Executing Data Integration Effectively and Efficiently Near the Memory

Chenfeng Zhao; Xuan Zhang; Roger D. Chamberlain

doi:10.1109/MDAT.2021.3069957

Executing Data Integration Effectively and Efficiently Near the Memory

Chenfeng Zhao
, Xuan Zhang
, Roger D. Chamberlain

Department of Computer Science & Engineering

Research output: Contribution to journal › Article › peer-review

3 Scopus citations

Abstract

The article investigates the use of near-memory processing to perform data integration tasks. Based on the observation that most data integration workloads have regular memory access patterns and varying computation intensities, the authors develop a near-memory processing architecture to accelerate the execution of data transformation workloads and reduce their energy needs.

Original language	English
Pages (from-to)	65-73
Number of pages	9
Journal	IEEE Design and Test
Volume	39
Issue number	2
DOIs	https://doi.org/10.1109/MDAT.2021.3069957
State	Published - Apr 1 2022

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title = "Executing Data Integration Effectively and Efficiently Near the Memory",

abstract = "The article investigates the use of near-memory processing to perform data integration tasks. Based on the observation that most data integration workloads have regular memory access patterns and varying computation intensities, the authors develop a near-memory processing architecture to accelerate the execution of data transformation workloads and reduce their energy needs.",

author = "Chenfeng Zhao and Xuan Zhang and Chamberlain, \{Roger D.\}",

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AB - The article investigates the use of near-memory processing to perform data integration tasks. Based on the observation that most data integration workloads have regular memory access patterns and varying computation intensities, the authors develop a near-memory processing architecture to accelerate the execution of data transformation workloads and reduce their energy needs.

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Executing Data Integration Effectively and Efficiently Near the Memory

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