PIM-Quantifier: A Processing-in-Memory Platform for mRNA Quantification

Fan Zhang, Shaahin Angizi, Naima Ahmed Fahmi, Wei Zhang, Deliang Fan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Scopus citations


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.

Original languageEnglish (US)
Title of host publication2021 58th ACM/IEEE Design Automation Conference, DAC 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages6
ISBN (Electronic)9781665432740
StatePublished - Dec 5 2021
Externally publishedYes
Event58th ACM/IEEE Design Automation Conference, DAC 2021 - San Francisco, United States
Duration: Dec 5 2021Dec 9 2021

Publication series

NameProceedings - Design Automation Conference
ISSN (Print)0738-100X


Conference58th ACM/IEEE Design Automation Conference, DAC 2021
Country/TerritoryUnited States
CitySan Francisco

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Control and Systems Engineering
  • Electrical and Electronic Engineering
  • Modeling and Simulation


  • MRAM
  • Processing-in-memory
  • mRNA-seq


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