Accelerating Genome Analysis: A Primer on an Ongoing Journey
This is an extended and updated version of a paper published in IEEE Micro, vol. 40, no. 5, pp. 65-75, 1 Sept.-Oct. 2020.
Mohammed Alser†, Zülal Bingöl^, Damla Senol Cali*, Jeremie Kim†*, Saugata Ghose‡*, Can Alkan^, Onur Mutlu†*^
† ETH Zürich
^ Bilkent University
* Carnegie Mellon University
‡ University of Illinois at Urbana–Champaign
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 stateof- 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.
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