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HOW CHOICES FOR PARALLEL PROGRAMMING MODELS ARE MADE-INFLUENCE OF PERSONALITY TYPE

机译:个性化类型对并行编程模型的选择有何影响

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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.
机译:通常,如果正在考虑针对高性能计算工具的编程模型和语言,则仅讨论诸如性能,成本或可伸缩性之类的技术论点。在本文中,我们研究了人为因素(例如个人偏好,观念和人格类型)对技术决策的影响。关于两种主要编程模型中的首选项,我们已经查询了安大略省/加拿大Sharcnet项目的大型HPC社区:共享内存/多线程与消息传递。在先前的论文中,我们已经表明,该研究证实了普遍的信念,即新手进入并行处理领域时,首选共享内存编程模型和体系结构。但是,个人偏好可能与多数观点有所不同。在本文中,我们研究了偏好与人格类型之间的相关性。

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