Abstract
In genomic analysis, the major computation bottleneck is the memory-and compute-intensive DNA short reads alignment due to memory-wall challenge. This work presents the first Resistive RAM (RRAM) based Compute-in-Memory (CIM) macro design for accelerating state-of-the-art BWT based genome sequencing alignment. Our design could support all the core instructions, i.e., XNOR based match, count, and addition, required by alignment algorithm. The proposed CIM macro implemented in integration of HfO2 RRAM and 65nm CMOS demonstrates the best energy efficiency to date with 2.07 TOPS/W and 2. 12Gsuffixes/J at 1. 0V.
Original language | English (US) |
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Title of host publication | ESSCIRC 2023 - IEEE 49th European Solid State Circuits Conference |
Publisher | IEEE Computer Society |
Pages | 117-120 |
Number of pages | 4 |
ISBN (Electronic) | 9798350304206 |
DOIs | |
State | Published - 2023 |
Externally published | Yes |
Event | 49th IEEE European Solid State Circuits Conference, ESSCIRC 2023 - Lisbon, Portugal Duration: Sep 11 2023 → Sep 14 2023 |
Publication series
Name | European Solid-State Circuits Conference |
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Volume | 2023-September |
ISSN (Print) | 1930-8833 |
Conference
Conference | 49th IEEE European Solid State Circuits Conference, ESSCIRC 2023 |
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Country/Territory | Portugal |
City | Lisbon |
Period | 9/11/23 → 9/14/23 |
Bibliographical note
Publisher Copyright:© 2023 IEEE.
Keywords
- Compute-in-Memory
- Genome Sequencing Alignment
- RRAM