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A Benchmarking Framework for Interactive 3D Applications in the Cloud
arXiv - CS - Distributed, Parallel, and Cluster Computing Pub Date : 2020-06-23 , DOI: arxiv-2006.13378
Tianyi Liu, Sen He, Sunzhou Huang, Danny Tsang, Lingjia Tang, Jason Mars, and Wei Wang

With the growing popularity of cloud gaming and cloud virtual reality (VR), interactive 3D applications have become a major type of workloads for the cloud. However, despite their growing importance, there is limited public research on how to design cloud systems to efficiently support these applications, due to the lack of an open and reliable research infrastructure, including benchmarks and performance analysis tools. The challenges of generating human-like inputs under various system/application randomness and dissecting the performance of complex graphics systems make it very difficult to design such an infrastructure. In this paper, we present the design of a novel cloud graphics rendering research infrastructure, Pictor. Pictor employs AI to mimic human interactions with complex 3D applications. It can also provide in-depth performance measurements for the complex software and hardware stack used for cloud 3D graphics rendering. With Pictor, we designed a benchmark suite with six interactive 3D applications. Performance analyses were conducted with these benchmarks to characterize 3D applications in the cloud and reveal new performance bottlenecks. To demonstrate the effectiveness of Pictor, we also implemented two optimizations to address two performance bottlenecks discovered in a state-of-the-art cloud 3D-graphics rendering system, which improved the frame rate by 57.7% on average.

中文翻译:

云中交互式 3D 应用程序的基准测试框架

随着云游戏和云虚拟现实 (VR) 的日益普及,交互式 3D 应用程序已成为云的主要工作负载类型。然而,尽管它们越来越重要,但由于缺乏开放和可靠的研究基础设施,包括基准和性能分析工具,关于如何设计云系统以有效支持这些应用程序的公共研究有限。在各种系统/应用程序随机性下生成类人输入和剖析复杂图形系统的性能的挑战使得设计这样的基础设施变得非常困难。在本文中,我们介绍了一种新颖的云图形渲染研究基础架构 Pictor 的设计。Pictor 使用 AI 来模拟人类与复杂 3D 应用程序的交互。它还可以为用于云 3D 图形渲染的复杂软件和硬件堆栈提供深入的性能测量。借助 Pictor,我们设计了一个包含六个交互式 3D 应用程序的基准测试套件。使用这些基准进行性能分析,以表征云中的 3D 应用程序并揭示新的性能瓶颈。为了证明 Pictor 的有效性,我们还实施了两项优化,以解决在最先进的云 3D 图形渲染系统中发现的两个性能瓶颈,平均提高了 57.7% 的帧率。使用这些基准进行性能分析,以表征云中的 3D 应用程序并揭示新的性能瓶颈。为了证明 Pictor 的有效性,我们还实施了两项优化,以解决在最先进的云 3D 图形渲染系统中发现的两个性能瓶颈,平均提高了 57.7% 的帧率。使用这些基准进行性能分析,以表征云中的 3D 应用程序并揭示新的性能瓶颈。为了证明 Pictor 的有效性,我们还实施了两项优化,以解决在最先进的云 3D 图形渲染系统中发现的两个性能瓶颈,平均提高了 57.7% 的帧率。
更新日期:2020-08-04
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