A Distributed Memory Hierarchy and Data Management for Interactive Scene Navigation and Modification on Tiled Display Walls

被引:4
|
作者
Duy-Quoc Lai [1 ]
Sajadi, Behzad [1 ]
Jiang, Shan [1 ]
Meenakshisundaram, Gopi [1 ]
Majumder, Aditi [1 ]
机构
[1] Univ Calif Irvine, Dept Comp Sci, Irvine, CA 92697 USA
关键词
Management of computing and information systems; project and people management; life cycle; the computing profession miscellaneous ethics; PERFORMANCE; FRAMEWORK;
D O I
10.1109/TVCG.2015.2398439
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
Simultaneous modification and navigation of massive 3D models are difficult because repeated data edits affect the data layout and coherency on a secondary storage, which in turn affect the interactive out-of-core rendering performance. In this paper, we propose a novel approach for distributed data management for simultaneous interactive navigation and modification of massive 3D data using the readily available infrastructure of a tiled display. Tiled multi-displays, projection or LCD panel based, driven by a PC cluster, can be viewed as a cluster of storage-compute-display (SCD) nodes. Given a cluster of SCD node infrastructure, we first propose a distributed memory hierarchy for interactive rendering applications. Second, in order to further reduce the latency in such applications, we propose a new data partitioning approach for distributed storage among the SCD nodes that reduces the variance in the data load across the SCD nodes. Our data distribution method takes in a data set of any size, and reorganizes it into smaller partitions, and stores it across the multiple SCD nodes. These nodes store, manage, and coordinate data with other SCD nodes to simultaneously achieve interactive navigation and modification. Specifically, the data is not duplicated across these distributed secondary storage devices. In addition, coherency in data access, due to screen-space adjacency of adjacent displays in the tile, as well as object space adjacency of the data sets, is well leveraged in the design of the data management technique. Empirical evaluation on two large data sets, with different data density distribution, demonstrates that the proposed data management approach achieves superior performance over alternative state-of-the-art methods.
引用
收藏
页码:714 / 729
页数:16
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