TL;DR
SneakySnake is a novel pre-alignment filter that transforms approximate string matching into a grid routing problem, achieving up to four orders of magnitude better accuracy and significantly accelerating sequence alignment on CPUs, GPUs, and FPGAs.
Contribution
It introduces a new approach that reduces ASM to SNR, enabling highly parallel and accurate pre-alignment filtering across multiple hardware platforms.
Findings
Up to 4 orders of magnitude improvement in filtering accuracy.
Accelerates sequence alignment by up to 979x on CPUs and over 400x on GPUs and FPGAs.
Maintains full aligner capabilities without sacrificing features.
Abstract
Motivation: We introduce SneakySnake, a highly parallel and highly accurate pre-alignment filter that remarkably reduces the need for computationally costly sequence alignment. The key idea of SneakySnake is to reduce the approximate string matching (ASM) problem to the single net routing (SNR) problem in VLSI chip layout. In the SNR problem, we are interested in finding the optimal path that connects two terminals with the least routing cost on a special grid layout that contains obstacles. The SneakySnake algorithm quickly solves the SNR problem and uses the found optimal path to decide whether or not performing sequence alignment is necessary. Reducing the ASM problem into SNR also makes SneakySnake efficient to implement on CPUs, GPUs, and FPGAs. Results: SneakySnake significantly improves the accuracy of pre-alignment filtering by up to four orders of magnitude compared to the…
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