RePAIR: A ReRAM-based Processing-in-Memory Accelerator for Indel Realignment
Ting Wu1,2,a, Chin-Fu Nien2,b, Kuang-Chao Chou3 and Hsiang-Yun Cheng2,c
1Electrical and Computer Engineering, Carnegie Mellon University, USA
atingwu@andrew.cmu.edu
2Research Center for Information Technology Innovation, Academia Sinica, Taiwan
bwatchmannien@citi.sinica.edu.tw
chycheng@citi.sinica.edu.tw
3Gradute Institute of Electronics Engineering, National Taiwan University, Taiwan
r10943002@ntu.edu.tw
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.
