Performance Issues in Parallel Processing Systems

1. Adve, V., Mellor-Crummey, J., Wang, J.-C., and Reed, D. Integrating Compilation and Performance Analysis for Data-Parallel Programs. In Proceedings of Supercomputing’95 (November 1995).

   Google Scholar 

2. Adve, V. S., Mellor-Crummey, J., Anderson, M., Kennedy, K., Wang, J., and Reed, D. A. Integrating Compilation and Performance Analysis for Data-Parallel Programs. In Proceedings of the Workshop on Debugging and Performance Tuning for Parallel Computing Systems, M. L. Simmons, A. H. Hayes, D. A. Reed, and J. Brown, Eds. IEEE Computer Society Press, 1994.

   Google Scholar 

3. Balasundaram, V., Fox, G., Kennedy, K., and Kremer, U. A Static Performance Estimator to Guide Data Partitioning Decisions. In 3rd ACM Sigplan Symposium on Principles and Practice of Parallel Programming (PPoPP) (April 1991).

   Google Scholar 

4. Benkner, S. Vienna Fortran Compilation System-Version 2.0-User’s Guide. Tech. rep., University of Vienna, 1995.

   Google Scholar 

5. Benkner, S., and Pantano, M. HPF+: Optimizing HPF for Advanced Applications. Supercomputer 13,2 (1997), 31–43.

   Google Scholar 

6. Benkner, S., Sanjari, K., Sipkova, V., and Velkov, B. Parallelizing Irregular Applications with the Vienna HPF+ Compiler VFC. In HPCN Europe (April 1998), Lecture Notes in Computer Science, Springer-Verlag.

   Google Scholar 

7. Bodin, F., Beckman, P., Gannon, D., Gotwals, J., Narayana, S., Srinivas, S., and Winnicka, B. Sage++: An Object-Oriented Toolkit and Class Library for Building Fortran and C++ Restructuring Tools. In OON-SKI’94 Proceedings of the First Annual Object-Oriented Numerics Conference (April 1993), pp. 122–138.

   Google Scholar 

8. Bodin, F., Beckman, P., Gannon, D., Narayana, S., and Yang, S. Distributed pC++: Basic Ideas for an Object Parallel Language. In OON-SKI’93 Proceedings of the First Annual Object-Oriented Numerics Conference (April 1993), pp. 1–24.

   Google Scholar 

9. Calzarossa, M., Massari, L., Merlo, A., Pantano, M., and Tessera, D. Medea: A Tool for Workload Characterization of Parallel Systems. IEEE Parallel and Distributed Technology 3,4 (November 1995), 72–80.

   Article  Google Scholar 

10. Calzarossa, M., Massari, L., Merlo, A., Pantano, M., and Tessera, D. Integration of a Compilation System and a Performance Tool: The HPF+ Approach. In HPCN Europe (April 1998), Lecture Notes in Computer Science, Springer-Verlag.

    Google Scholar 

11. Chang, P. P., Mahlke, S. A., and Hwu, W. W. Using Profile Information to Assist Classic code Optimization. Software-Practice & Experience (to appear).

    Google Scholar 

12. Cleveland, W. S., and MiGill, M. E., Eds. Dynamic Graphics for Statistics. Wadsworth & Brooks/Cole, 1988.

    Google Scholar 

13. Colwell, R., Nix, R., O’Donnell, J., Papwoth, D., and Rodman, P. A VLIW Architecture for a Trace Scheduling Compiler. In Proceedings of the Second International Conference on Architectural Support for Programming Languages and Operating Systems (October 1987).

    Google Scholar 

14. Couch, A.Graphical Representations of Program Performance on Hypercube Message-Passing Multiprocessors. PhD thesis, Tufts University, Department of Computer Science, 1988.

    Google Scholar 

15. DeRose, L., Zhang, Y., and Reed, D. Svpablo: A Multi-Language Performance Analysis System. In Computer Performance Evaluation Modelling Techniques and Tools (September 1998), R. Puigjaner, N. Savino, and B. Serra, Eds., Lecture Notes in Computer Science, vol. 1469, Springer-Verlag, pp. 352–355.

