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Syst Biol. 2019 Apr 23. pii: syz020. doi: 10.1093/sysbio/syz020. [Epub ahead of print]

BEAGLE 3: Improved Performance, Scaling, and Usability for a High-Performance Computing Library for Statistical Phylogenetics.

Author information

1
Center for Bioinformatics and Computational Biology, University of Maryland, College Park, MD, USA.
2
Department of Microbiology and Immunology, Rega Institute, KU Leuven - University of Leuven, Leuven, Belgium.
3
The ithree institute, University of Technology Sydney, Ultimo, NSW, Australia.
4
Department of Ecology and Evolutionary Biology, University of Connecticut, Unit 3043, Storrs, CT, USA.
5
Florida Museum of Natural History, University of Florida, Gainesville, FL, USA.
6
Department of Integrative Biology, University of California, Berkeley, CA USA.
7
Institute of Evolutionary Biology, University of Edinburgh, King's Buildings, EH9 3FL, UK.
8
Fogarty International Center, National Institutes of Health, Bethesda, MD, USA.
9
Department of Biomathematics, University of California, Los Angeles, CA, USA.
10
Department of Biostatistics, University of California, Los Angeles, CA, USA.
11
Department of Human Genetics, University of California, Los Angeles, CA, USA.

Abstract

BEAGLE is a high-performance likelihood-calculation library for phylogenetic inference. The BEAGLE library defines a simple, but flexible, application programming interface (API), and includes a collection of efficient implementations for calculation under a variety of evolutionary models on different hardware devices. The library has been integrated into recent versions of popular phylogenetics software packages including BEAST and MrBayes, and has been widely used across a diverse range of evolutionary studies. Here we present BEAGLE 3, with new parallel implementations, increased performance for challenging data sets, improved scalability, and better usability. We have added new openCL and CPU (central processing unit)-threaded implementations to the library, allowing the effective utilization of a wider range of modern hardware. Further, we have extended the API and library to support concurrent computation of independent partial likelihood arrays, for increased performance of nucleotide-model analyses with greater flexibility of data partitioning. For better scalability and usability, we have improved how phylogenetic software packages use BEAGLE in multi-GPU (graphics processing unit) and cluster environments, and introduced an automated method to select the fastest device given the data set, evolutionary model, and hardware. For application developers who wish to integrate the library, we also have developed an online tutorial. To evaluate the effect of the improvements, we ran a variety of benchmarks on state-of-the-art hardware. For a partitioned exemplar analysis, we observe run-time performance improvements as high as 5.9-fold over our previous GPU implementation. BEAGLE 3 is free, open-source software licensed under the Lesser GPL and available at https://beagle-dev.github.io.

KEYWORDS:

Bayesian phylogenetics; GPU; maximum likelihood; multicore processing; parallel computing

PMID:
31034053
DOI:
10.1093/sysbio/syz020

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