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提高智能设备应用系统性能的技术研究与设计
引用本文:何伟文.提高智能设备应用系统性能的技术研究与设计[J].计算机系统应用,2016,25(8):79-85.
作者姓名:何伟文
作者单位:广东工贸职业技术学院, 广州 510510
摘    要:随着智能设备在各个领域的广泛应用,他们的应用系统在功耗、效率、实时性等方面的问题日益突出,这些问题已经成为智能设备可以持续发展的主要障碍. 如何能够提高智能设备应用系统的性能,已成为这一领域的一个重要课题. 从应用软件的核心算法、设计架构等方面研究了能够有效提高智能设备应用系统性能的技术. 首先,基于JNI、NDK等技术,对应用软件的核心算法、架构进行跨平台的移植;然后使用本地代码(C或C++语言)对原来的算法进行改进;最后,利用智能设备多核的运算处理能力,适当地增加任务数量,改善负载均衡. 实验结果表明:如果把这些技术适当地集成到原来的应用系统里面,就能够大幅提高智能设备的整体性能.

关 键 词:跨平台移植  并行计算  负载均衡  本地代码
收稿时间:1/4/2016 12:00:00 AM
修稿时间:2016/2/25 0:00:00

Research and Design on Technology to Improve Intelligent Device Application System Performance
HE Wei-Wen.Research and Design on Technology to Improve Intelligent Device Application System Performance[J].Computer Systems& Applications,2016,25(8):79-85.
Authors:HE Wei-Wen
Affiliation:Guangdong Polytechnic of Industry & Commerce, Guangzhou 510510, China
Abstract:With the wide application of intelligent devices in all the fields, their application system has the increasingly prominent issues in the aspects such as power consumption, efficiency and instantaneity, and such issues have become the main obstacle for the continuous development of the intelligent devices. How to improve the intelligent device application system performance has become an important topic in this field. In this paper, the technology is able to effectively improve the intelligent device application system performance in the way of core algorithm and design framework of the application software. First, it conducts the cross-platform transplant on the core algorithm and framework of the application software based on the technologies such as JNI and NDK; then, it improves the original algorithm with the native code (C or C++ language); finally, it utilizes the multi-core calculation and processing ability of the intelligent devices to appropriately increase the task quantity and improve the load balancing. The experimental result indicates that: if such technologies are appropriately integrated into the original application system, the overall performance of the intelligent devices can be improved substantially.
Keywords:cross-platform transplant  parallel computing  load balancing  native code
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