A Task-driven Parallel Code Generation Scheme for Coarse Grain Parallelization on Android Platform

• Item type: Trans(1)
• 公開日: 2017-05-25
• タイトル: A Task-driven Parallel Code Generation Scheme for Coarse Grain Parallelization on Android Platform
• タイトル / 言語: en
• タイトル: A Task-driven Parallel Code Generation Scheme for Coarse Grain Parallelization on Android Platform
• 言語: eng
• キーワード / 主題Scheme: Other
• キーワード / 主題: [並列計算] Android, Java Fork/Join, task-driven, coarse-grain parallelization, multicore, compiler
• 資源タイプ / 資源タイプ識別子: http://purl.org/coar/resource_type/c_6501
• 資源タイプ: journal article
• 著者所属: Meiji University, School of Interdisciplinary Mathematical Sciences／Waseda University, GCS Research Organization
• 著者所属: SoftBank Corp.
• 著者所属: Meiji University, School of Interdisciplinary Mathematical Sciences
• 著者所属(英): en
• 著者所属(英): Meiji University, School of Interdisciplinary Mathematical Sciences / Waseda University, GCS Research Organization
• 著者所属(英): en
• 著者所属(英): SoftBank Corp.
• 著者所属(英): en
• 著者所属(英): Meiji University, School of Interdisciplinary Mathematical Sciences
• 著者名: Akimasa, Yoshida; Akira, Kamiyama; Hiroki, Oka
• 著者名(英): Akimasa, Yoshida; Akira, Kamiyama; Hiroki, Oka
• 論文抄録 / 内容記述タイプ: Other
• 論文抄録 / 内容記述: Thanks to high performance and low power consumption on Android mobile devices such as smartphones and tablet computers, the use of Android platform has been increasing significantly. Android platforms almost consist of ARM-based multicores and most of the applications have been developed in Java language. Recent Android OS introduces the Java runtime environment called ART which enables use of Fork/Join framework. The Fork/Join framework provides the scheduling mechanism with work-stealing and it is mainly used for programs to implement the divide-and-conquer algorithm or the recursive algorithm. However, in the case of ordinary programs, it is difficult to implement a coarse-grain parallel code based on Fork/Join framework considering data-dependency. To cope with such a problem, this paper proposes a coarse-grain parallel code generation scheme using a developed compiler which converts a Java source program with directives into a task-driven parallel code based on Fork/Join framework. In the performance evaluation using four programs from Java Grande Forum Benchmark Suite, the execution on Samsung Galaxy S6 with heterogeneous eight cores could achieve 2.77-5.12 times speedup versus sequential processing and the execution on NVIDIA Shield Tablet with four cores could also achieve 2.34-3.94 times speedup. Consequently, effectiveness of the proposed scheme was confirmed.; ------------------------------; This is a preprint of an article intended for publication Journal of; Information Processing(JIP). This preprint should not be cited. This; article should be cited as: Journal of Information Processing Vol.25(2017) (online); ------------------------------
• 論文抄録(英) / 内容記述タイプ: Other
• 論文抄録(英) / 内容記述: Thanks to high performance and low power consumption on Android mobile devices such as smartphones and tablet computers, the use of Android platform has been increasing significantly. Android platforms almost consist of ARM-based multicores and most of the applications have been developed in Java language. Recent Android OS introduces the Java runtime environment called ART which enables use of Fork/Join framework. The Fork/Join framework provides the scheduling mechanism with work-stealing and it is mainly used for programs to implement the divide-and-conquer algorithm or the recursive algorithm. However, in the case of ordinary programs, it is difficult to implement a coarse-grain parallel code based on Fork/Join framework considering data-dependency. To cope with such a problem, this paper proposes a coarse-grain parallel code generation scheme using a developed compiler which converts a Java source program with directives into a task-driven parallel code based on Fork/Join framework. In the performance evaluation using four programs from Java Grande Forum Benchmark Suite, the execution on Samsung Galaxy S6 with heterogeneous eight cores could achieve 2.77-5.12 times speedup versus sequential processing and the execution on NVIDIA Shield Tablet with four cores could also achieve 2.34-3.94 times speedup. Consequently, effectiveness of the proposed scheme was confirmed.; ------------------------------; This is a preprint of an article intended for publication Journal of; Information Processing(JIP). This preprint should not be cited. This; article should be cited as: Journal of Information Processing Vol.25(2017) (online); ------------------------------
• 書誌レコードID / 収録物識別子タイプ: NCID
• 書誌レコードID / 収録物識別子: AA11833852
• 書誌情報: 情報処理学会論文誌コンピューティングシステム（ACS）; 巻 10, 号 1, 発行日 2017-05-25
• ISSN / 収録物識別子タイプ: ISSN
• ISSN / 収録物識別子: 1882-7829
• 出版者 / 言語: ja
• 出版者: 情報処理学会