm can solve the typical multi-objective co-synthesis problems effectively and efficiently.

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