Compression Accelerator for Hadoop Appliance

Kim, Sang Don; Lee, Seong Mo; Lee, Sang Muk; Jang, Ji Hoon; Son, Jae-Gi; Kim, Young Hwan; Lee, Seung Eun

doi:10.1007/978-3-319-11167-4_41

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Cited by 7 publications

(3 citation statements)

References 6 publications

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“…However, the study of the LZ4 algorithm to address the power and cost issues of Hadoop is still needed. Based on our previous works [20,21], we aim to address the TCO and cost issues of Hadoop by adopting the LZ4 hardware accelerator on Atom-based server.…”

Section: Related Workmentioning

confidence: 99%

Energy Efficient and Low-Cost Server Architecture for Hadoop Storage Appliance

2020

KSII TIIS

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Section: Related Workmentioning

confidence: 99%

Energy Efficient and Low-Cost Server Architecture for Hadoop Storage Appliance

2020

KSII TIIS

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“…al. [7] proposed a memory compression mechanism for Hadoop appliances which is widely used in big data analysis with the goal of improving data storage. They reported a data reduction average 74% and 66 µs of compression time, by compressing trading log datasets using a software implementation of the LZ4 algorithm implemented on the Cortex-A9 processor present in Xilinx Zynq chips (Xilinx ZC-706 board).…”

Section: Related Workmentioning

confidence: 99%

CPCIe: A compression-enabled PCIe core for energy and performance optimization

Zainol

Nunez-Yanez

2016

2016 IEEE Nordic Circuits and Systems Conference (NORCAS)

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“…The bottleneck between the DB server and the storage is caused by frequent updates of the specific data. applications [2][3][4][5], accelerating the performance of systems.…”

Section: Introductionmentioning

confidence: 99%

Accelerating forex trading system through transaction log compression

Jang

Lee

Kim

et al. 2014

2014 International SoC Design Conference (ISOCC)

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In this paper, we propose the hardware architecture for high-speed transaction logging of forex trading system. In forex trading market, the trading volume of currencies is growing larger every year. In order to provide real-time processing of large volume and high availability service, we focused on the two types of the workload, where the bottleneck occurs, and conducted workload analysis. The bottleneck between the application server and the internal hard disk is caused by the overhead from storing the transaction logs, due to the bandwidth limitation of a hard disk. Our key idea is to suppress an overhead of the transaction logging through the compression of the transaction logs. Implementation result demonstrates the feasibility of our proposal for increasing the bandwidth through the log compression.

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Compression Accelerator for Hadoop Appliance

Cited by 7 publications

References 6 publications

Energy Efficient and Low-Cost Server Architecture for Hadoop Storage Appliance

Energy Efficient and Low-Cost Server Architecture for Hadoop Storage Appliance

CPCIe: A compression-enabled PCIe core for energy and performance optimization

Accelerating forex trading system through transaction log compression

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