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拜读了一点点Simon Heinzle和他的团队的文章 哎. 可惜小弟才思学浅啊! 无法理解~
忘GZ达人能帮帮忙哈..诠释下真谛~
目前他们团队的研究是:
Hardware Architectures for Point-Based Graphics----硬件架构点为基础的图形
Dynamic Sampling and Rendering of Algebraic Point Set Surfaces ----动态采样和渲染代数曲面的点集
等等...~
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我的研究兴趣主要集中于图形硬件架构,重点放在渲染和加工点集。 Furthermore, I
am interested also in GPGPU applications and analysis, as well as further
improving hardware for floating point arithmetics.此外,我也有兴趣在GPGPU应
用和分析,以及进一步改善硬件的浮点算法。
hardware architectures for point based graphics硬件架构为基础的图形点
In recent years, point primitives have received a growing attention in
graphics.近年来,指向原始收到了越来越多的注意图形。 On one hand, the
dramatic increase of polygonal complexity has led to an overhead in
processing huge meshes.一方面,急剧增加多边形的复杂性,导致在处理开销巨大的
网格。 On the other hand, modern 3D digital photography and scanning
systems generate huge volumes of point samples and create the need for
advanced digital processing of points.另一方面,现代的三维数字摄影和扫描系
统产生大量的样本点,并建立需要先进的数字处理点。 As a sample of geometry
and appearance, points do not store any connectivity.作为一个样本,几何形状
和外观,点不存储任何连接。 Therefore, finding neighboring points is a
fundamental operation in point processing and is usually performed using
spatial data structures.因此,寻找邻近点是一个基本操作点处理和通常是利用空
间数据结构。 While high-performance software implementations exist, multi-
core CPU systems do not scale very well because of their inflexible and
general caching scheme.虽然高性能的软件实现存在,多核CPU系统不表非常好,因
为他们灵活和一般缓存计划。 In comparison, GPGPU implementations are
inefficient considering the size of graphic chips, mainly due to
incompatibilities between the execution patterns and the massively-
multithreaded SIMD model.相比之下, GPGPU的实施是低效的考虑大小的图形芯片,
最后我想说!很气愤!!本来编辑了很久的稿子被GZ这个烂规矩弄没了.!!!!严重气愤!!!怪不得很多这里的GG都北飘了.!哎.. |
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