LAMPVIEW: A LOOP-AWARE TOOLSET FOR FACILITATING PARALLELIZATION

A continual growth of the number of transistors per unit area coupled with diminishing returns from traditional microarchitectural and clock frequency improvements has led processor manufacturers to place multiple cores on a single chip. However, only multi-threaded code can fully take advantage of the new multicore processors; legacy single-threaded code does not benefit. Many approaches to parallelization have been explored, including both manual and automatic techniques. Unfortunately, research in this area is impeded by the innate difficulty of exploring code by hand for new possible parallelization schemes. Regardless of whether it is a researcher attempting to discover possible automatic techniques or a programmer trying to make manual parallelization, the benefits of good dependence information are substantial. This thesis provides a profiling and analysis toolset aimed at easing a programmer or researcher’s effort in finding parallelism. The toolset, The Loop-Aware Memory Profile Viewing System (LAMPView), is developed in three parts. The first part is a multi-frontend, multi-target compiler pass written to instrument the code with calls to the Loop-Aware Memory Profiling (LAMP) library. The compile-time instrumentation was partially developed previously and has been augmented here with additional features. The second part is a post-runtime processing pass that translates the output of the profiling run from a machine-level view to a source-level view. As it translates, it also processes and sorts dependence information. The third and final part is a pair of stand-alone utilities that takes the translated information and provides the user with human-readable output that is searchable by various parameters. In various discussions with potential users, it has been seen that the utility eases analysis of parallelism opportunities.