New Algorithms for Performance Trace Analysis Based on Compressed Complete Call Graphs

  • Andreas Knüpfer
  • Wolfgang E. Nagel
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3515)


This paper addresses performance and scalability issues of state-of-the-art trace analysis. The Complete Call Graph (CCG) data structure is proposed as an alternative to the common linear storage schemes. By transparent in-memory compression CCGs are capable of exploiting redundancy as frequently found in traces and thus reduce the memory requirements notably. Evaluation algorithms can be designed to take advantage of CCGs, too, such that the computational effort is reduced in the same order of magnitude as the memory requirements.


Node Count Graph Node Initial Query Successive Query Interactive Query 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. 1.
    Almasi, G., Archer, C., Gunnels, J., Heidelberger, P., Martorell, X., Moreira, J.E.: Architecture and Performance of the BlueGene/L Message Layer. In: Kranzlmüller, D., Kacsuk, P., Dongarra, J. (eds.) EuroPVM/MPI 2004. LNCS, vol. 3241, pp. 259–267. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  2. 2.
    Brunst, H., Hoppe, H.-C., Nagel, W.E., Winkler, M.: Performance Otimization for Large Scale Computing: The Scalable VAMPIR Approach. In: Alexandrov, V.N., Dongarra, J., Juliano, B.A., Renner, R.S., Tan, C.J.K. (eds.) ICCS-ComputSci 2001. LNCS, vol. 2074, p. 751. Springer, Heidelberg (2001)CrossRefGoogle Scholar
  3. 3.
    Brunst, H., Nagel, W.E., Seidl, S.: Performance Tuning on Parallel Systems: All Problems Solved? In: Sørevik, T., Manne, F., Moe, R., Gebremedhin, A.H. (eds.) PARA 2000. LNCS, vol. 1947, pp. 279–287. Springer, Heidelberg (2001)CrossRefGoogle Scholar
  4. 4.
    Brunst, H., Malony, A.D., Shende, S.S., Bell, R.: Online Remote Trace Analysis of Parallel Applications on High-Performance Clusters. In: Veidenbaum, A., Joe, K., Amano, H., Aiso, H. (eds.) ISHPC 2003. LNCS, vol. 2858, pp. 440–449. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  5. 5.
    Brunst, H., Nagel, W.E., Malony, A.D.: A Distributed Performance Analysis Architecture for Clusters. In: IEEE International Conference on Cluster Computing, Cluster 2003, Hong Kong, China, December 2003, pp. 73–81. IEEE Computer Society, Los Alamitos (2003)Google Scholar
  6. 6.
    Grove, D., Chambers, C.: An assessment of call graph construction algorithms (2000),
  7. 7.
    Knüpfer, A.: A New Data Compression Technique for Event Based Program Traces. In: Sloot, P.M.A., Abramson, D., Bogdanov, A.V., Gorbachev, Y.E., Dongarra, J., Zomaya, A.Y. (eds.) ICCS 2003. LNCS, vol. 2659, pp. 956–965. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  8. 8.
    Knüpfer, A., Brunst, H., Nagel, W.E.: High Performance Event Trace Visualization. In: 13th Euromicro Conference on Parallel, Distributed and Network-based Processing, Lugano, Switzerland (February 2005)Google Scholar
  9. 9.
    Knüpfer, A., Kranzlmüller, D., Nagel, W.E.: Detection of Collective MPI Operation Patterns. In: Kranzlmüller, D., Kacsuk, P., Dongarra, J. (eds.) EuroPVM/MPI 2004. LNCS, vol. 3241, pp. 259–267. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  10. 10.
    Knüpfer, A., Nagel, W.E.: Compressible Memory Data Structures for Event Based Trace Analysis. Future Generation Computer Systems by Elsevier (2004) (accepted for publication)Google Scholar
  11. 11.
    Kranzlmüller, D., Scarpa, M., Volkert, J.: DeWiz - A Modular Tool Architecture for Parallel Program Analysis. In: Kosch, H., Böszörményi, L., Hellwagner, H. (eds.) Euro-Par 2003. LNCS, vol. 2790, pp. 74–80. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  12. 12.
    Seidl, S.: VTF3 - A Fast Vampir Trace File Low-Level Library. personal communications (May 2002)Google Scholar
  13. 13.
    The ASCI Project. The IRS Benchmark Code: Implicit Radiation Solver (2003),
  14. 14.
    Wolf, F., Mohr, B.: EARL - A Programmable and Extensible Toolkit for Analyzing Event Traces of Message Passing Programs. Technical report, Research Center Jülich, FZJ-ZAM-IB-9803 (April 1998)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Andreas Knüpfer
    • 1
  • Wolfgang E. Nagel
    • 1
  1. 1.Center for High Performance ComputingDresden University of TechnologyGermany

Personalised recommendations