Efficient Phase-Functioned Real-time Character Control in Mobile Games: A TVM Enabled Approach
Authors: 
Haidong Lan, Wenxi Zhu, Du Wu, Qian Qiu, Honglin Zhu, Jingjing Zhao, Xinghui Fu, Liu Wei, Jintao Meng, Minwen DengAuthors Info & Claims
Haidong Lan, Wenxi Zhu, Du Wu, Qian Qiu, Honglin Zhu, Jingjing Zhao, Xinghui Fu, Liu Wei, Jintao Meng, Minwen DengAuthors Info & ClaimsArticle No.: 15, Pages 1 - 9
Abstract
In this paper, we propose a highly efficient computing method for game character control with phase-functioned neural networks (PFNN). The primary challenge to accelerate PFNN on mobile platforms is that PFNN dynamically produces weight matrices with an argument, phase, which is individual to each game character. Therefore existing libraries that generally assume frozen weight matrices are inefficient to accelerate PFNN. The situation becomes even worse when multiple characters are present. To address the challenges, we reformulate the equations and leverage the deep learning compiler stack TVM to build a cross-platform, high-performance implementation. Evaluations reveal that our solutions deliver close-to-peak performance on various platforms, from high-performance servers to energy-efficient mobile platforms. This work is publicly available at https://github.com/turbo0628/pfnn_tvm.
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- Efficient Phase-Functioned Real-time Character Control in Mobile Games: A TVM Enabled Approach
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August 2022
976 pages
ISBN:9781450397339
DOI:10.1145/3545008
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Association for Computing Machinery
New York, NY, United States
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Published: 13 January 2023
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- Research-article
- Research
- Refereed limited
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- General Program of Key Technology from Shenzhen
- Shenzhen Basic Research Fund
- National Science Foundation of China
- National Key Research and Development Program of China
- Strategic Priority CAS Project
- the Key Research and Development Project of Guangdong Province
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ICPP '22
ICPP '22: 51st International Conference on Parallel Processing
August 29 - September 1, 2022
Bordeaux, France
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Overall Acceptance Rate 91 of 313 submissions, 29%
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