TY - GEN
T1 - A benchmarking framework for interactive 3d applications in the cloud
AU - Liu, Tianyi
AU - He, Sen
AU - Huang, Sunzhou
AU - Tsang, Danny
AU - Tang, Lingjia
AU - Mars, Jason
AU - Wang, Wei
N1 - Publisher Copyright:
© 2020 IEEE Computer Society. All rights reserved.
PY - 2020/10
Y1 - 2020/10
N2 - 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.
AB - 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.
KW - Cloud Computing
KW - Cloud Gaming
KW - Cloud Gaming Benchmarks
KW - Cloud Gaming Performance Analysis
KW - Cloud Graphics Systems
UR - http://www.scopus.com/inward/record.url?scp=85097328824&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85097328824&partnerID=8YFLogxK
U2 - 10.1109/MICRO50266.2020.00076
DO - 10.1109/MICRO50266.2020.00076
M3 - Conference contribution
AN - SCOPUS:85097328824
T3 - Proceedings of the Annual International Symposium on Microarchitecture, MICRO
SP - 881
EP - 894
BT - Proceedings - 2020 53rd Annual IEEE/ACM International Symposium on Microarchitecture, MICRO 2020
PB - IEEE Computer Society
T2 - 53rd Annual IEEE/ACM International Symposium on Microarchitecture, MICRO 2020
Y2 - 17 October 2020 through 21 October 2020
ER -