Metaoptimization of the in-lining priority function for a compiler targeting a polymorphous computing architecture

Authors:
Laurence D. Merkle
Affiliations:
Rose-Hulman Institute of Technology, Terre Haute, IN, USA
Venue:
Proceedings of the 10th annual conference companion on Genetic and evolutionary computation
Year:
2008

Citing 4
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Abstract

Leading polymorphous computing architecture (PCA) efforts include the Raw Architecture Workstation (Raw) and the Tera-op Reliable and Intelligently Adaptive Processing System (TRIPS), both of which are tile-based. The Raw toolchain places responsibility for program decomposition on the programmer, but the TRIPS toolchain automatically generates hyperblocks and allocates them to processing elements. This report identifies evolutionary computation (EC) techniques that enable and that are enabled by PCA technology, focusing on application of EC in enhancing the effectiveness of the TRIPS toolchain, including the Scale compiler. In particular, computational experiments are described that investigate the application of genetic programming to the meta-optimization of the priority function used to increase the number of instructions per hyperblock in the in-lining optimization phase of Scale. Results suggest continued experimentation with larger population sizes and more generations.