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RAxML-Light: a tool for computing terabyte phylogenies

Motivation: Due to advances in molecular sequencing and the increasingly rapid collection of molecular data, the field of phyloinformatics is transforming into a computational science. Therefore, new tools are required that can be deployed in supercomputing environments and that scale to hundreds or...

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Detalles Bibliográficos
Autores principales: Stamatakis, A., Aberer, A.J., Goll, C., Smith, S.A., Berger, S.A., Izquierdo-Carrasco, F.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3400957/
https://www.ncbi.nlm.nih.gov/pubmed/22628519
http://dx.doi.org/10.1093/bioinformatics/bts309
Descripción
Sumario:Motivation: Due to advances in molecular sequencing and the increasingly rapid collection of molecular data, the field of phyloinformatics is transforming into a computational science. Therefore, new tools are required that can be deployed in supercomputing environments and that scale to hundreds or thousands of cores. Results: We describe RAxML-Light, a tool for large-scale phylogenetic inference on supercomputers under maximum likelihood. It implements a light-weight checkpointing mechanism, deploys 128-bit (SSE3) and 256-bit (AVX) vector intrinsics, offers two orthogonal memory saving techniques and provides a fine-grain production-level message passing interface parallelization of the likelihood function. To demonstrate scalability and robustness of the code, we inferred a phylogeny on a simulated DNA alignment (1481 taxa, 20 000 000 bp) using 672 cores. This dataset requires one terabyte of RAM to compute the likelihood score on a single tree. Code Availability: https://github.com/stamatak/RAxML-Light-1.0.5 Data Availability: http://www.exelixis-lab.org/onLineMaterial.tar.bz2 Contact: alexandros.stamatakis@h-its.org Supplementary Information: Supplementary data are available at Bioinformatics online.