An efficient format for nearly constant-time access to arbitrary time intervals in large trace files

Scientific Programming

Volumn 16, Issue 2-3, 2008, Pages 155-165

  Chan, Anthony ^a,b   Gropp, William ^a,c   Lusk, Ewing ^a  

^a ARGONNE NATIONAL LABORATORY   (United States)

^b UNIVERSITY OF CHICAGO   (United States)

^c University of Illinois at Urbana Champaign   (United States)

Author keywords

Message passing interface; Performance visualization; Trace file

Indexed keywords

DIGITAL STORAGE;

ARBITRARY TIME; CONSTANT TIME; MESSAGE PASSING INTERFACE; PARALLEL APPLICATION; PERFORMANCE VISUALIZATION; TIME INDEPENDENTS; TIME WINDOWS; TRACE FILES;

MESSAGE PASSING;

EID: 48849117708     PISSN: 10589244     EISSN: None     Source Type: Journal    
DOI: 10.3233/SPR-2008-0252     Document Type: Article

References (22)

1. R tree, http://en.wikipedia.org/wiki/R-tree.
2. J. Chassin de Kergommeaux and B. Stein, Pajé, an extensible environment for visualizing multi-threaded programs executions, in: Proceedings of Euro-Par 2000, A. Bode et al., eds, LNCS, Vol. 1900, Springer-Verlag, Berlin, 2000, pp. 133-140.
3. J. Chassin de Kergommeaux, B. Stein and P.E. Bernard, Pajé, an interactive visualization tool for tuning multi-threaded parallel applications, Parallel Computing 26 (2000), 1253-1274.
4. TimeScan Multiprocess Event Analyzer, http://www.etnus.com/products/ timescan.
5. J. Gemenez, Are you sure that tracing is not scalable?, in: Dagstuhl Seminar, "Code Instrumentation and Modeling for Performance Analysis", http://kathrin.dagstuhl.de/07341, August 2007.
6. A. Guttman, R-trees: a dynamic index structure for spatial searching, in: SIGMOD'84: Proceedings of the 1984 ACM SIGMOD International Conference on Management of Data, ACM Press, New York, NY, USA, 1984, pp. 47-57.
7. D. Hankerson, G.A. Harris and P.D. Johnson Jr., Introduction to Information Theory and Data Compression, CRC Press, Boca Raton, FL, 1998.
8. M.T. Heath, Recent developments and case studies in performance visualization using ParaGraph, in: Performance Measurement and Visualization of Parallel Systems, G. Haring and G. Kotsis, eds, Elsevier Science Publishers, Amsterdam, 1993, pp. 175-200.
9. M.T. Heath and J.E. Finger, Paragraph: A performance visualization tool for MPI, http://www.csar.uiuc.edu/software/paragraph.
10. V. Herrarte and E. Lusk, Studying parallel program behavior with upshot, Technical Report ANL-91/15, Argonne National Laboratory, 1991.
11. IBM, IBM Parallel Environment for AIX, Vol. 2 (Chapter 3), IBM, 1998; http://www.s390.ibm.com/bookmgr-cgi/bookmgr.cmd/books/PEOP2240/CONTENTS.
12. H. Jagode, Random access to event traces with OTF, August 2007; http://kathrin.dagstuhl.de/07341/Materials2.
13. E. Karrels and E. Lusk, Performance analysis of MPI programs, in: Proceedings of theWorkshop on Environments and Tools for Parallel Scientific Computing, J. Dongarra and B. Tourancheau, eds, SIAM Publications, Philadelphia, PA, 1994, pp. 195-200.
14. E. Lusk, Performance visualization for parallel programs, Theoretica Chimica Acta 84 (1993), 377-384.
15. A. Malony, D. Hammerslag and D. Jablonowski, TraceView: A trace visualization tool, IEEE-Software 8(5) (1991), 19-28.
16. A.D. Malony, D.A. Reed and H.A.G. Wijshoff, Performance measurement intrusion and perturbation analysis, IEEE Transactions on Parallel and Distributed Systems 3(4) (1992), 433-450.
17. F. Mueller, M. Noeth, P. Ratn, M. Schulz and B.R. de Supinski, Scalable compression and replay of communication traces, August 2007; http://kathrin.dagstuhl.de/07341/Materials2.
18. Vampir 2.0 - Visualization and analysis of MPI programs, http://www.pallas.de/pages/vampir.htm.
19. D.A. Reed, R.A. Aydt, R.J. Noe, P.C. Roth, K.A. Shields, B. Schwartz and L.F. Tavera, Scalable performance analysis: The Pablo performance analysis environment, in: Proceedings of the Scalable Parallel Libraries Conference, A. Skjellum, ed., IEEE Computer Society, Los Alamitos, CA, 1993.
20. G. Tomas and C.W. Ueberhuber, Visualization of Scientific Parallel Programs, LNCS, Vol. 771, Springer-Verlag, Berlin, 1994.
21. C.E. Wu, A. Bolmarcich, M. Snir, D. Wootton, F. Parpia, A. Chan, E.L. Lusk andW. Gropp, From trace generation to visualization: A performance framework for distributed parallel systems. in: Proceedings of SC2000, Los Alamitos, CA, 2000.
22. O. Zaki, E. Lusk, W. Gropp and D. Swider, Toward scalable performance visualization with Jumpshot, High Performance Computing Applications 13(2) (1999), 277-288.