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Analyzing the performance of a cluster-based architecture for immersive visualization systems

机译:分析身临其境的可视化系统的基于群集的体系结构的性能

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Cluster computing has become an essential issue for designing immersive visualization systems. This paradigm employs scalable clusters of commodity computers with much lower costs than would be possible with the high-end, shared memory computers that have been traditionally used for virtual reality purposes. This change in the design of virtual reality systems has caused some development environments oriented toward shared memory computing to require modifications to their internal architectures in order to support cluster computing. This is the case of VR Juggler, which is considered one of the most important virtual reality application development frameworks based on open source code. This paper not only describes in detail the mechanisms based on cluster computing included in the internal design of VR Juggler, but also proposes a new global performance evaluation methodology. The goal of this methodology is to test the graphical performance of immersive visualization systems based on clusters of computers in terms of both network latency and number of nodes in the cluster. In this sense, a performance evaluation of VR Juggler, both in an overall and a modular approach, is presented. The obtained results show that VR Juggler can be considered as an efficient tool to support immersive visualization systems on a cluster of computers.
机译:集群计算已成为设计沉浸式可视化系统的重要问题。与使用传统的虚拟现实技术的高端共享内存计算机相比,这种范例采用了可伸缩的商用计算机集群,其成本要低得多。虚拟现实系统设计的这种变化已导致某些面向共享内存计算的开发环境需要修改其内部体系结构以支持集群计算。 VR Juggler就是这种情况,它被认为是基于开放源代码的最重要的虚拟现实应用程序开发框架之一。本文不仅详细介绍了VR Juggler内部设计中基于集群计算的机制,而且提出了一种新的全局性能评估方法。该方法的目标是根据网络延迟和群集中的节点数来测试基于计算机群集的沉浸式可视化系统的图形性能。从这个意义上讲,本文介绍了VR Juggler的整体和模块化性能评估。获得的结果表明,VR Juggler可以被视为在计算机集群上支持沉浸式可视化系统的有效工具。

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