English

Massively parallel read mapping on GPUs with PEANUT

Data Structures and Algorithms 2014-03-10 v1 Distributed, Parallel, and Cluster Computing Quantitative Methods

Abstract

We present PEANUT (ParallEl AligNment UTility), a highly parallel GPU-based read mapper with several distinguishing features, including a novel q-gram index (called the q-group index) with small memory footprint built on-the-fly over the reads and the possibility to output both the best hits or all hits of a read. Designing the algorithm particularly for the GPU architecture, we were able to reach maximum core occupancy for several key steps. Our benchmarks show that PEANUT outperforms other state-of- the-art mappers in terms of speed and sensitivity. The software is available at http://peanut.readthedocs.org.

Keywords

Cite

@article{arxiv.1403.1706,
  title  = {Massively parallel read mapping on GPUs with PEANUT},
  author = {Johannes Köster and Sven Rahmann},
  journal= {arXiv preprint arXiv:1403.1706},
  year   = {2014}
}
R2 v1 2026-06-22T03:22:11.679Z