Load Balance in the Phylogenetic Likelihood Kernel

—Recent advances in DNA sequencing techniques have led to an unprecedented accumulation and availability of molecular sequence data that needs to be analyzed. This data explosion in combination with the multi-core revolution also affects the computational kernels for phylogenetic inference (reconstruction of evolutionary trees from molecular sequence data) under the widely-used Maximum Likelihood (ML) model. At present, analyses of so called multi-gene or phylogenomic alignments, i.e., input data sets that comprise concatenated sequence data of several genes, are becoming increasingly popular. Usually such multi-gene analyses are partitioned, i.e., a separate set of likelihood model parameters is estimated for each gene/partition. While the phylogenetic likelihood function exhibits intrinsic fine-grained parallelism, the parallel computation of the likelihood function in such partitioned multigene analyses can lead to significant load-balance problems. Here, we describe these probl...

• Type: Conference
• Year: 2009
• Where: ICPP
• Authors: Alexandros Stamatakis, Michael Ott
• Keywords: Distributed And Parallel Computing, ICPP 2009, Likelihood Function, Molecular Sequence Data, Sequence Data