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The issues of compiler optimization phase ordering and selection present important challenges to compiler developers in several domains, and in particular to the speed, code size, power, and cost-constrained domain of embedded systems. Different sequences of optimization phases have been observed to provide the best performance for different applications. Compiler writers and embedded systems developers have recently addressed this problem by conducting iterative empirical searches using machine-learning based heuristic algorithms in an attempt to find the phase sequences that are most effective for each application.
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