Towards Multi-objective Optimization of Automatic Design Space Exploration for Computer Architecture through Hyper-heuristic

Authors

  • M. Latif Department of Software Engineering, NED University of Engineering & Technology, Pakistan
  • M. A. Ismail Department of Computer and Information Systems Engineering, NED University of Engineering & Technology, Pakistan

Abstract

Multi-objective optimization is an NP-hard problem. ADSE (automatic design space exploration) using heuristics has been proved to be an appropriate method in resolving this problem. This paper presents a hyper-heuristic technique to solve the DSE issue in computer architecture. Two algorithms are proposed. A hyper-heuristic layer has been added to the FADSE (framework for automatic design space exploration) and relevant algorithms have been implemented. The benefits of already existing multi-objective algorithms have been joined in order to strengthen the proposed algorithms. The proposed algorithms, namely RRSNS (round-robin scheduling NSGA-II and SPEA2) and RSNS (random scheduling NSGA-II and SPEA2) have been evaluated for the ADSE problem. The results have been compared with NSGA-II and SPEA2 algorithms. Results show that the proposed methodologies give competitive outcomes in comparison with NSGA-II and SPEA2.

Keywords:

hyper-heuristic, multi-objective optimization, design space exploration, x86 processor

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How to Cite

[1]
M. Latif and M. A. Ismail, “Towards Multi-objective Optimization of Automatic Design Space Exploration for Computer Architecture through Hyper-heuristic”, Eng. Technol. Appl. Sci. Res., vol. 9, no. 3, pp. 4292–4297, Jun. 2019.

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