Abstract
Most performance tools that run on Massively Parallel (MP) systems do not scale up as the number of nodes increases. We studied the scalability problem of MP system performance tools and proposed a solution, replacing the two-level data collection structure by hierarchal one. To demonstrate that hierarchical data collection structure solves the scalability problem, we synthesized an implementation model to implement the performance data collection in MP systems. This paper presents our synthetic implementation results.
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References
Alderson, W.C.L.A., Randell, B.: Thrashing in a multiprogrammed paging system. Operating Systems Techniques by Hoare and Perrott, 152–167 (1972)
Denning, P.J.: The working set model for program behavior. Communication of the ACM (5), 323–333 (1968)
Eisenhauer, G., Schroeder, B., Schwan, K., Martin, V., Vetter, J.: DataExchange: High Performance Communication in Distributed Laboratories. Ninth International Conference on Parallel and Distributed Computing and Systems (October 1997)
D.A.R., et al.: Scalable Performance Analysis: The Pablo Performance Analysis Environment. In: IEEE Scalable Performance Libraries Conference, IEEE Service Center, Piscaataway (1993)
Gu, W., Eisenhauer, G., Schwan, K.: Falcon: On-line Monitoring and Steering of Parallel Programs. Concurrency: Practice and Experience (1995)
Hansen, P.B.: Operating System Principles. Prentice-Hall, Inc., Englewood Cliffs (1973)
Jong, C.J., Maccabe, A.B.: A simulator for performance tools in massively parallel system. Postceedings of The International Conference on Parallel and Distributed Processing Techniques and Applications (June 2003)
Kindler, T., Schwan, K., Silva, D., Trauner, M., Alyea, F.: A Paraller Spectral Model for Atmospheric Transport Processes. Concurrency: Practice and Experience 8, 639–666 (1996)
Liao, C., Martonosi, M., Clark, D.W.: Performance Monitoring in a Myrinet- Connected Shrimp Cluster. In: Symposium on Parallel and Distributed Tools, P.O. Box 12114 Church Street Station, New York, N.Y. 10257, pp. 21–29 (August 1998) The Association for Computing Machinery
Ribler, R.L., Vetter, J.S., Simitci, H., Reed, D.A.: Autopilot: Adaptive Control of Distributed Applications. In: 7th IEEE Symposium on High- Performance Distributed Computing, Chicago, IL (July 1998)
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Jong, C.J., Maccabe, A.B. (2004). Synthetic Implementations of Performance Data Collection in Massively Parallel Systems. In: Li, M., Sun, XH., Deng, Q., Ni, J. (eds) Grid and Cooperative Computing. GCC 2003. Lecture Notes in Computer Science, vol 3033. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24680-0_1
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DOI: https://doi.org/10.1007/978-3-540-24680-0_1
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