Exascale Maximum Likelihood (ExaML) code for phylogenetic inference


Exascale Maximum Likelihood (ExaML) is a code for phylogenetic inference using MPI. This code implements the popular RAxML search algorithm for maximum likelihood based inference of phylogenetic trees.

ExaML is a strapped-down light-weight version of RAxML for phylogenetic inference on huge datasets. It can only execute some very basic functions and is intended for computer-savvy users that can write little perl-scripts and have experience using queue submission scripts for clusters. ExaML only implements the CAT and GAMMA models of rate heterogeneity for binary, DNA, and protein data.

ExaML uses a radically new MPI parallelization approach that yields improved parallel efficiency, in particular on partitioned multi-gene or whole-genome datasets. It also implements a new load balancing algorithm that yields better parallel efficiency.

It is up to 4 times faster than its predecessor RAxML-Light and scales to a larger number of processors.

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