2017/04/05 by Adrián Calvo Chozas, Chozas, Adrian Calvo, Suejb Memeti +3
Computer Science · #Cloud Computing and Resource Management #Distributed and Parallel Computing Systems #FOS: Computer and information sciences #Parallel Computing and Optimization Techniques #Programming Languages (cs.PL)
paper · pdf · doi:10.48550/arxiv.1704.01513
openalex publication_date 2017/04/05 · openalex created_date 2022/10/04 · openalex updated_date 2026/07/28
While modern parallel computing systems provide high performance resources,\nutilizing them to the highest extent requires advanced programming expertise.\nProgramming for parallel computing systems is much more difficult than\nprogramming for sequential systems. OpenMP is an extension of C++ programming\nlanguage that enables to express parallelism using compiler directives. While\nOpenMP alleviates parallel programming by reducing the lines of code that the\nprogrammer needs to write, deciding how and when to use these compiler\ndirectives is up to the programmer. Novice programmers may make mistakes that\nmay lead to performance degradation or unexpected program behavior. Cognitive\ncomputing has shown impressive results in various domains, such as health or\nmarketing. In this paper, we describe the use of IBM Watson cognitive system\nfor education of novice parallel programmers. Using the dialogue service of the\nIBM Watson we have developed a solution that assists the programmer in avoiding\ncommon OpenMP mistakes. To evaluate our approach we have conducted a survey\nwith a number of novice parallel programmers at the Linnaeus University, and\nobtained encouraging results with respect to usefulness of our approach.\n