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A Practical Guide to Phylogenetics for Nonexperts
12:00

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Published on: February 5, 2014

RAxML-Light: a tool for computing terabyte phylogenies.

A Stamatakis1, A J Aberer, C Goll

  • 1The Exelixis Lab, Scientific Computing Group, Heidelberg Institute for Theoretical Studies, Schloss-Wolfsbrunnenweg 35, D-68159 Heidelberg, Germany. alexandros.stamatakis@h-its.org

Bioinformatics (Oxford, England)
|May 26, 2012
PubMed
Summary
This summary is machine-generated.

RAxML-Light is a new tool for large-scale phylogenetic inference on supercomputers. It efficiently handles massive DNA datasets, enabling robust evolutionary analyses with its scalable parallelization and memory-saving techniques.

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Area of Science:

  • Computational Biology
  • Phylogenetics
  • Bioinformatics

Background:

  • Advances in molecular sequencing generate vast amounts of data, necessitating computational science approaches in phyloinformatics.
  • Existing tools require enhancement to operate effectively in supercomputing environments and scale to numerous cores.

Purpose of the Study:

  • To introduce RAxML-Light, a novel tool designed for large-scale phylogenetic inference on supercomputers.
  • To address the need for scalable computational tools in the rapidly evolving field of phyloinformatics.

Main Methods:

  • RAxML-Light implements a lightweight checkpointing mechanism for enhanced robustness.
  • The tool utilizes 128-bit (SSE3) and 256-bit (AVX) vector intrinsics for performance optimization.
  • It incorporates two orthogonal memory-saving techniques and fine-grained Message Passing Interface (MPI) parallelization for likelihood computation.

Main Results:

  • Demonstrated scalability and robustness by inferring a phylogeny from a simulated DNA alignment (1481 taxa, 20 million base pairs) using 672 cores.
  • The analysis required one terabyte of RAM to compute the likelihood score on a single tree, highlighting the dataset's scale.

Conclusions:

  • RAxML-Light is a powerful and scalable tool for phylogenetic inference in supercomputing environments.
  • The software facilitates the analysis of massive datasets, advancing the field of phyloinformatics.