DocumentCode :
1797130
Title :
GPU consolidation for cloud games: Are we there yet?
Author :
Hua-Jun Hong ; Tao-Ya Fan-Chiang ; Che-Run Lee ; Kuan-Ta Chen ; Chun-Ying Huang ; Cheng-Hsin Hsu
Author_Institution :
Dept. of Comput. Sci., Nat. Tsing Hua Univ., Hsinchu, Taiwan
fYear :
2014
fDate :
4-5 Dec. 2014
Firstpage :
1
Lastpage :
6
Abstract :
Since the operating expense is crucial to the increasingly popular cloud gaming services, server consolidation is one of the key technologies for the success of these services. In this paper, we conduct extensive experiments using real GPUs and a complete cloud gaming platform to answer the following question: Are modern GPUs ready for cloud gaming? Our experiment results show that modern GPUs have low consolidation overhead, and are powerful enough to concurrently support multiple GPU-intensive cloud games. For example, when using our cloud gaming platform, the recent NVidia K2 GPU outperforms NVidia Quadro 6000 by up to 3.46 times in FPS (frame per second). Moreover, our experiments lead to two new findings that are counter to common beliefs. First, with the latest GPU virtualization technique, shared GPUs may run faster than dedicated GPUs. Second, more context switches not necessarily lead to lower FPS. Last, our experiments shed some light on further enhancements of cloud gaming platforms. For example, offloading the software video codec to the GPUs will result in better gaming experience, which is one of our future tasks.
Keywords :
cloud computing; computer games; graphics processing units; virtualisation; GPU consolidation; GPU virtualization technique; NVidia K2 GPU; cloud gaming service; Benchmark testing; Context; Games; Graphics processing units; Packet loss; Servers; Virtualization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Network and Systems Support for Games (NetGames), 2014 13th Annual Workshop on
Conference_Location :
Nagoya
Type :
conf
DOI :
10.1109/NetGames.2014.7008969
Filename :
7008969
Link To Document :
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