A.C. Sodan (Canada)
parallel programming models, parallel programming languages, parallel machines, human factors, personality types
Typically, only technical arguments like performance, cost or scalability are discussed if programming models and languages for High Performance Computing facilities are under consideration. In this paper, we investigate the impact of human factors such as personal preferences, perceptions, and personality types on making technical decisions. We have queried a large HPC community of the Sharcnet project in Ontario/Canada in regards to preferences in the two major programming models: shared memory/multithreading vs. message passing. In a previous paper, we have already shown that the study confirms the general belief that shared-memory programming models and architectures are preferred by novices entering the field of parallel processing. However, individual preferences may differ from the majority view. In this paper, we investigate the correlation between preferences and personality type.
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