A Hadoop-based Principle Component Analysis on embedded heterogeneous platform

Sheng Yen Chen, Chia I. Wei, Yu Chen Chiu, Bo-Cheng Lai

研究成果: Conference contribution同行評審

1 引文 斯高帕斯(Scopus)

摘要

Hadoop is a widely adopted distributed processing framework which assumes each computing node a CPU-based system with local memory. This design scheme cannot effectively take full advantage of an embedded heterogeneous many-core platform due the mismatch of data collection and management paradigms between the Hadoop environment and embedded heterogeneous systems. This paper proposes a Hadoop-based design of Principle Component Analysis (PCA) to efficiently leverage the distributed embedded heterogeneous many-core systems. By taking the same data layout of conventional Hadoop applications, the proposed design introduces efficient manners to collect and manage the fine-grained data chunks. The experiments on a Tegra K1 has achieved 5.9× performance enhancement.

原文English
主出版物標題2017 International Symposium on VLSI Design, Automation and Test, VLSI-DAT 2017
發行者Institute of Electrical and Electronics Engineers Inc.
ISBN(電子)9781509039692
DOIs
出版狀態Published - 5 6月 2017
事件2017 International Symposium on VLSI Design, Automation and Test, VLSI-DAT 2017 - Hsinchu, Taiwan
持續時間: 24 4月 201727 4月 2017

出版系列

名字2017 International Symposium on VLSI Design, Automation and Test, VLSI-DAT 2017

Conference

Conference2017 International Symposium on VLSI Design, Automation and Test, VLSI-DAT 2017
國家/地區Taiwan
城市Hsinchu
期間24/04/1727/04/17

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