Stochastic High-Level Petri Nets and Applications
IEEE Transactions on Computers
An analytic model for parallel Gaussian elimination on a binary N-Cube architecture
C3P Proceedings of the third conference on Hypercube concurrent computers and applications - Volume 2
Performance Equivalent Analysis of Workflow Systems Based on Stochastic Petri Net Models
EDCIS '02 Proceedings of the First International Conference on Engineering and Deployment of Cooperative Information Systems
Using a Parallel CFD Code for Evaluation of Clusters and MPPs
IPDPS '03 Proceedings of the 17th International Symposium on Parallel and Distributed Processing
Evaluation and Co parison Perfor ance of Various MPI plementations on an OSCAR Linux Cluster
ITCC '03 Proceedings of the International Conference on Information Technology: Computers and Communications
Performance Analysis Using Stochastic Petri Nets
IEEE Transactions on Computers
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Cluster systems are widely used in modern high performance computing. With the rapidly increasing of parallel algorithms, it is an open problem to analyze and evaluate whether they take good advantage of the computing and network resources of clusters. We present a novel mathematic model(n-Cube Model for Cluster Computing) that epitomizes the algorithms commonly used on clusters and evaluate this model using Stochastic Petri Nets (SPN). The state space of our model's SPN is also discussed formally. Finally, we take MM5(the Fifth-Generation Model) as a case and the comparative performance analysis shows the immense vitality of the model.