Effective performance measurement and analysis of multithreaded applications

Understanding why the performance of a multithreaded program does not improve linearly with the number of cores in a sharedmemory node populated with one or more multicore processors is a problem of growing practical importance. This paper makes three contributions to performance analysis of multithreaded programs. First, we describe how to measure and attribute parallel idleness, namely, where threads are stalled and unable to work. This technique applies broadly to programming models ranging from explicit threading (e.g., Pthreads) to higher-level models such as Cilk and OpenMP. Second, we describe how to measure and attribute parallel overhead--when a thread is performing miscellaneous work other than executing the user's computation. By employing a combination of compiler support and post-mortem analysis, we incur no measurement cost beyond normal profiling to glean this information. Using idleness and overhead metrics enables one to pinpoint areas of an application where con...

• Type: Conference
• Year: 2009
• Where: PPOPP
• Authors: Nathan R. Tallent, John M. Mellor-Crummey
• Keywords: Arbitrary Performance Metrics, Multithreaded Programming Models, Parallel Computing, Parallel Idleness, PPOPP 2009