S
Shengsheng Huang
Researcher at Intel
Publications - 10
Citations - 1545
Shengsheng Huang is an academic researcher from Intel. The author has contributed to research in topics: Cloud computing & Scalability. The author has an hindex of 6, co-authored 9 publications receiving 1314 citations. Previous affiliations of Shengsheng Huang include National University of Singapore & Zhejiang University.
Papers
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Proceedings ArticleDOI
The HiBench benchmark suite: Characterization of the MapReduce-based data analysis
TL;DR: This paper presents the benchmarking, evaluation and characterization of Hadoop, an open-source implementation of MapReduce, and introduces HiBench, a new benchmark suite for Hadoops, which evaluates and characterize theHadoop framework in terms of speed, throughput, and system resource utilizations.
Proceedings ArticleDOI
SALICON: Saliency in Context
TL;DR: A mouse-contingent multi-resolutional paradigm based on neurophysiological and psychophysical studies of peripheral vision, to simulate the natural viewing behavior of humans is designed, thus enabling large-scale data collection.
Proceedings ArticleDOI
HiTune: dataflow-based performance analysis for big data cloud
TL;DR: HiTune as mentioned in this paper is a performance analyzer for Hadoop based on distributed instrumentations and dataflow-driven performance analysis, which can help users to efficiently conduct performance analysis and tuning, demonstrating the benefits of dataflowbased analysis and the limitations of existing approaches.
Journal ArticleDOI
Interactive Control of Large-Crowd Navigation in Virtual Environments Using Vector Fields
TL;DR: A simple but effective way for authoring a crowd scene with a governing tool that is fast enough to allow on-the-fly modification of vector fields.
Proceedings Article
HiTune: dataflow-based performance analysis for big data cloud
TL;DR: This paper has implemented HiTune, a scalable, lightweight and extensible performance analyzer for Hadoop, demonstrating the benefits of dataflow-based analysis and the limitations of existing approaches.