本文選題：天文交叉證認(rèn)　切入點(diǎn)：HTM　出處：《計(jì)算機(jī)應(yīng)用》2010年08期

【摘要】：交叉證認(rèn)是實(shí)現(xiàn)多波段數(shù)據(jù)融合的關(guān)鍵技術(shù),天文數(shù)據(jù)的海量性使這一問題必須要依靠計(jì)算機(jī)技術(shù)加以解決。按照PCAM并行設(shè)計(jì)模型設(shè)計(jì)了并行交叉證認(rèn)算法。針對(duì)交叉證認(rèn)在數(shù)據(jù)I/O訪問方面存在的性能瓶頸,通過調(diào)整劃分的粒度、過濾空白區(qū)域、優(yōu)化數(shù)據(jù)加載、計(jì)算流程等方法,協(xié)調(diào)了數(shù)據(jù)讀取量與計(jì)算量間的關(guān)系。實(shí)驗(yàn)表明該并行方法對(duì)交叉證認(rèn)計(jì)算的效率提升明顯。另一方面還考慮了對(duì)HTM、HEALPix兩種最常用天文數(shù)據(jù)索引方式的支持,并通過實(shí)驗(yàn)對(duì)比了兩者的性能,為我國(guó)天文數(shù)據(jù)主題庫、虛擬天文臺(tái)等項(xiàng)目提供了技術(shù)參考。
[Abstract]:Cross identification is the key technology to realize multi-band data fusion. Because of the magnanimity of astronomical data, the problem must be solved by computer technology. According to the parallel design model of PCAM, the parallel cross identification algorithm is designed. By adjusting the granularity of partition, filtering blank area, optimizing data loading, calculating flow, etc. The experimental results show that the parallel method can improve the efficiency of cross-identification computation obviously. On the other hand, the support for two most commonly used astronomical data indexing methods, HTMHEALPix, is also considered. The performances of the two are compared through experiments, which provides a technical reference for the subject database of astronomical data and the virtual observatory in China.
【作者單位】： 天津大學(xué)計(jì)算機(jī)科學(xué)與技術(shù)學(xué)院;中國(guó)科學(xué)院國(guó)家天文臺(tái);
【基金】：國(guó)家自然科學(xué)基金資助項(xiàng)目(10978016) 天津自然科學(xué)基金資助項(xiàng)目(08JCZDJC19700) 天津市科技支撐重點(diǎn)項(xiàng)目(09ZCKFGX00400)
【分類號(hào)】：P112

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1 趙青;孫濟(jì)洲;于策;崔辰州;肖健;;面向海量數(shù)據(jù)的并行天文交叉證認(rèn)[J];計(jì)算機(jī)應(yīng)用;2010年08期

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