Efficient execution of well-parallelized applications is central to performance in the multicore era. Program analysis tools support the hardware and software sides of this effort by exposing relevant features of multithreaded applications. This paper describes parallel block vectors, which uncover previously unseen characteristics of parallel programs. Parallel block vectors provide block execution profiles per concurrency phase (e.g., the block execution profile of all serial regions of a program). This information provides a direct and fine-grained mapping between an application’s runtime parallel phases and the static code that makes up those phases. This paper also demonstrates how to collect parallel block vectors with minimal application perturbation using Harmony. Harmony is an instrumentation pass for the LLVM compiler that introduces just 1621% overhead on average across eight Parsec benchmarks. We apply parallel block vectors to uncover several novel insights about pa...
Melanie Kambadur, Kui Tang, Martha A. Kim