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国家教育部博士点基金(20120002110033)

作品数:2 被引量:192H指数:1
相关作者:周杰张志浩苏衡更多>>
相关机构:清华大学更多>>
发文基金:国家教育部博士点基金国家自然科学基金国家杰出青年科学基金更多>>
相关领域:自动化与计算机技术更多>>

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Schedule refinement for homogeneous multi-core processors in the presence of manufacturing-caused heterogeneity
2015年
Multi-core homogeneous processors have been widely used to deal with computation-intensive embedded applications. However, with the continuous down scaling of CMOS technology, within-die variations in the manufacturing process lead to a significant spread in the operating speeds of cores within homogeneous multi-core processors. Task scheduling approaches, which do not consider such heterogeneity caused by within-die variations,can lead to an overly pessimistic result in terms of performance. To realize an optimal performance according to the actual maximum clock frequencies at which cores can run, we present a heterogeneity-aware schedule refining(HASR) scheme by fully exploiting the heterogeneities of homogeneous multi-core processors in embedded domains.We analyze and show how the actual maximum frequencies of cores are used to guide the scheduling. In the scheme,representative chip operating points are selected and the corresponding optimal schedules are generated as candidate schedules. During the booting of each chip, according to the actual maximum clock frequencies of cores, one of the candidate schedules is bound to the chip to maximize the performance. A set of applications are designed to evaluate the proposed scheme. Experimental results show that the proposed scheme can improve the performance by an average value of 22.2%, compared with the baseline schedule based on the worst case timing analysis. Compared with the conventional task scheduling approach based on the actual maximum clock frequencies, the proposed scheme also improves the performance by up to 12%.
Zhi-xiang CHENZhao-lin LIShan CAOFang WANGJie ZHOU
关键词:HETEROGENEITY
超分辨率图像重建方法综述被引量:192
2013年
由于广泛的实用价值与理论价值,超分辨率图像重建(Super-resolution image reconstruction,SRIR或SR)技术成为计算机视觉与图像处理领域的一个研究热点,引起了研究者的广泛关注.本文将超分辨率图像重建问题按照不同的输入输出情况进行系统分类,将超分辨率问题分为基于重建的超分辨率、视频超分辨率、单帧图像超分辨率三大类.对于其中每一大类问题,分别全面综述了该问题的发展历史、常用算法的分类及当前的最新研究成果等各种相关问题,并对不同算法的特点进行了比较分析.本文随后讨论了各不同类别超分辨率算法的互相融合和图像视频质量评价的方法,最后给出了对这一领域未来发展的思考与展望.
苏衡周杰张志浩
关键词:超分辨率图像重建计算机视觉图像处理
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