Performance prediction of parallel applications: a systematic literature review

• Published in: The Journal of supercomputing 2021-04, Vol.77 (4), p.4014-4055
• Main Authors: Flores-Contreras, Jesus, Duran-Limon, Hector A., Chavoya, Arturo, Almanza-Ruiz, Sergio H.
• Format: Article
• Language: English
• Subjects: Compilers; Computer Science; Interpreters; Literature reviews; Performance prediction; Processor Architectures; Programming Languages
• ISSN: 0920-8542; 1573-0484
• DOI: 10.1007/s11227-020-03417-5

Different techniques for estimating the execution time of parallel applications have been studied for the last 25 years. These approaches have proposed different methods for predicting the performance behaviour of applications. Most of these methods rely on analysing one or more of the following aspects: system workload, application structure, platform system, and the computing resources that the application needs to perform its operations. These elements are used and applied by different methods such as analytic and non-analytic methods. However, no wide-ranging survey of these approaches exists at the time of writing. This paper presents a systematic review of performance prediction methods for parallel applications, which were published in the open literature during the period 2005–2020. We define a classification framework to categorise the reviewed approaches. In addition, we identify some directions and trends in performance prediction as well as some unsolved issues.