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Shared-data or message passing computing models – A human factor in technical choices
15th International Conference on Parallel and Distributed Computing Systems
  • Angela Sodan, University of Windsor
  • Luiz Fernando Capretz, University of Western Ontario
Document Type
Conference Proceeding
Publication Date
9-1-2002
Notes

It is an ongoing debate in parallel processing whether shared- or distributed-memory computing models are better, whether shared-data or message passing is preferable. Recent research has shed some more light on the debate, showing that many applications can be supported well in either model (though potentially with some special tuning for the corresponding machine) but that for some applications with more extreme behavior the corresponding machine type and computing model are preferable or even the only feasible solution. Otherwise, what does make people choose one or the other? We investigate the human factor and propose the model that the personality type determines to a large extent personal preferences. The paper discusses the relationship between certain personality types and the programming model. To determine these aspects, we applied the psychological Myer-Briggs-Type-Indicator test on a group of students for whom both programming models were mostly new (i.e. who were not pre-occupied). The results give reasonable evidence for the validity of our proposed model and the relevance of the human factor in technical choices, i.e. that choices are not only/always a matter of which model is “better”.

Citation Information
Angela Sodan and Luiz Fernando Capretz. "Shared-data or message passing computing models – A human factor in technical choices" 15th International Conference on Parallel and Distributed Computing Systems (2002) p. 500 - 5006
Available at: http://works.bepress.com/luiz_fernando_capretz/28/