DNA Pattern Matching Acceleration with Analog Resistive CAM

TL;DR

This paper introduces a hardware-software co-design using analog content-addressable memory to accelerate DNA pattern matching, crucial for disease diagnosis, achieving significant energy efficiency and speedup on real human DNA data.

Contribution

It presents a novel analog CAM-based architecture and algorithm for rapid DNA pattern matching, specifically targeting repeat-expansion disease detection.

Findings

Significant speedup over previous methods

Energy-efficient hardware implementation

Validated on real human DNA datasets

Abstract

DNA pattern matching is essential for many widely used bioinformatics applications. Disease diagnosis is one of these applications, since analyzing changes in DNA sequences can increase our understanding of possible genetic diseases. The remarkable growth in the size of DNA datasets has resulted in challenges in discovering DNA patterns efficiently in terms of run time and power consumption. In this paper, we propose an efficient hardware and software codesign that determines the chance of the occurrence of repeat-expansion diseases using DNA pattern matching. The proposed design parallelizes the DNA pattern matching task using associative memory realized with analog content-addressable memory and implements an algorithm that returns the maximum number of consecutive occurrences of a specific pattern within a DNA sequence. We fully implement all the required hardware circuits with PTM 45-nm technology, and we evaluate the proposed architecture on a practical human DNA dataset. The results show that our design is energy-efficient and significantly accelerates the DNA pattern matching task compared to previous approaches described in the literature.