Accelerating Genome Analysis: A Primer on an Ongoing Journey

TL;DR

This paper reviews recent advances in accelerating genome read mapping, a crucial step in genome analysis, through algorithmic improvements and hardware-based acceleration, highlighting ongoing challenges in adoption.

Contribution

It provides a comprehensive overview of current algorithmic and hardware acceleration techniques for read mapping in genome analysis.

Findings

Algorithmic methods exploit genome structure and hardware features.

Hardware acceleration uses specialized microarchitectures and execution paradigms.

Challenges remain in adopting hardware-accelerated read mappers.

Abstract

Genome analysis fundamentally starts with a process known as read mapping, where sequenced fragments of an organism's genome are compared against a reference genome. Read mapping is currently a major bottleneck in the entire genome analysis pipeline, because state-of-the-art genome sequencing technologies are able to sequence a genome much faster than the computational techniques employed to analyze the genome. We describe the ongoing journey in significantly improving the performance of read mapping. We explain state-of-the-art algorithmic methods and hardware-based acceleration approaches. Algorithmic approaches exploit the structure of the genome as well as the structure of the underlying hardware. Hardware-based acceleration approaches exploit specialized microarchitectures or various execution paradigms (e.g., processing inside or near memory). We conclude with the challenges of adopting these hardware-accelerated read mappers.