Abstract
This paper describes a toolset, PACE, that provides detailed predictive performance information throughout the implementation and execution stages of an application. It is structured around a hierarchy of performance models that describes distributed computing systems in terms of its software, parallelisation and hardware components, providing performance information concerning expected execution time, scalability and resource use of applications. A principal aim of the work is to provide a capability for rapid calculation of relevant performance numbers without sacrificing accuracy. The predictive nature of the approach provides both pre- and post-implementation analyses, and allows implementation alternatives to be explored prior to the commitment of an application to a system. Because of the relatively fast analysis times, these techniques can be used at run-time to assist in application steering and efficient management of the available system resources.
Chapter PDF
Keywords
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.
References
I Foster, C Kesselman, The GRID., Morgan Kaufman (1998)
G.R. Nudd, D.J. Kerbyson, E. Papaefstathiou, S.C. Perry, J.S. Harper, D.V. Wilcox, „PACE. A Toolset for the Performance Prediction of Parallel and Distributed Systems“, in the Journal of High Performance Applications, Vol. 14, No. 3 (2000) 228–251
D.G. Green et al. „HPCN tools: a European perspective“, IEEE Concurrency, Vol. 5(3) (1997) 38–43
I. Gorton and I.E. Jelly., „Software engineering for parallel and distributed systems, challenges and opportunities“, IEEE Concurrency, Vol. 5(3) (1997) 12–15
E Papaefstathiou et al., An overview of the CHIP3S performance prediction toolset for parallel systems., in Proc. of 8th ISCA Int. Conf. on Parallel and Distributed Computing Systems (1995) 527–533
C.U. Smith, „Performance Engineering of Software Systems., Addison Wesley (1990).
E. Papaefstathiou et al., „An introduction to the CHIP3S language for characterising parallel systems in performance studies., Research Report RR335, Dep. of Computer Science, University of Warwick (1997)
Stanford Compiler Group, „The SUIF Library“, The SUIF compiler documentation set, Stanford University (1994)
Harper, J.S., Kerbyson, D.J., Nudd, G.R.: Analytical Modeling of Set-Associative Cache Behavior, IEEE Transactions on Computers, Vol. 48(10) (1999) 1009–1024
D.A. Reed, et al., „Scalable Performance Analysis: The Pablo Analysis Environment“, in: Proc. Scalable Parallel Libraries Conf., IEEE Computer Society (1993)
R. Wolski, „Dynamically Forecasting Network Performance Using the Network Weather Service“, UCSD Technical Report, TR-CS96-494 (1996)
J. Gehring, A. Reinefeld, MARS-A framework for minizing the job execution time in a metacomputing environment“, Future Generation Computer Systems, Vol. 12 (1996) 87–99
D.J. Kerbyson, E. Papaefstathiou and G.R. Nudd, „Application execution steering using on-the-fly performance prediction“, in: High Performance Computing and Networking, Vol 1401, LNCS Springer-Verlag (1998) 718–727
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2000 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Kerbyson, D.J., Harper, J.S., Papaefstathiou, E., Wilcox, D.V., Nudd, G.R. (2000). Use of Performance Technology for the Management of Distributed Systems. In: Bode, A., Ludwig, T., Karl, W., Wismüller, R. (eds) Euro-Par 2000 Parallel Processing. Euro-Par 2000. Lecture Notes in Computer Science, vol 1900. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44520-X_19
Download citation
DOI: https://doi.org/10.1007/3-540-44520-X_19
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-67956-1
Online ISBN: 978-3-540-44520-3
eBook Packages: Springer Book Archive