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Jerry W. Hu

dblp:276/3192 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2020
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Graphics, computer vision, multimedia, augmented reality and games · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer architecture, parallel and distributed computing, and storage systems
1 paper
Cloud and datacenter computing · 87% GPUs and heterogeneous computing · 13%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Cloud and datacenter computing › cloud applications
cloud rendering
0.412020
DroidCloud: Scalable High Density AndroidTM Cloud Rendering · ACM Multimedia 2020
Cloud and datacenter computing
cluster resource management and scheduling
0.412020
DroidCloud: Scalable High Density AndroidTM Cloud Rendering · ACM Multimedia 2020
GPUs and heterogeneous computing
GPU computing
0.112020
DroidCloud: Scalable High Density AndroidTM Cloud Rendering · ACM Multimedia 2020

Methods — techniques the papers use, named apart from their topics

virtualization · 0.4vHAL · 0.4
YearPublicationVenuePosition
2020 DroidCloud: Scalable High Density AndroidTM Cloud Rendering
abstract
Cloud rendering is an emerging technology in which rendering-heavy applications run on the cloud server and then stream the rendered contents to the end-user device. High density and high scalability of the cloud rendering services are crucial to support millions of users concurrently and cost-effectively. However, it is still challenging to run Android OS in cloud smoothly with high density and high scalability without compromising user experience. This paper presents DroidCloud, the first open-source Android\footnoteAndroid is a trademark of Google LLC. cloud rendering solution focusing on the scalable design and density aspect optimization to the best of our knowledge. To cloudify Android OS, DroidCloud utilizes thevHAL technology in order to support remote devices and keep transparent to Android applications. And aFlexible rendering scheduling policy is introduced to break the boundary of GPU physical locations. Thus, both remote GPUs and local GPUs can accommodate render tasks by forwarding rendering tasks and making it possible to support multiple Android OSes with GPU acceleration. Besides, to further improve the density, DroidCloud optimizes the resource cost both in a single instance and across instances. We show that DroidCloud can run hundreds of Android OSes on a single Intel Xeon server with GPU acceleration simultaneously, increasing the density at the scale of one order of magnitude compared to current cloud gaming systems. Further experimental results demonstrate that DroidCloud can transparently run Android applications at native speed with lower CPU, memory, and storage utilization.
Linsheng Li, Cathy Bao, Randy Xu, Mohammad R. Haghighat, Jerry W. Hu, Shoumeng Yan, Zhengwei Qi
ACM Multimedia8