    Google Scholar 

16. Fahringer, T. Estimating and Optimizing Performance for Parallel Programs. IEEE Computer 28,11 (November 1995), 47–56.

    Google Scholar 

17. Fahringer, T. Effective Symbolic Analysis to Support Parallelizing Compilers and Performance Analysis. In HPCN Europe (April 1997), Lecture Notes in Computer Science, Springer-Verlag.

    Google Scholar 

18. Fisher, J. Trace Scheduling: A Technique for Global Microcode Compactation. IEEE Tranactions on Computers (July 1981), 478–490.

    Google Scholar 

19. Foster, I., and Kesselman, C., Eds. The Grid: Blueprint for a New Computing Infrastructure. Morgan-Kaufmann, 1998.

    Google Scholar 

20. Graham, S., Kessler, P., and McKusick, M. gprof: A Call Graph Execution Profiler. In Proceedings of the SIGPLAN’82 Symposium on Compiler Construction (Boston, MA, June 1982), Association for Computing Machinery, pp. 120–126.

    Google Scholar 

21. Gu, W., Eisenhauer, G., Schwan, K., and Vetter, J. Falcon: On-line monitoring and steering of parallel programs. Concurrency: Practice and Experience 10,9 (1998), 699–736.

    Article  MATH  Google Scholar 

22. Hartleb, F., and Mertsiotakis, V. Bounds for the Mean Runtime of Parallel Programs. In Computer Performance Evaluation’ 92: Modeling Techniques and Tools (1992), R. Pooley and J. Hillston, Eds., pp. 197–210.

    Google Scholar 

23. Heath, M. T., and Etheridge, J. A. Visualizing the Performance of Parallel Programs. IEEE Software (Sept. 1991), 29–39.

    Google Scholar 

24. Heath, M. T., Malony, A. D., and Rover, D. T. The Visual Display of Parallel Performance Data. Computer 28,11 (1995), 21–8.

    Article  Google Scholar 

25. Hurley, C., and Buja, A. Analyzing High-dimensional Data with Motion Graphics. SIAM Journal of Scientific and Statistical Computing 11,6 (Nov. 1990), 1193–1211.

    Article  MATH  Google Scholar 

26. Kraemer, E., and Stasko, J. T. The Visualization of Parallel Systems: An Overview. Jour. Parallel and Distributed Computing 18,2 (1993), 105–17.

    Article  Google Scholar 

27. Larus, J. R., and Schnarr, E. EEL: Machine-Independent Executable Editing. In Proceedings of the SIGPLAN’ 95 Conference on Programming Languages Design and Impelementation (PLDI) (June 1995).

    Google Scholar 

28. LeBlanc, T. J., and Markatos, E. P. Operating System Support for Adaptive Real-time Systems. In Proceedings of the Seventh IEEE Workshop on Real-Time Operating Systems and Software (May 1990), pp. 1–10.

    Google Scholar 

29. Malony, A. D., Reed, D. A., and Wijshoff, H. Performance Measurement Intrusion and Perturbation Analysis. IEEE Transactions on Parallel and Distributed Systems 3,4 (July 1992), 433–450.

    Article  Google Scholar 

30. Mendes, C. L.Performance Scalability Prediction on Multicomputers. PhD thesis, University of Illinois at Urbana-Champaign, May 1997.

    Google Scholar 

31. Mendes, C. L., Wang, J.-C., and Reed, D. A. Automatic Performance Prediction and Scalability Analysis for Data Parallel Programs. In Proceedings of the CRPC Workshop on Data Layout and Performance Prediction (Houston, April 1995).

    Google Scholar 

32. Miller, B. P., Callaghan, M. D., Cargille, J. M., Hollingsworth, J. K., Irvin, R. B., Karavanic, K. L., Kunchithapadam, K., and Newhall, T. The Paradyn Parallel Performance Measurement Tools. IEEE Computer 28,11 (November 1995), 37–46.

