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arXiv · 1704.01513

Using Cognitive Computing for Learning Parallel Programming: An IBM Watson Solution

Adrian Calvo Chozas·Suejb Memeti·Sabri Pllana
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Abstract

While modern parallel computing systems provide high performance resources, utilizing them to the highest extent requires advanced programming expertise. Programming for parallel computing systems is much more difficult than programming for sequential systems. OpenMP is an extension of C++ programming language that enables to express parallelism using compiler directives. While OpenMP alleviates parallel programming by reducing the lines of code that the programmer needs to write, deciding how and when to use these compiler directives is up to the programmer. Novice programmers may make mistakes that may lead to performance degradation or unexpected program behavior. Cognitive computing has shown impressive results in various domains, such as health or marketing. In this paper, we describe the use of IBM Watson cognitive system for education of novice parallel programmers. Using the dialogue service of the IBM Watson we have developed a solution that assists the programmer in avoiding common OpenMP mistakes. To evaluate our approach we have conducted a survey with a number of novice parallel programmers at the Linnaeus University, and obtained encouraging results with respect to usefulness of our approach.

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Adrian Calvo Chozas, Suejb Memeti, Sabri Pllana. 2017-04-05. Using Cognitive Computing for Learning Parallel Programming: An IBM Watson Solution. https://arxiv.org/abs/1704.01513

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