{"title":"Optimized data-reuse in processor arrays","authors":"Sebastian Siegel, R. Merker","doi":"10.1109/ASAP.2004.10024","DOIUrl":null,"url":null,"abstract":"We present a method for co-partitioning affine indexed algorithms resulting in a processor array with an optimized data-reuse. Through this method, a memory hierarchy with an optimized data transfer is derived which allows a significant reduction of the power consumption caused by memory accesses. Apart from former design flows which begin with a space-time transformation, we start with the co-partitioning of the iteration space. This allows an adaption of the resulting processor array towards the constraints of the target architecture at the beginning of the design. We illustrate our method for the full search motion estimation algorithm which bears a high potential of data-reuse.","PeriodicalId":120245,"journal":{"name":"Proceedings. 15th IEEE International Conference on Application-Specific Systems, Architectures and Processors, 2004.","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2004-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings. 15th IEEE International Conference on Application-Specific Systems, Architectures and Processors, 2004.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ASAP.2004.10024","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6

Abstract

We present a method for co-partitioning affine indexed algorithms resulting in a processor array with an optimized data-reuse. Through this method, a memory hierarchy with an optimized data transfer is derived which allows a significant reduction of the power consumption caused by memory accesses. Apart from former design flows which begin with a space-time transformation, we start with the co-partitioning of the iteration space. This allows an adaption of the resulting processor array towards the constraints of the target architecture at the beginning of the design. We illustrate our method for the full search motion estimation algorithm which bears a high potential of data-reuse.
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优化了处理器数组中的数据重用
我们提出了一种共划分仿射索引算法的方法,导致处理器阵列具有优化的数据重用。通过这种方法,导出了具有优化数据传输的内存层次结构,从而大大降低了内存访问引起的功耗。与以往的设计流程从时空变换开始不同,我们从迭代空间的共划分开始。这允许在设计之初根据目标体系结构的约束对生成的处理器阵列进行调整。给出了一种具有较高数据重用潜力的全搜索运动估计算法。
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