计算机辅助设计与图形学学报
計算機輔助設計與圖形學學報
계산궤보조설계여도형학학보
JOURNAL OF COMPUTER-AIDED DESIGN & COMPUTER GRAPHICS
2015年
1期
1-8
,共8页
单桂华%谢茂金%李逢安%高阳%迟学斌
單桂華%謝茂金%李逢安%高暘%遲學斌
단계화%사무금%리봉안%고양%지학빈
时序数据%高动态范围%粒子绘制%科学可视化%色调映射
時序數據%高動態範圍%粒子繪製%科學可視化%色調映射
시서수거%고동태범위%입자회제%과학가시화%색조영사
time-varying data%high dynamic range%particle rendering%scientific visualization%tone mapping
时序数据的可视化是理解宇宙结构形成与演化的重要手段。围绕大规模天文数值模拟输出的近百 TB 粒子时序数据的可视化,针对数据的高动态范围色调映射问题,提出一种基于统计直方图的算法,实现了时序上色调连贯的可视化;同时,在插值重建演化过程时,考虑到模拟输出的每个关键帧的数据依据 Hilbert 三维填充曲线分布于2048个文件中,在一次可视化中通常有相当部分的文件包含的数据不会进入视锥内,据此提出一种文件尺度上根据前后关键幀预判插值幀可见性的剪裁算法,将前后关键帧可见数据文件的序号集合作为插值幁可见数据文件的序号集合;对裁剪结果进行实时插值和投影,通过裁剪算法大幅降低计算量、存储和I/O,并通过Hilbert哈希元胞快速完成裁剪过程;最后给出了算法的性能和效果分析。可视化结果表明文中算法可以直观、有效地表达大规模数据所包含的宇宙结构形成细节与演化信息。
時序數據的可視化是理解宇宙結構形成與縯化的重要手段。圍繞大規模天文數值模擬輸齣的近百 TB 粒子時序數據的可視化,針對數據的高動態範圍色調映射問題,提齣一種基于統計直方圖的算法,實現瞭時序上色調連貫的可視化;同時,在插值重建縯化過程時,攷慮到模擬輸齣的每箇關鍵幀的數據依據 Hilbert 三維填充麯線分佈于2048箇文件中,在一次可視化中通常有相噹部分的文件包含的數據不會進入視錐內,據此提齣一種文件呎度上根據前後關鍵幀預判插值幀可見性的剪裁算法,將前後關鍵幀可見數據文件的序號集閤作為插值幁可見數據文件的序號集閤;對裁剪結果進行實時插值和投影,通過裁剪算法大幅降低計算量、存儲和I/O,併通過Hilbert哈希元胞快速完成裁剪過程;最後給齣瞭算法的性能和效果分析。可視化結果錶明文中算法可以直觀、有效地錶達大規模數據所包含的宇宙結構形成細節與縯化信息。
시서수거적가시화시리해우주결구형성여연화적중요수단。위요대규모천문수치모의수출적근백 TB 입자시서수거적가시화,침대수거적고동태범위색조영사문제,제출일충기우통계직방도적산법,실현료시서상색조련관적가시화;동시,재삽치중건연화과정시,고필도모의수출적매개관건정적수거의거 Hilbert 삼유전충곡선분포우2048개문건중,재일차가시화중통상유상당부분적문건포함적수거불회진입시추내,거차제출일충문건척도상근거전후관건정예판삽치정가견성적전재산법,장전후관건정가견수거문건적서호집합작위삽치수가견수거문건적서호집합;대재전결과진행실시삽치화투영,통과재전산법대폭강저계산량、존저화I/O,병통과Hilbert합희원포쾌속완성재전과정;최후급출료산법적성능화효과분석。가시화결과표명문중산법가이직관、유효지표체대규모수거소포함적우주결구형성세절여연화신식。
Time-varying data visualization is a fundamental way of understanding the formation and evolu-tion process of the cosmology structures. In our terascale time-varying cosmology data visualization, we present a statistic based tone mapping algorithm for the data with extreme high dynamic range both in spatial and time dimensions, with which we gained novel tone-coherent visualization results. At the mean time, when reconstructing the evolution process, as the data in one time step are distributed on 2048 files in Hil-bert space filling curve way, we found that quite a part of the data files are invisible in most visualization, thus we proposed a visibility culling algorithm for the interpolated data based on the nearest key frame pair. Our algorithm puts the union set of visible file IDs as the culling result, through which we dramatically re-duce the computation, memory consumption and I/O operations. The culling process is efficiently done by using the Hilbert hash cell. Last, we analyze the performance and image quality .Our visualization results show that algorithms proposed here are great help for efficiently expressing forming detail of the cosmology structure, and also great help for gaining insight into the evolution of the Universe.