An Analytic Performance Model Of Parallel Systems That Perform N tasks Using P Processors That Can Fail (2001) [5 citations — 4 self]
Abstract:
We present a family of Markov models for analyzing the performance of parallel /distributed processors that execute a job consisting of N independent tasks in parallel using P processors. The model is a Markov Chain with states representing service and failure rates with k (0! k P) active processors. The task-times and processor failures are both exponentially distributed. We derive a number of expressions to determine the mean execution time, probability of success, work, and other measurable quantities, all conditioned on the job finishing successfully. A prototype, implemented using an extended version of ACMPI, is used for actual experiments that are based on simulated task-times and processor failures. We present our results comparing the analytic model with the prototype for a range of values of processor failure rates. We then discuss extensions of the model and issues related to communication costs, approximations and effect of task-time distributions. 1
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