Accelerating DNA Read Mapping with Digital Processing-in-Memory

TL;DR

This paper presents DART-PIM, a comprehensive processing-in-memory framework that significantly accelerates the entire DNA read mapping process, reducing execution time and energy consumption compared to existing GPU and PIM solutions.

Contribution

DART-PIM introduces a holistic digital PIM approach for end-to-end DNA read mapping, integrating indexing, filtering, and alignment for improved performance.

Findings

5.7x throughput improvement over GPU

92x energy efficiency gain over GPU

257x throughput enhancement over PIM

Abstract

Genome analysis has revolutionized fields such as personalized medicine and forensics. Modern sequencing machines generate vast amounts of fragmented strings of genome data called reads. The alignment of these reads into a complete DNA sequence of an organism (the read mapping process) requires extensive data transfer between processing units and memory, leading to execution bottlenecks. Prior studies have primarily focused on accelerating specific stages of the read-mapping task. Conversely, this paper introduces a holistic framework called DART-PIM that accelerates the entire read-mapping process. DART-PIM facilitates digital processing-in-memory (PIM) for an end-to-end acceleration of the entire read-mapping process, from indexing using a unique data organization schema to filtering and read alignment with an optimized Wagner Fischer algorithm. A comprehensive performance evaluation with real genomic data shows that DART-PIM achieves a 5.7x and 257x improvement in throughput and a 92x and 27x energy efficiency enhancement compared to state-of-the-art GPU and PIM implementations, respectively.