Issue No. 10 - October (1991 vol. 17)

ISSN: 0098-5589

pp: 1005-1012

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/32.99189

ABSTRACT

<p>Stochastic bounds are obtained on execution times of parallel programs when the number of processors is unlimited. A parallel program is considered to consist of interdependent tasks with synchronization constraints. These constraints are described by an acyclic directed graph called a task graph. The execution times of tasks are considered to be independently identically distributed (i.i.d.) random variables. The performance measure of interest is the overall execution of the considered parallel program (task graph). Stochastic bound methods are applied to obtain lower and upper bounds on this measure. Another upper bound is obtained for parallel programs having 'new better than used in expectation' (NBUE) random variables as task execution times. NBUE random variables are replaced with exponential random variables of the same mean to derive this upper bound.</p>

INDEX TERMS

stochastic bound methods; execution times; parallel programs; interdependent tasks; synchronization constraints; acyclic directed graph; task graph; performance measure; NBUE; exponential random variables; directed graphs; parallel programming; performance evaluation; stochastic processes

CITATION

J. Vincent and N. Yazia-Pekergin, "Stochastic Bounds on Execution Times of Parallel Programs," in

*IEEE Transactions on Software Engineering*, vol. 17, no. , pp. 1005-1012, 1991.

doi:10.1109/32.99189

CITATIONS