In the last few years cloud computing is growing as a dominant solution for large scale numerical problems. It is based on MapReduce programming model, which provides high scalability and flexibility, but also optimizes costs of computing infrastructure. This paper studies feasibility of MapReduce model for scientific problems consisting of many independent simulations. Experiment based on variability analysis for simple electro­magnetic problem with over 10,000 scenarios proves that platform has nearly linear scalability with over 80% of theoretical maximum performance.


mapreduce; cloud computing; platform performance; hadoop

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Published : 2015-10-28

Krupa, A., & Sawicki, B. (2015). MASSIVE SIMULATIONS USING MAPREDUCE MODEL. Informatyka, Automatyka, Pomiary W Gospodarce I Ochronie Środowiska, 5(4), 45-47.

Artur Krupa
Politechnika Warszawska, Instytut Elektrotechniki Teoretycznej i Systemów Informacyjno-Pomiarowych  Poland
Bartosz Sawicki 
Politechnika Warszawska, Instytut Elektrotechniki Teoretycznej i Systemów Informacyjno-Pomiarowych  Poland