TY - GEN
T1 - PIM-Quantifier
T2 - 58th ACM/IEEE Design Automation Conference, DAC 2021
AU - Zhang, Fan
AU - Angizi, Shaahin
AU - Fahmi, Naima Ahmed
AU - Zhang, Wei
AU - Fan, Deliang
N1 - Funding Information:
This work is supported in part by the National Science Foundation under Grant No.2005209, No.2003749
Publisher Copyright:
© 2021 IEEE.
PY - 2021/12/5
Y1 - 2021/12/5
N2 - Processing-in-memory (PIM) architecture has been considered as a promising solution for the 'memory-wall' issue in many data-intensive applications, especially in bioinformatics. Recent works of developing PIM for genome alignment and assembling have achieved tremendous improvement, while another important genome analysis-mRNA quantification has not been explored. Efficient and accurate mRNA quantification is a crucial step for molecular signature identification, disease outcome prediction and drug development. In this paper, for the first time, we propose a SOT-MRAM based PIM platform, named PIM-Quantifier, for efficient mRNA quantification. A PIM-friendly alignment-free quantification algorithm is first proposed. Then, we present the optimized PIM architecture/circuit designs and mapping method to efficiently accelerate mRNA quantification. Extensive experiments show that PIM-Quantifier significantly improves mRNA quantification performance than CPU and recent other PIM platforms in efficiency defined as throughput/power.
AB - Processing-in-memory (PIM) architecture has been considered as a promising solution for the 'memory-wall' issue in many data-intensive applications, especially in bioinformatics. Recent works of developing PIM for genome alignment and assembling have achieved tremendous improvement, while another important genome analysis-mRNA quantification has not been explored. Efficient and accurate mRNA quantification is a crucial step for molecular signature identification, disease outcome prediction and drug development. In this paper, for the first time, we propose a SOT-MRAM based PIM platform, named PIM-Quantifier, for efficient mRNA quantification. A PIM-friendly alignment-free quantification algorithm is first proposed. Then, we present the optimized PIM architecture/circuit designs and mapping method to efficiently accelerate mRNA quantification. Extensive experiments show that PIM-Quantifier significantly improves mRNA quantification performance than CPU and recent other PIM platforms in efficiency defined as throughput/power.
KW - MRAM
KW - mRNA-seq
KW - Processing-in-memory
UR - http://www.scopus.com/inward/record.url?scp=85119406659&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85119406659&partnerID=8YFLogxK
U2 - 10.1109/DAC18074.2021.9586144
DO - 10.1109/DAC18074.2021.9586144
M3 - Conference contribution
AN - SCOPUS:85119406659
T3 - Proceedings - Design Automation Conference
SP - 43
EP - 48
BT - 2021 58th ACM/IEEE Design Automation Conference, DAC 2021
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 5 December 2021 through 9 December 2021
ER -