RePAIR: A ReRAM-based Processing-in-Memory Accelerator for Indel Realignment

Ting Wu, Chin Fu Nien, Kuang Chao Chou, Hsiang Yun Cheng

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

Genomic analysis has attracted a lot of interest recently since it is the key to realizing precision medicine for diseases such as cancer. Among all the genomic analysis pipeline stages, Indel Realignment is the most time-consuming and induces intensive data movements. Thus, we propose RePAIR, the first ReRAM-based processing-in-memory accelerator targeting the Indel Realignment algorithm. To further increase the computation parallelism, we design several mapping and scheduling optimization schemes. RePAIR achieves 7443× speedup and is 27211× more energy efficient over the GATK3.8 running on a CPU server, significantly outperforming the state-of-the-art.

Original languageEnglish
Title of host publicationProceedings of the 2022 Design, Automation and Test in Europe Conference and Exhibition, DATE 2022
EditorsCristiana Bolchini, Ingrid Verbauwhede, Ioana Vatajelu
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages400-405
Number of pages6
ISBN (Electronic)9783981926361
DOIs
StatePublished - 2022
Externally publishedYes
Event2022 Design, Automation and Test in Europe Conference and Exhibition, DATE 2022 - Virtual, Online, Belgium
Duration: 14 03 202223 03 2022

Publication series

NameProceedings of the 2022 Design, Automation and Test in Europe Conference and Exhibition, DATE 2022

Conference

Conference2022 Design, Automation and Test in Europe Conference and Exhibition, DATE 2022
Country/TerritoryBelgium
CityVirtual, Online
Period14/03/2223/03/22

Bibliographical note

Publisher Copyright:
© 2022 EDAA.

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