{"title":"The Study of Android Parallel Programming Based on the Dual-Core Cortex-A9","authors":"Chien-Chung Wu, Jyun-Jie Huang","doi":"10.1109/IIH-MSP.2013.124","DOIUrl":null,"url":null,"abstract":"This study is based on the Samsung Exynos 4210 dual-core Cortex-A9 and Android 4.2.1. The performances of the APPs are improved by tuning CPUs' resources allocation and adding parallelism using the OpenMP compiler directives. The Cgroup and Cpuset are used in this paper to manage the CPUs' resources allocation. Besides, the Android's Native Development Kit is modified to support the Android Apps with OpenMP library in this paper. The study takes the Canny edge detection of the OpenCV as an example. The result shows that the processing time of the one picture can be improved from 939ms to 671ms with 28.5% enhancement.","PeriodicalId":105427,"journal":{"name":"2013 Ninth International Conference on Intelligent Information Hiding and Multimedia Signal Processing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 Ninth International Conference on Intelligent Information Hiding and Multimedia Signal Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IIH-MSP.2013.124","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
This study is based on the Samsung Exynos 4210 dual-core Cortex-A9 and Android 4.2.1. The performances of the APPs are improved by tuning CPUs' resources allocation and adding parallelism using the OpenMP compiler directives. The Cgroup and Cpuset are used in this paper to manage the CPUs' resources allocation. Besides, the Android's Native Development Kit is modified to support the Android Apps with OpenMP library in this paper. The study takes the Canny edge detection of the OpenCV as an example. The result shows that the processing time of the one picture can be improved from 939ms to 671ms with 28.5% enhancement.
本研究基于三星Exynos 4210双核Cortex-A9和Android 4.2.1。通过调整cpu的资源分配和使用OpenMP编译器指令增加并行性，可以提高应用程序的性能。本文使用Cgroup和Cpuset来管理cpu的资源分配。此外，本文还对Android的Native Development Kit进行了修改，使其支持OpenMP库的Android应用程序。本研究以OpenCV的Canny边缘检测为例。结果表明，单幅图像的处理时间从939ms提高到671ms，提高了28.5%。
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