A Benchmarking Framework for Interactive 3D Applications in the Cloud
| Autor: | Danny H. K. Tsang, Sen He, Sunzhou Huang, Wei Wang, Lingjia Tang, Jason Mars, Tianyi Liu |
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| Rok vydání: | 2020 |
| Předmět: |
010302 applied physics
FOS: Computer and information sciences Computer science business.industry Cloud gaming Distributed computing Cloud computing 02 engineering and technology Benchmarking Energy consumption Virtual reality 01 natural sciences Graphics (cs.GR) 020202 computer hardware & architecture Rendering (computer graphics) Computer Science - Graphics Software Computer Science - Distributed Parallel and Cluster Computing 0103 physical sciences 0202 electrical engineering electronic engineering information engineering Distributed Parallel and Cluster Computing (cs.DC) Graphics business System software |
| Zdroj: | MICRO |
| DOI: | 10.48550/arxiv.2006.13378 |
| Popis: | With the growing popularity of cloud gaming and cloud virtual reality (VR), interactive 3D applications have become a major class 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 nondeterminism 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 research infrastructure, Pictor, for cloud 3D applications and systems. Pictor employs AI to mimic human interactions with complex 3D applications. It can also track the processing of user inputs to 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, which show that cloud system designs, including both system software and hardware designs, are crucial to the performance of cloud 3D applications. The analyses also show that energy consumption can be reduced by at least 37% when two 3D applications share a could server. 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. These two optimizations improved the frame rate by 57.7% on average. |
| Databáze: | OpenAIRE |
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