Hybrid performance modeling and prediction of large-scale computing systems
Document typeConference report
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Rights accessOpen Access
Performance is a key feature of large-scale computing systems. However, the achieved performance when a certain program is executed is significantly lower than the maximal theoretical performance of the large-scale computing system. The model-based performance evaluation may be used to support the performance-oriented program development for large-scale computing systems. In this paper we present a hybrid approach for performance modeling and prediction of parallel and distributed computing systems, which combines mathematical modeling and discrete-event simulation. We use mathematical modeling to develop parameterized performance models for components of the system. Thereafter, we use discrete-event simulation to describe the structure of system and the interaction among its components. As a result, we obtain a high-level performance model, which combines the evaluation speed of mathematical models with the structure awareness and fidelity of the simulation model. We evaluate empirically our approach with a real-world material science program that comprises more than 15,000 lines of code
CitationPllana, S., Benkner, S., Xhafa, F., Barolli, L. Hybrid performance modeling and prediction of large-scale computing systems. A: International Conference on Complex, Intelligent and Software Intensive Systems. "International Conference on Complex, Intelligent and Software Intensive Systems, 2008: CISIS 2008; 4-7 March 2008, Polytechnic University of Catalonia, Barcelona, Spain". Institute of Electrical and Electronics Engineers (IEEE), 2008, p. 132-138.
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