Statistical Simulation of Symmetric Multiprocessor Systems

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	Similar Articles Articles by Sebastien Nussbaum Articles by James E. Smith

35th Annual Simulation Symposium

San Diego, California

April 14-April 18

ISBN: 0-7695-1552-5

	ASCII Text	x
	Sebastien Nussbaum, James E. Smith, "Statistical Simulation of Symmetric Multiprocessor Systems," Simulation Symposium, Annual, pp. 0089, 35th Annual Simulation Symposium, 2002.

	BibTex	x
	@article{ 10.1109/SIMSYM.2002.1000093, author = {Sebastien Nussbaum and James E. Smith}, title = {Statistical Simulation of Symmetric Multiprocessor Systems}, journal ={Simulation Symposium, Annual}, volume = {0}, year = {2002}, isbn = {0-7695-1552-5}, pages = {0089}, doi = {http://doi.ieeecomputersociety.org/10.1109/SIMSYM.2002.1000093}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Simulation Symposium, Annual TI - Statistical Simulation of Symmetric Multiprocessor Systems SN - 0-7695-1552-5 SP EP A1 - Sebastien Nussbaum, A1 - James E. Smith, PY - 2002 KW - Statistical KW - Simulation KW - Performance KW - Fast KW - SMP KW - systems KW - multiprocessor KW - out-of-order KW - superscalar KW - SimpleMP KW - Architecture KW - Memory Hierarchy KW - shared bus VL - 0 JA - Simulation Symposium, Annual ER -

Sebastien Nussbaum, Sun Microsystems, Inc.

James E. Smith, University of Wisconsin at Madison

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/SIMSYM.2002.1000093

Statistical simulation is driven by a stream of randomly generated instructions, based on statistics collected during a single detailed simulation. This method can give accurate performance estimates within minutes, allowing a large design space to be simulated quickly. Prior work has applied this technique to superscalar processors. We evaluate the extension of statistical simulation to Symmetric Multiprocessing (SMP) systems. Key program parameters are identified, and program statistics are collected during detailed simulations for both multiprogrammed workloads (SpecInt) and parallel scientific workload (Splash-2). The accuracy of statistical simulation is evaluated at different levels of model detail, and it is shown that for multiprogrammed workloads a 10% average error can be achieved, and for parallel benchmark programs 15% average error can be achieved.

Index Terms:

Statistical, Simulation, Performance, Fast, SMP, systems, multiprocessor, out-of-order, superscalar, SimpleMP, Architecture, Memory Hierarchy, shared bus

Citation:

Sebastien Nussbaum, James E. Smith, "Statistical Simulation of Symmetric Multiprocessor Systems," ss, pp.0089, 35th Annual Simulation Symposium, 2002

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