Exploring Parallel MPI Fault Tolerance Mechanisms for Phylogenetic Inference with RAxML-NG

Abstract

Phylogenetic trees are now routinely inferred on large scale HPC systems with thousands of cores as the parallel scalability of phylogenetic inference tools has improved over the past years to cope with the molecular data avalanche. Thus, the parallel fault tolerance of phylogenetic inference tools has become a relevant challenge. To this end, we explore parallel fault tolerance mechanisms and algorithms, the software modifications required, and the performance penalties induced via enabling parallel fault tolerance by example of RAxML-NG, the successor of the widely used RAxML tool for maximum likelihood based phylogenetic tree inference. We find that the slowdown induced by the necessary additional recovery mechanisms in RAxML-NG is on average 2%. The overall slowdown by using these recovery mechanisms in conjunction with a fault tolerant MPI implementation amounts to 8% on average for large empirical datasets. Via failure simulations, we show that RAxML-NG can successfully recover from multiple simultaneous failures, subsequent failures, failures during recovery, and failures during checkpointing. Recoveries are automatic and transparent to the user. The modified fault tolerant RAxML-NG code is available under GNU GPL at https://github.com/lukashuebner/ft-raxml-ng Contact: lukas.huebner@{kit.edu,h-its.org};, alexey.kozlov@h-its.org, hespe@kit.edu, sanders@kit.edu, alexandros.stamatakis@hits.org Supplementary information: Supplementary data are available at bioRχiv.