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@INPROCEEDINGS{szebenyi-ea:2011:perf_analysis,
     author = {Szebenyi, Zolt{\'{a}}n and Wolf, Felix and Wylie, Brian J. N.},
      month = may,
      title = {Performance Analysis of Long-running Applications},
  booktitle = {Proc. of the 25th IEEE International Parallel and Distributed Processing Symposium (IPDPS) PhD Forum, Anchorage, AK, USA},
       year = {2011},
      pages = {2100--2103},
  publisher = {IEEE},
       isbn = {978-0-7695-4385-7},
        doi = {10.1109/IPDPS.2011.388},
   abstract = {With the growing complexity of supercomputing
applications and systems, it is important to constantly develop
existing performance measurement and analysis tools to provide
new insights into application performance characteristics and
thereby help scientists and engineers utilize computing resources
more efficiently. We present the various new techniques developed,
implemented and integrated into the Scalasca toolset
specifically to enhance performance analysis of long-running
applications. The first is a hybrid measurement system seamlessly
integrating sampled and event-based measurements capable
of low-overhead, highly detailed measurements and therefore
particularly convenient for initial performance analyses. Then
we apply iteration profiling to scientific codes, and present an
algorithm for reducing the memory and space requirements of
the collected data using iteration profile clustering. Finally, we
evaluate the complete integration of all these techniques in a
unified measurement system.}
}