Stochastic bounds on execution times of parallel computations

Abstract

We obtain stochastic bounds on execution times of parallel computations assuming ideal conditions for shared resources. A parallel computation is modelled as a task system with precedence constraints expressed as a directed acyclic graph (DAG). The task execution times are assumed independent random variables. The performance measure considered is the overall execution time of the computation. To obtain upper bounds on this measure, we apply stochastic ordering and stochastic comparison techniques.<>