@PT: Unobtrusive parallel programming with Java annotations. (27th July 2018)

• Record Type: Journal Article
• Authors: Mehrabi, Mostafa; Giacaman, Nasser; Sinnen, Oliver
• Is Part Of: Concurrency and computation. Volume 31:Number 1(2019)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2018-07-27
• Subjects: annotation -- GUI concurrency -- lambda expressions -- object‐oriented -- parallel -- parallel tasks; Parallel processing (Electronic computers) -- Periodicals; Parallel computers -- Periodicals; 004.35
• DOI: 10.1002/cpe.4831
• Languages: English
• ISSNs: 1532-0626

Abstract

Summary: Parallel computing techniques have been supported by programming languages in two major ways: either library‐based APIs or extended language constructs. Library‐based features are portable and offer fine‐grained control on parallelization details. However, they rely on individual programmer skills; thus, they may lead to inconsistent implementations and considerable code restructurings. On the contrary, language constructs promote environments that largely conceal the details of parallel programming techniques. However, they normally reduce programmer control over the granularity of parallelization and impose additional development concepts and compilation requirements that may sacrifice ease of use and portability. Therefore, approaches that balance between programmer control on parallelization details, intuitiveness of concepts, and portability can gain priority over other paradigms. In this paper, we discuss @PT (Annotation Parallel Task), a parallel computing framework that proposes Java annotations, standard Java components, as its language constructs. @PT takes an object‐oriented approach on efficient execution and management of asynchronous tasks, with a special focus on GUI‐responsive applications. This paper presents the annotation‐based programming interface of the framework and its fundamental parallelization concepts. Furthermore, it studies the usability and performance of @PT by comparisons with other Java parallelization approaches in a set of standard benchmarks. The observations suggest that @PT maintains a simple programming interface, whereas it performs efficiently in different parallel computing domains.