Evolutionary Computation in Polymorphous Computing Architectures: Metaoptimization of the Scale In-Lining Priority Function for Trips

摘要

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 Scalable Compiler for Analytic Experiments (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.