SCIENCE@home

NP-CAM: Efficient and Scalable DNA Classification using a NoC-Partitioned CAM Architecture

Benjamin F. Morris,Tergel Molom-Ochir,Changchun Zhou,Yiran Chen,Alex K. Jones,Hai Li

Published 2026 in International Symposium on High-Performance Computer Architecture

ABSTRACT

The rapid advancement in genomic sequencing technologies has resulted in an explosion of data, creating substantial computational bottlenecks in DNA analysis workloads. Applications such as DNA classification are particularly impacted due to their reliance on intensive, large-scale pattern matching. Existing hardware accelerator and software solutions are increasingly unable to manage the scale and energy demands of these datasets, highlighting the need for architectures that can perform faster and more efficient pattern matching. To address these challenges, we propose NP-CAM: a data-optimized, CAMbased accelerator designed for parallel and energy-efficient DNA classification. NP-CAM harnesses a network-on-chip to implement a novel optimized indexing and CAM partitioning scheme that reduces the active search space, allowing significant scalability. We demonstrate results for NP-CAM on commodity 10T binary CAM cell designs. Our experimental evaluations show that NPCAM achieves a simultaneous $65 \times$ improvement in sequence throughput and an over $173 \times$ improvement in energy efficiency over state-of-the-art hardware solutions on existing small viral workloads. We go on to demonstrate feasibility for larger bacterial and fungal workloads, enabling scalable DNA classification in the era of large-scale genomic data.

PUBLICATION RECORD

CITATION MAP

EXTRACTION MAP

CLAIMS

  • No claims are published for this paper.

CONCEPTS

  • No concepts are published for this paper.

REFERENCES

Showing 1-67 of 67 references · Page 1 of 1

CITED BY

  • No citing papers are available for this paper.

Showing 0-0 of 0 citing papers · Page 1 of 1