The design and analysis of parallel algorithms
The design and analysis of parallel algorithms
Programming distributed systems
Programming distributed systems
A randomized parallel sorting algorithm with an experimental study
Journal of Parallel and Distributed Computing
Predicting Application Run Times Using Historical Information
IPPS/SPDP '98 Proceedings of the Workshop on Job Scheduling Strategies for Parallel Processing
Modelling asynchronous message passing in small cluster environments
International Journal of Computers and Applications
Execution time prediction for grid infrastructures based on runtime provenance data
WORKS '13 Proceedings of the 8th Workshop on Workflows in Support of Large-Scale Science
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Nowadays a wide range of highly efficient hardware components are available as possible building blocks for parallel distributed systems, however many questions arise at the software side. There is no common solution for optimal distribution of co-operating tasks, and performance prediction is also an open issue. In this paper the efforts are focused on creating and making use of mathematical models in a precise domain, namely applications making moderate computation effort on a relatively large amount of data. The possibilities to predict and to minimize execution times are investigated in a cluster of workstations environment, where the data transfer system is expected to become the performance bottleneck. The use of the presented generic model is shown on the example of a parallel integer sorting algorithm: formulas are built up to provide the expected execution times and to approximate the optimal cluster size. Finally the predicted and the measured execution times of the sorting algorithm are compared for different problem and cluster sizes.