@INPROCEEDINGS{zhukov_wylie:PROPER13,
     author = {Zhukov, Ilya and Wylie, Brian J. N.},
      month = jan,
      title = {Assessing Measurement and Analysis Performance and Scalability of Scalasca 2.0},
  booktitle = {Proc. of the Euro-Par 2013: Parallel Processing Workshops},
     series = {Lecture Notes in Computer Science},
     volume = {8374},
       year = {2014},
      pages = {627-636},
  publisher = {Springer},
        doi = {10.1007/978-3-642-54420-0_61},
   abstract = {The Scalasca toolset was developed to provide highly scalable performance measurement and analysis of scientific applications on current HPC platforms, including leadership systems such as IBM BlueGene/Q and more traditional Linux clusters. Its primary focus is support for C/C++/Fortran applications using MPI and OpenMP, and mixed-mode combinations thereof, offering detailed call-path profiles for each process and thread produced by runtime summarization or augmented with wait-state analysis of event traces. A new generation of Scalasca (2.0) uses the community-developed infrastructure comprising of Score-P and associated components, while continuing to provide the previous functionality. By comparing the new version of Scalasca with its predecessor, using the applications from the NPB3.3-MZ-MPI benchmark suite, we validate core functionality and assess overheads and scalability. Although adequate for general use, various aspects are identified for further improvement, particularly for larger scales.}
}