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

被引：0

作者：

Wu, Ting ^{[1
,2
]}

Nien, Chin-Fu ^{[2
]}

Chou, Kuang-Chao ^{[3
]}

Cheng, Hsiang-Yun ^{[2
]}

机构：

[1] Carnegie Mellon Univ, Elect & Comp Engn, Pittsburgh, PA 15213 USA

[2] Acad Sinica, Res Ctr Informat Technol Innovat, Taipei, Taiwan

[3] Natl Taiwan Univ, Grad Inst Elect Engn, Taipei, Taiwan

来源：

PROCEEDINGS OF THE 2022 DESIGN, AUTOMATION & TEST IN EUROPE CONFERENCE & EXHIBITION (DATE 2022) | 2022年

关键词：

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

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 7443x speedup and is 27211x more energy efficient over the GATK3.8 running on a CPU server, significantly outperforming the state-of-the-art.

引用

页码：400 / 405

页数：6

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