## Abstract

Performance analysis of concurrent executions in parallel systems has been recognized as a challenging problem. The aim of this research is to study approximate but efficient solution techniques for this problem. We model the structure of a parallel machine and the structure of the jobs executing on such a system. We investigate rich classes of jobs, which can be expressed by series, parallel-and, parallel-or, and probabilistic-fork. We propose an efficient performance prediction method for these classes of jobs running on a parallel environment which is modeled by a standard queueing network model. The proposed prediction method is computationally efficient, it has polynomial complexity in both time and space. The time complexity is O(C^{2}N^{2}K) and the space complexity is O(C^{2}N^{2}K), where C is the number of job classes in the system, the number of tasks in each job class is O(N), and K is the number of service centers in the queueing model. The accuracy of the approximate solution is validated via simulation.

Original language | English |
---|---|

Pages (from-to) | 491-508 |

Number of pages | 18 |

Journal | IEEE Transactions on Parallel and Distributed Systems |

Volume | 11 |

Issue number | 5 |

DOIs | |

State | Published - May 2000 |