Workload, platform, and available resources constitute a parallel program's execution environment. Most parallelization efforts statically target an anticipated range of environments, but performance generally degrades outside that range. Existing approaches address this problem with dynamic tuning but do not optimize a multiprogrammed system holistically. Further, they either require manual programming effort or are limited to array-based data-parallel programs.
This paper presents Parcae, a… CONTINUE READING