Abstract
In confronting the “Memory Wall”, the design of embedded vision systems exhibits many challenges regarding design cost, energy consumption, and performance. This paper considers a variant of the Job Shop Scheduling Problem with tooling constraints, arising in this context, in which the completion time (makespan) is to be minimized. This objective corresponds to the performance of the produced circuit. We discuss different formulations using integer linear programming and point out their characteristics, namely the size and the quality of the linear programming relaxation bound. To solve this scheduling problem with large size, we compare various approaches, including a Constraint Programming model, two constructive greedy heuristics, two models of LocalSolver, a Simulated Annealing algorithm, and a Beam Search algorithm. Numerical experiments are conducted on 16 benchmark instances from the literature and 12 real-life non-linear image processing kernels for validating their efficiency.
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Notes
In the field of computer design, memory transfers are known to be a major part of energy consumption, up to 80% of the total energy.
Bipartite graph \(B=({\mathcal {U}},{\mathcal {V}})\): consists of a set of vertices \({\mathcal {U}}\), a disjoint set of vertices \({\mathcal {V}}\), and a set of edges \({\mathcal {E}} \subset {\mathcal {U}} \times {\mathcal {V}}\).
end_of(): End of an interval variable.
no_overlap(): Constrains a set of interval variables not to overlap each others
end_before_start(): Constrains minimum delay between the end of one interval variable and start of another one.
A box plot (or box-and-whisker plot) shows the distribution of quantitative data in a way that facilitates comparisons between variables or across levels of a categorical variable. Specifically, the bottom and the top of each box represent the first and third quartiles; the band inside the box represents the second quartile (the median); the ends of the whiskers represent the 9th percentile and the 91 percentile. Outliers are plotted as individual points.
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Hadj Salem, K., Jost, V., Kieffer, Y. et al. Minimizing makespan under data prefetching constraints for embedded vision systems: a study of optimization methods and their performance. Oper Res Int J 22, 1639–1673 (2022). https://doi.org/10.1007/s12351-021-00647-0
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DOI: https://doi.org/10.1007/s12351-021-00647-0