Accelerating DNA Long Read Mapping with Emerging Technologies

Student: Roman Kaplan (Israel Institute of Technology)
Supervisor: Ran Ginosar (Israel Institute of Technology)

Abstract: DNA sequencing technologies output only short fragments of a genome, called reads. New single-molecule real-time sequencing technologies can produce long reads, up to tens of thousands base pairs, within minutes. However, these long reads may contain up to 15% errors.

To construct a genome from DNA reads, a computationally expensive bioinformatics task, read mapping, is required. Read mapping finds the best-fitting location for each DNA read on a long reference sequence. The length and error rate of long reads poses a challenge for existing read mapping hardware solutions, designed for short reads with low error rates. This work presents a novel DNA read mapping hardware architecture, RASSA. RASSA is a Resistive Approximate Similarity Search Accelerator that exploits charge distribution and parallel in-memory processing to reflect a mismatch count between DNA sequences. RASSA implementation of long read DNA mapping outperforms state-of-the-art long read mapping solution by 16-77x with comparable accuracy.

ACM-SRC Semi-Finalist: no

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Poster Summary: pdf
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