BibTeX Export

@INPROCEEDINGS{dbo:2012:criticalpath,
     author = {B{\"{o}}hme, David and de Supinski, Bronis R. and Geimer, Markus and Schulz, Martin and Wolf, Felix},
      month = may,
      title = {Scalable Critical-Path Based Performance Analysis},
  booktitle = {Proc. of the 26th IEEE International Parallel and Distributed Processing Symposium (IPDPS), Shanghai, China},
       year = {2012},
      pages = {1330--1340},
  publisher = {IEEE},
       issn = {1530-2075},
        doi = {10.1109/IPDPS.2012.120},
   abstract = {The critical path, which describes the longest execution sequence
without wait states in a parallel program, identifies the activities
that determine the overall program runtime. Combining knowledge of the
critical path with traditional parallel profiles, we have defined a
set of compact performance indicators that help answer a variety of important
performance-analysis questions, such as identifying load imbalance,
quantifying the impact of imbalance on runtime, and characterizing
resource consumption. By replaying event traces in parallel, we can
calculate these performance indicators in a highly
scalable way, making them a suitable analysis instrument for massively
parallel programs with thousands of processes. Case studies with
real-world parallel applications confirm that---in comparison to
traditional profiles---our indicators provide enhanced insight into
program behavior, especially when evaluating partitioning schemes of
MPMD programs.}
}