The International Conference for High Performance Computing, Networking, Storage and Analysis
Compiler Independent Strategy for Data Locality Optimization.
Authors: Jinxin Yang (University of Houston), Abid Malik (University of Houston), Barbara Chapman (University of Houston)
Abstract: Data locality is an important optimization for loop oriented kernels.
Auto tuning techniques are used to find the best strategy for data locality
optimization. However, auto tuning techniques are expensive and not
independent of computing frameworks. Porting an application from one
framework to another requires the whole auto tuning process to be repeated,
in order to get an optimal solution for the new one. A global
strategy will help in expediting the porting process for an application. In
this work, we present a framework, consisting of OpenUH transformation directives and CHiLL framework, which provides an optimal strategy for the data locality problem which is independent of compilers. Our results show that the strategies given by our framework clearly out class the default optimization levels of OpenUH, GCC, Intel and PGI compilers.