Analytic Queueing Network Models for Parallel Processing of Task Systems
IEEE Transactions on Computers
Solving problems on concurrent processors. Vol. 1: General techniques and regular problems
Solving problems on concurrent processors. Vol. 1: General techniques and regular problems
Approximate Analysis of Fork/Join Synchronization in Parallel Queues
IEEE Transactions on Computers
Performance Analysis of Parallel Processing Systems
IEEE Transactions on Software Engineering
A modeling methodology for the analysis of concurrent systems and computations
Journal of Parallel and Distributed Computing
CSIM: a C-based process-oriented simulation language
WSC '86 Proceedings of the 18th conference on Winter simulation
Open, Closed, and Mixed Networks of Queues with Different Classes of Customers
Journal of the ACM (JACM)
Mean-Value Analysis of Closed Multichain Queuing Networks
Journal of the ACM (JACM)
Probability and Statistics with Reliability, Queuing and Computer Science Applications
Probability and Statistics with Reliability, Queuing and Computer Science Applications
Predicting Performance of Parallel Computations
IEEE Transactions on Parallel and Distributed Systems
The approximate solution of large queueing network models
The approximate solution of large queueing network models
Theory, Volume 1, Queueing Systems
Theory, Volume 1, Queueing Systems
A new performance evaluation approach for system level design space exploration
Proceedings of the 15th international symposium on System Synthesis
Parallel program performance prediction using deterministic task graph analysis
ACM Transactions on Computer Systems (TOCS)
Low-Cost Static Performance Prediction of Parallel Stochastic Task Compositions
IEEE Transactions on Parallel and Distributed Systems
A simulator for adaptive parallel applications
Journal of Computer and System Sciences
Parallel execution time prediction of the multitask parallel programs
Performance Evaluation
Performance modeling and analysis of correlated parallel computations
Parallel Computing
A simulator for parallel applications with dynamically varying compute node allocation
IPDPS'06 Proceedings of the 20th international conference on Parallel and distributed processing
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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.