Techniques for delayed binding of monitoring mechanisms to application-specific instrumentation points

Proceedings of the International Conference on Parallel Processing

Volumn , Issue , 1998, Pages 477-484

  Vetter, Jeffrey ^a   Schwan, Karsten ^b  

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

^b Georgia Institute of Technology   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BINS; ONLINE SYSTEMS; PROGRAM DEBUGGING;

APPLICATION SPECIFIC; EXECUTION PATHS; MISMATCH MONITORING; MONITORING MECHANISMS; MONITORING SYSTEM; ON-LINE INTERACTIONS; RUNTIMES;

MONITORING;

EID: 33847420715     PISSN: 01903918     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICPP.1998.708520     Document Type: Conference Paper

References (25)

1. G. Ammons, T. Ball, and J. Larus. Exploiting hardware performance counters with flow and context sensitive profiling. In Proc. ACM SIGPLAN Programming Language Design and Implementation (PLDI), 1997.
2. T. Anderson and E. Lazowska. Quartz: A tool for tuning parallel program performance. In Proc. 1990 SIGMETRICS Conf.Measurement andModeling Computer Systems, pages 115-125, Boston, 1990.
3. T. Ball and J. Larus. Optimally profiling and tracing programs. ACM Trans. Programming Languages and Systems, 16(4):1319-60, 1994.
4. P. Bates. Debugging heterogeneous distributed systems using event-based models of behavior. ACM Trans. Computer Systems, 13(1):1-31, 1995.
5. D. Bhatt. Scalable parallel instrumentation (SPI): an environment for developing parallel system instrumentation. In Proc. Intel Supercomputer Users Group Conf., pages 98-104, 1994.
6. D. Brown, S. Hackstadt, A. Malony, B. Mohr, J. Dongarra, and B. Tourancheau. Program analysis environments for parallel language systems: the tau environment. In Proc. Second Workshop on Environments and Tools for Parallel Scientific Computing, pages 162-71, 1994.
7. M. Copperman and C. McDowell. A further note on hennessy's 'symbolic debugging of optimized code'. ACM Trans.Programming Languagesand Systems, 15(2):357-65, 1993.
8. S. Graham, P. Kessler, and M. McKusick. Gprof: A call graph execution profiler. SIGPLAN Notices (SIGPLAN '82 Symp. Compiler Construction), 17(6):120-126, 1982.
9. W. Gu, G. Eisenhauer, E. Kraemer, K. Schwan, J. Stasko, J. Vetter, and N. Mallavarupu. Falcon: On-line monitoring and steering of large-scale parallel programs. In Proc. Frontiers of Massively Parallel Computation, 1995.
10. W. Gu, J. Vetter, and K. Schwan. An annotated bibliography of interactive program steering. SIGPLAN Notices, 29(9):140-8, 1994.
11. S. Hackstadt, A. Malony, L. Bouge, P. Fraigniaud, A. Mignotte, and Y. Robert. Distributed array query and visualization for high performance fortran. In Proc. Euro-Par '96 Parallel Processing., pages 55-63, 1996.
12. E. Kraemer and J. Stasko. The visualization of parallel systems: An overview. Jour. Parallel and Distributed Computing, 18(2):105-117, 1993.
13. J. Kundu and J. Cuny. A scalable, visual interface for debugging with event-based behavioral abstraction. In Proc. Fifth Symp. the Frontiers of MassivelyParallel Computation, pages 472-9, 1995.
14. A. Malony. Event-based performance perturbation: a case study. SIGPLAN Notices (Third ACMSIGPLAN Symp.Principles and Practice ofParallelProgramming), 26(7):201-12, 1991.
15. A. Malony, D. Reed, and H. Wijshoff. Performance measurement intrusion and perturbation analysis. IEEE Trans. Parallel and Distributed Systems, 3(4):433-50, 1992.
16. D. Marinescu, H. Siegel, J. Lumpp, and T. Casavant. Models for monitoring and debugging tools for parallel and distributed software. Jour. Parallel and Distributed Computing, 9:171-184, 1990.
17. B. Miller, M. Callaghan, J. Cargille, J. Hollingsworth, R. Irvin, K. Karavanic,K. Kunchithapadam, and T. Newhall. The paradyn parallel performance measurement tool. Computer, 28(11):37-46, 1995.
18. B. Miller, M. Clark, J. Hollingsworth, S. Kierstead, S.-S. Lim, and T. Torzewski. IPS-2: The second generation of a parallel programmeasurement system. IEEE Trans.Parallel and Distributed Systems, 1:206-217, 1990.
19. D. Ogle, K. Schwan, and R. Snodgrass. Applicationdependent dynamic monitoring of distributed and parallel systems. IEEE Trans. Parallel and Distributed Systems, 4(7):762-778, 1993.
20. D. Reed, K. Shields, W. Scullin, L. Tavera, and C. Elford. Virtual reality and parallel systems performance analysis. Computer, 28(11):57-67, 1995.
21. R. Ribler, J. Vetter, H. Simitci, and D. Reed. Autopilot: adaptive control of distributed applications. In Proc. Seventh IEEE Int'l Symp.High PerformanceDistributed Computing, 1998.
22. J. Vetter and K. Schwan. High performance computational steering of physical simulations. In Proc. Int'l Parallel Processing Symp., pages 128-132,Geneva, 1997.
23. A. Waheed and D. Rover. A structured approach to instrumentation system development and evaluation. In Proc. Supercomputing 95, pages 1-1, 1995.
24. R. Wismuller. Debugging of globally optimized programs using data flow analysis. SIGPLAN Notices (ACMSIGPLAN '94 Conf. Programming LanguageDesign and Implementation), 29(6):278-89, 1994.
25. J. Yan, E. Hesham, and B. Shriver. Performance tuning with AIMS-an automated instrumentation andmonitoring system for multicomputers. In Proc. Twenty-Seventh Hawaii Int'l Conf. System Sciences. Vol.II: Software Technology, pages 625-33, 1994.