Efficient Parallelization and Performance Analysis of Meta-heuristics on Many-core Platforms
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Date
2023
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Abstract
Meta-heuristics are an efficient method for solving complex problems in science, engineering, and industry. They explore the solution space efficiently to generate a good solution in a reasonable time through a neighborhood or population-based local search. Even if the meta-heuristics do it efficiently, for large instances (practical problems of science, engineering, or industry), generation of neighborhood and evaluation of solution of single-solution based meta-heuristics or population-based meta-heuristics takes a tremendous amount of time.
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Supervisor: Mitra, Pinaki
Keywords
Meta-heuristics, Multi-Core Architecture, GPU, CUDA