GA - based Task Allocation by Throughput Prediction

• Item type: Journal(1)
• 公開日: 1999-12-15
• タイトル: GA - based Task Allocation by Throughput Prediction
• タイトル / 言語: en
• タイトル: GA - based Task Allocation by Throughput Prediction
• 言語: eng
• キーワード / 主題Scheme: Other
• キーワード / 主題: 論文
• 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
• その他タイトル / その他のタイトル: 並列処理ソフトウェア
• 著者所属: Annex Information Inc.
• 著者所属: Department of Information and Computer Sciences Toyo University
• 著者所属: Department of Information and Computer Sciences Toyo University
• 著者所属: Department of Information and Computer Sciences Toyo University
• 著者所属(英): en
• 著者所属(英): Annex Information, Inc
• 著者所属(英): en
• 著者所属(英): Department of Information and Computer Sciences, Toyo University
• 著者所属(英): en
• 著者所属(英): Department of Information and Computer Sciences, Toyo University
• 著者所属(英): en
• 著者所属(英): Department of Information and Computer Sciences, Toyo University
• 著者名: Yoichi, Aoyagi; Minoru, Uehara; Hideki, Mori; Akira, Sato
• 著者名(英): Yoichi, Aoyagi; Minoru, Uehara; Hideki, Mori; Akira, Sato
• 論文抄録 / 内容記述タイプ: Other
• 論文抄録 / 内容記述: Recently multimedia data processing dealing with audio and visual data and various combinations of such data is gaining importance.In such multimedia processing data streaming is utilized by pipelinedparallel processing on successive data flow computations such as data compressions data expansions effect processing and so on.With this background high throughput task scheduling for software oriented pipeline processing is expected. Scheduling issues are classified into allocations of tasks to processors and deciding the appropriateexecution orders of tasks.As there are so many solutions these issues are called an NP hard problem. In this paper a static task allocation method for stream-based computations using a Genetic Algorithm (GA) is proposed.In our proposed method in order to find global solutions efficiently a list-scheduling algorithm and a GA are adopted and both are combinedtogether.Finally we show that our proposed method gives better allocation resultscompared with a conventional CP/MISF method.
• 論文抄録(英) / 内容記述タイプ: Other
• 論文抄録(英) / 内容記述: Recently, multimedia data processing dealing with audio and visual data and various combinations of such data is gaining importance.In such multimedia processing, data streaming is utilized by pipelinedparallel processing on successive data flow computations such as data compressions, data expansions, effect processing and so on.With this background, high throughput task scheduling for software oriented pipeline processing is expected. Scheduling issues are classified into allocations of tasks to processors, and deciding the appropriateexecution orders of tasks.As there are so many solutions, these issues are called an NP hard problem. In this paper, a static task allocation method for stream-based computations using a Genetic Algorithm (GA) is proposed.In our proposed method, in order to find global solutions efficiently,a list-scheduling algorithm and a GA are adopted, and both are combinedtogether.Finally, we show that our proposed method gives better allocation resultscompared with a conventional CP/MISF method.
• 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: AN00116647
• 書誌情報: 情報処理学会論文誌; 巻 40, 号 12, p. 4309-4318, 発行日 1999-12-15
• ISSN / 収録物識別子タイプ: ISSN
• ISSN / 収録物識別子: 1882-7764