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Toward High Mobile GPU Performance Through Collaborative Workload Offloading

delete2018-02-01
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OA
AI
C
Chao Wu *
B
Bowen Yang
Wenwu Zhu cover
Wenwu Zhu (Wenwu Zhu)
Y
Yaoxue Zhang
DOI:10.1109/TPDS.2017.2754482delete
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Abstract

Abstract

En 中文
The ever increasing of display resolution on mobile devices raises high demand for GPU rendering details. However, the challenge of poor hardware support but fine-grained rendering details often makes user unsatisfied especially in calling for high frame rate scenarios, e.g., game. To resolve such issue, we propose ButterFly, a novel system which collaboratively utilizes mobile GPUs to process high-quality rendering details for on-the-go mobile users. In particular, ButterFly achieves three technical contributions for the collaborative design: (1) a mobile device can migrate GPU workloads in buffer queue to peers, (2) the collaborative rendering mechanism benefits user high quality details while significant power saving performance, and (3) unnecessary 3D texture rendering can be clipped for further optimization. All the techniques are compatible with the OpenGL ES standards. Furthermore, a 40-person survey perceives that ButterFly can provide excellent user experience of both rendering details and frame rate over Wi-Fi network. In addition, our comprehensive trace-driven experiments on Android prototype reveal the benefits of Butterfly have more superior performance over state-of-the-art systems, which achieves more than 28.3 percent power saving.
Keywords:
Mobile applications
distributed system
code offload
performance optimization
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Journal

IEEE Transactions on Parallel and Distributed Systems cover
IEEE Transactions on Parallel and Distributed Systems
IF:
6
Papers:
5.2K
Citations:
1.1W

Organization

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tsinghua university
Scholars:
11.9W
Papers: 10.0W
Citations: 137
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