diBELLA: Distributed Long Read to Long Read Alignment

Conference · Tue Jan 01 04:00:00 EST 2019

DOI:https://doi.org/10.1145/3337821.3337919· OSTI ID:1602840

Ellis, Marquita ^[1]; Guidi, Giulia ^[1]; Buluc, Aydin ^[1]; Oliker, Leonid ^[2]; Yelick, Katherine ^[1]; Machinery, Assoc Comp ^[1]

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1. Univ. of California, Berkeley, CA (United States); Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
2. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

© 2019 ACM. We present a parallel algorithm and scalable implementation for genome analysis, specifically the problem of finding overlaps and alignments for data from "third generation" long read sequencers [29]. While long sequences of DNA offer enormous advantages for biological analysis and insight, current long read sequencing instruments have high error rates and therefore require different approaches to analysis than their short read counterparts. Our work focuses on an efficient distributed-memory parallelization of an accurate single-node algorithm for overlapping and aligning long reads. We achieve scalability of this irregular algorithm by addressing the competing issues of increasing parallelism, minimizing communication, constraining the memory footprint, and ensuring good load balance. The resulting application, diBELLA, is the first distributed memory overlapper and aligner specifically designed for long reads and parallel scalability. We describe and present analyses for high level design trade-offs and conduct an extensive empirical analysis that compares performance characteristics across state-of-the-art HPC systems as well as a commercial cloud architectures, highlighting the advantages of state-of-the-art network technologies.

• Research Organization: Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
• Sponsoring Organization: USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR) (SC-21)
• DOE Contract Number: AC02-05CH11231
• OSTI ID: 1602840
• Country of Publication: United States
• Language: English