AliSim-HPC: parallel sequence simulator for phylogenetics

Abstract

Motivation: Sequence simulation plays a vital role in phylogenetics with many applications, such as evaluating phylogenetic methods, testing hypotheses, and generating training data for machine-learning applications. We recently introduced a new simulator for multiple sequence alignments called AliSim, which outperformed existing tools. However, with the increasing demands of simulating large data sets, AliSim is still slow due to its sequential implementation; for example, to simulate millions of sequence alignments, AliSim took several days or weeks. Parallelization has been used for many phylogenetic inference methods but not yet for sequence simulation. Results: This paper introduces AliSim-HPC, which, for the first time, employs high-performance computing for phylogenetic simulations. AliSim-HPC parallelizes the simulation process at both multi-core and multi-CPU levels using the OpenMP and MPI libraries, respectively. AliSim-HPC is highly efficient and scalable, which reduces the runtime to simulate 100 large alignments from one day to 9 minutes using 256 CPU cores from a cluster with 6 computing nodes, a 162-fold speedup. Availability and implementation: AliSim-HPC is open source and available as part of the new IQ-TREE version v2.2.2.2 at https://github.com/iqtree/iqtree2/releases with a user manual at http://www.iqtree.org/doc/AliSim.