    Google Scholar 

33. MIPS Technologies Inc. MIPS R10000 Microprocessor User’s Manual, 2.0 ed., 1996.

    Google Scholar 

34. Mohr, B., Malony, A., and Cuny, J. Tau Tuning and Analysis Utilities for Portable Parallel Programming. In Parallel Programming using C++, G. Wilson, Ed. M.I.T. Press, 1996.

    Google Scholar 

35. Nickolayev, O. Y., Roth, P. C., and Reed, D. A. Real-time Statistical Clustering for Event Trace Reduction. International Journal of Supercomputer Applications and High Performance Computing (1997).

    Google Scholar 

36. Reed, D. A. Experimental Performance Analysis of Parallel Systems: Techniques and Open Problems. In Proceedings of the 7th International Conference on Modelling Techniques and Tools for Computer Performance Evaluation (May 1994), pp. 25–51.

    Google Scholar 

37. Reed, D. A., Aydt, R. A., DeRose, L., Mendes, C. L., Ribler, R. L., Shaffer, E., Simitci, H., Vetter, J. S., Wells, D. R., Whitmore, S., and Zhang, Y. Performance Analysis of Parallel Systems: Approaches and Open Problems. In Proceedings of the Joint Symposium on Parallel Processing (JSPP) (June 1998), pp. 239–256.

    Google Scholar 

38. Reed, D. A., Aydt, R. A., Noe, R. J., Roth, P. C., Shields, K. A., Schwartz, B., and Tavera, L. F. Scalable Performance Analysis: The Pablo Performance Analysis Environment. In Proceedings of the Scalable Parallel Libraries Conference (1993), A. Skjellum, Ed., IEEE Computer Society.

    Google Scholar 

39. Reed, D. A., Elford, C. L., Madhyastha, T., Scullin, W. H., Aydt, R. A., and Smirni, E. I/O, Performance Analysis, and Performance Data Immersion. In Proceedings of MASCOTS’ 96 (Feb. 1996), pp. 1–12.

    Google Scholar 

40. Ribarsky, W., Ayers, E., Eble, J., and Mukherjea, S. Using Glyphmaker to Create Customized Visualizations of Complex Data. IEEE Computer, July (1994), 57–64.

    Google Scholar 

41. Ribler, R., Vetter, J., Simitci, H., and Reed, D. Autopilot: Adaptive Control of Distributed Applications. In Proc. Seventh IEEE Int’l Symp. High Performance Distributed Computing (HPDC) (1998), pp. 172–9.

    Google Scholar 

42. Robertson, G. G., Card, S. K., and Mackinlay, J. D. Information Visualization using 3D Interactive Animation. Communications of the ACM 36,4 (1993), 56–71.

    Article  Google Scholar 

43. Rosenblum, L. J. Research Issues in Scientific Visualization. IEEE Computer Graphics and Applications 14,2 (1994), 61–3.

    Article  Google Scholar 

44. Stasko, J., Domingue, J., Brown, M. H., and Price, B. A., Eds. Software Visualization: Programming as a Multimedia Experience,. MIT Press, Cambridge, MA, 1998.

    Google Scholar 

45. Sun, X. H., Pantano, M., and Fahringer, T. Performance Range Comparison for Restructuring Compilation. In IEEE International Conference on Parallel Processing (Minneapolis, August 1998), pp. 595–602.

    Google Scholar 

46. Vetter, J. S. Computational Steering Annotated Bibliography. SIGPLAN Notices 32,6 (1997), 40–4.

    Article  Google Scholar 

47. Yan, J. C., Sarukkai, S. R., and Mehra, P. Performance Measurement, Visualization and Modeling of Parallel and Distributed Programs using the AIMS Toolkit. Software Practice & Experience 25,4 (April 1995), 429–461.

    Article  Google Scholar 

48. Zagha, M., Larson, B., Turner, S., and Itzkowitz, M. Performance Analysis Using the MIPS R10000 Performance Counters. In Proceedings of Supercomputing’96 (November 1996).

    Google Scholar 

Download references