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Accelerating large scale de novo metagenome assembly using GPUs

Conference · · Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis
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  1. Lawrence Berkeley National Laboratory
  2. University of California
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Metagenomic workflows involve studying uncultured microorganisms directly from the environment. These environmental samples when processed by modern sequencing machines yield large and complex datasets that exceed the capabilities of metagenomic software. The increasing sizes and complexities of datasets make a strong case for exascale-capable metagenome assemblers. However, the underlying algorithmic motifs are not well suited for GPUs. This poses a challenge since the majority of next-generation supercomputers will rely primarily on GPUs for computation. In this paper we present the first of its kind GPU-Accelerated implementation of the local assembly approach that is an integral part of a widely used large-scale metagenome assembler, MetaHipMer. Local assembly uses algorithms that induce random memory accesses and non-deterministic workloads, which make GPU offloading a challenging task. Our GPU implementation outperforms the CPU version by about 7x and boosts the performance of MetaHipMer by 42% when running on 64 Summit nodes.

Research Organization:
Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
Sponsoring Organization:
USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR)
DOE Contract Number:
AC02-05CH11231
OSTI ID:
1896672
Journal Information:
Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis, Conference: SC '21: The International Conference for High Performance Computing, Networking, Storage and Analysis, St. Louis, MO (United States), 14-19 Nov 2021
Country of Publication:
United States
Language:
English

References (9)

Comparison of the two major classes of assembly algorithms: overlap-layout-consensus and de-bruijn-graph journal December 2011
GRASShopPER—An algorithm for de novo assembly based on GPU alignments journal August 2018
A new antibiotic kills pathogens without detectable resistance journal January 2015
IDBA-UD: a de novo assembler for single-cell and metagenomic sequencing data with highly uneven depth journal April 2012
Scaling metagenome sequence assembly with probabilistic de Bruijn graphs journal July 2012
Comparative metatranscriptomics reveals kingdom level changes in the rhizosphere microbiome of plants journal July 2013
MEGAHIT v1.0: A fast and scalable metagenome assembler driven by advanced methodologies and community practices journal June 2016
Terabase-scale metagenome coassembly with MetaHipMer journal July 2020
Overlap graphs and de Bruijn graphs: data structures for de novo genome assembly in the big data era journal December 2019

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