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Journals ACM SIGARCH Computer Architecture News Volume 31 Issue 1

In this paper, we present a methodology, based on an Enhanced Genetic Algorithm (EGA), for assigning data objects to dual-bank memories. Our approach is global, and special effort is made to identify those objects that could potentially benefit from an assignment to a specific memory, or perhaps duplication in both memories. The enhancements to the genetic algorithm include a directed mutation operator and a new type of elitism. Together, these enhancements improve the performance of the genetic algorithm and allow the EGA to run unsupervised. The EGA has been incorporated into a retargetable, optimizing compiler for embedded systems, currently under development at the University of Guelph.

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An EGA approach to the compile-time assignment of data to multiple memories in digital-signal processors

Gréwal, Gary; Wilson, Tom; Morton, Andrew
ACM SIGARCH Computer Architecture News , Volume 31 (1)
Association for Computing Machinery – Mar 1, 2003

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