A Deterministic Model for Parallel Program Performance Evaluation

A Deterministic Model for Parallel Program Performance Evaluation (1998)

by Vikram S. Adve , Mary K. Vernon

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Datum	Value	Source
TITLE	A Deterministic Model for Parallel Program Performance Evaluation	SVM HeaderParse 0.1
AUTHOR NAME	Vikram S. Adve	SVM HeaderParse 0.1
AUTHOR AFFIL	University; and	SVM HeaderParse 0.2
AUTHOR NAME	Mary K. Vernon	SVM HeaderParse 0.1
AUTHOR AFFIL	University of Wisconsin-Madison	SVM HeaderParse 0.2
ABSTRACT	Parallelism Metrics Previous studies have shown that a few key parameters such as the fraction of sequential work [Amdahl 1967], average parallelism [Eager et al. 1989], and variance of parallelism [Sevcik 1989] can each provide a concise yet powerful characterization of program performance. For example, Eager et al. have derived bounds on speedup for arbitrary, work-conserving, task scheduling functions using the average parallelism (A) alone [Eager et al. 1989]. Sevcik has shown that for scheduling parallel jobs on a multiprocessor system, where only very concise information about the arriving jobs can be used, effective scheduling is possible using just two parameters, average parallelism and variance of parallelism [Sevcik 1989]. While simple parameters like the fraction of sequential work and Pmax can be easily estimated for a given program, other parameters like A and the variance of parallelism are much more difficult to obtain. (For example, consider estimating A for PSIM or ...	user correction - Legacy Corrections
YEAR	1998	INFERENCE
VENUE TYPE	TECHREPORT	INFERENCE
TECH	Technical Report CS-TR98-333	INFERENCE
CITATIONS	50 found	ParsCit 1.0