sponsored byACMIEEE The International Conference for High Performance 
Computing, Networking, Storage and Analysis
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SCHEDULE: NOV 15-20, 2015

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HipMer: An Extreme-Scale De Novo Genome Assembler

SESSION: Applications: Biophysics and Genomics


TIME: 1:30PM - 2:00PM

SESSION CHAIR(S): Amanda Randles

AUTHOR(S):Evangelos Georganas, Aydin Buluc, Jarrod Chapman, Steven Hofmeyr, Chaitanya Aluru, Rob Egan, Leonid Oliker, Daniel Rokhsar, Katherine Yelick



De novo whole genome assembly reconstructs genomic sequence from short, overlapping, and potentially erroneous DNA segments and is one of the most important computations in modern genomics. This work presents the first high-quality end-to-end de novo assembler designed for extreme scale analysis, via efficient parallelization of the Meraculous code. First, we significantly improve scalability of parallel k-mer analysis for complex repetitive genomes that exhibit skewed frequency distributions. Next, we optimize the traversal of the de Bruijn graph of k-mers by employing a novel communication-avoiding parallel algorithm in a variety of use-case scenarios. Finally, we parallelize the Meraculous scaffolding modules by leveraging the one-sided communication capabilities of the Unified Parallel C while effectively mitigating load imbalance. Large-scale results on a Cray XC30 using grand-challenge genomes, demonstrate efficient performance and scalability on thousands of cores. Overall, our pipeline accelerates Meraculous performance by orders of magnitude, creating unprecedented capability for extreme-scale genomic analysis.

Chair/Author Details:

Amanda Randles (Chair) - Duke University|

Evangelos Georganas - University of California, Berkeley

Aydin Buluc - Lawrence Berkeley National Laboratory

Jarrod Chapman - Joint Genome Institute

Steven Hofmeyr - Lawrence Berkeley National Laboratory

Chaitanya Aluru - University of California, Berkeley

Rob Egan - Joint Genome Institute

Leonid Oliker - Lawrence Berkeley National Laboratory

Daniel Rokhsar - University of California, Berkeley

Katherine Yelick - Lawrence Berkeley National Laboratory

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Paper provided by the ACM Digital Library

Paper also available from IEEE Computer Society