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Jungpil Yoon

dblp:207/1757 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 2017
—ORCID · none

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

Computer networks · 2

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
2 papers
Energy-efficient computing · 61% GPUs and heterogeneous computing · 39%
Computer graphics and multimedia
2 papers
Computer animation and physical simulation · 100%

Topics — the 2 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
GPUs and heterogeneous computing › embedded GPU
mobile GPU
0.312017
Demo: FROG: Optimizing Power Consumption of Mobile Games Using Perception-Aware Frame Rate Scaling · MobiCom 2017
Energy-efficient computing
power management
0.312017
Demo: FROG: Optimizing Power Consumption of Mobile Games Using Perception-Aware Frame Rate Scaling · MobiCom 2017

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

low-resolution virtual display · 0.6human visual perception modeling · 0.6frame similarity measurement · 0.6frame rate scaling · 0.6
YearPublicationVenuePosition
2017 RAVEN: Perception-aware Optimization of Power Consumption for Mobile Games
abstract
High-end mobile GPUs are now becoming an integral part of mobile devices. However, a mobile GPU constitutes a major portion of power consumption on the devices, and mobile games top as the most popular class of graphics applications. This paper presents the design and implementation of RAVEN, a novel, on-the-fly frame rate scaling system for mobile gaming applications. RAVEN utilizes human visual perception of graphics change to opportunistically achieve power saving without degrading user experiences. The system develops a light-weight frame comparison technique to measure and predict perception-aware frame similarity. It also builds a low resolution virtual display which clones the device screen for performing similarity measurement at a low-power cost. It is able to work on an existing commercial smartphone and support applications from app stores without any modifications. It has been implemented on Nexus 5X, and its performance has been measured with 13 games. The system effectively reduces the overall power consumption of mobile devices while maintaining satisfactory user experiences. The power consumption is reduced by 21.78% on aver-age and up to 34.74%.
Chanyou Hwang, Saumay Pushp, Changyoung Koh, Jungpil Yoon, Yunxin Liu 0001, Seungpyo Choi, Junehwa Song
MobiCom4
2017 Demo: FROG: Optimizing Power Consumption of Mobile Games Using Perception-Aware Frame Rate Scaling
abstract
A mobile GPU constitutes the majority of power consumption on a mobile device and mobile games top as the most popular class of graphics applications. In this demo, we present FROG, a novel frame rate optimization system for mobile gaming applications. FROG makes use of human visual perception to graphics and regulates application's frame rendering process on-the-fly for maximizing power saving without degrading the user experience. The system works on an existing commercial smartphone and support the legacy gaming applications from app stores without requiring any changes from applications
Saumay Pushp, Chanyou Hwang, Changyoung Koh, Jungpil Yoon, Yunxin Liu 0001, Seungpyo Choi, Junehwa Song
MobiCom4