CSR: Small: Collaborative Research: EUReCa: Enabling Untethered VR/AR System via Human-centric Graphic Computing and Distributed Data Processing
CSR: Small: Collaborative Research: EUReCa: Enabling Untethered VR/AR System via Human-centric Graphic Computing and Distributed Data Processing
批准号:
1717775
负责人:
Xiang Chen
金额:
$24.98万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2017
资助国家:
美国
项目状态:
已结题
起止时间:
2017-09-01 至 2021-08-31
中文摘要
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英文摘要
Virtual Reality (VR) and Augmented Reality (AR) devices, especially their mobile versions are newly emergent technologies. However, a major challenge that VR/AR technologies faces is the gap between the increasing needs for graphic and data processing and the limited computing capability of the mobile hardware. Two researchers from GMU and Duke form a team to develop an innovative VR/AR system, namely, "EUReCa", which tackles the challenge of human-centric graphic processing and distributed data processing. This research studies VR/AR system design using standard workloads to understand the computation source utilization that leads to development of usage model, and reduces the computation loads via task allocation, thereby enhancing the efficiency and scalability of computation. The research outcomes will benefit both research and industry at large by integrating the innovations of human interaction and advanced data processing technologies. The education plan enhances existing curricula and pedagogy by integrating interdisciplinary modules on computer graphic, embedded systems, and machine learning with newly developed teaching practices, and gives special attention to women and underrepresented minority groups. The project performs three tasks. Task 1 models the computation resource utilization of VR/AR systems by considering the system configuration and dynamics of user operations. Task 2 explores efficient human-centric graphic rendering framework for reducing computation loads of VR/AR systems. Task 3 exploits novel schemes to enhance computation efficiency via balancing the computation loads and data allocations in graphic rendering and deep neural network (DNN) applications. The techniques will be evaluated on mobile devices.
期刊论文(14)
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科研奖励(0)
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DOI:
10.1109/iccad.2017.8203864
发表时间:
2017-11
期刊:
2017 IEEE/ACM International Conference on Computer-Aided Design (ICCAD)
影响因子:
--
作者:
[Zhuwei Qin;Zirui Xu;Qide Dong;Yiran Chen;Xiang Chen]
通讯作者:
Zhuwei Qin;Zirui Xu;Qide Dong;Yiran Chen;Xiang Chen
DOI:
10.1145/3447548.3467309
发表时间:
2021-08
期刊:
Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining
影响因子:
--
作者:
[Fuxun Yu;Weishan Zhang;Zhuwei Qin;Zirui Xu;Di Wang;Chenchen Liu;Zhi Tian;Xiang Chen]
通讯作者:
Fuxun Yu;Weishan Zhang;Zhuwei Qin;Zirui Xu;Di Wang;Chenchen Liu;Zhi Tian;Xiang Chen
DOI:
10.1145/3316781.3324696
发表时间:
2019-06
期刊:
2019 56th ACM/IEEE Design Automation Conference (DAC)
影响因子:
--
作者:
[Zirui Xu;Fuxun Yu;Chenchen Liu;Xiang Chen]
通讯作者:
Zirui Xu;Fuxun Yu;Chenchen Liu;Xiang Chen
DOI:
10.1109/iccad51958.2021.9643501
发表时间:
2021-11
期刊:
2021 IEEE/ACM International Conference On Computer Aided Design (ICCAD)
影响因子:
--
作者:
[Fuxun Yu;Shawn Bray;Di Wang;Longfei Shangguan;Xulong Tang;Chenchen Liu;Xiang Chen]
通讯作者:
Fuxun Yu;Shawn Bray;Di Wang;Longfei Shangguan;Xulong Tang;Chenchen Liu;Xiang Chen
Helios: Heterogeneity-Aware Federated Learning with Dynamically Balanced Collaboration
Helios:具有动态平衡协作的异构感知联邦学习
DOI:
10.1109/dac18074.2021.9586241
发表时间:
2021
期刊:
ACM/IEEE Design Automation Conference (DAC
影响因子:
--
作者:
[Xu, Zirui, Yu, Fuxun, Xiong, Jinjun, Chen, Xiang]
通讯作者:
Chen, Xiang
共 13 条
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BIGDATA: F: Collaborative Research: Acquisition, Collection and Computation of Dynamic Big Sensory Data in Smart Cities
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SaTC: CORE: Medium: Collaborative: Privacy Attacks and Defense Mechanisms in Online Social Networks
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CIF: Small: Task-Cognizant Sparse Sensing for Inference
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EARS: Collaborative Research: Spectrum Sensing for Coexistence of Active and Passive Radio Services
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依托单位:
国内基金
海外基金
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