A generic vectorization scheme and a GPU kernel for the phylogenetic likelihood library

Fernando Izquierdo-Carrasco, Nikolaos Alachiotis, Simon Berger, Tomas Flouri, Solon P. Pissis, Alexandros Stamatakis

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review

Abstract

Highly optimized library implementations for important scientific kernels can improve scientific productivity. To this end, we are currently developing the Phylogenetic Likelihood Library (PLL) that implements functions to compute and optimize the phylogenetic likelihood score on evolutionary trees. Here, we focus on novel techniques to orchestrate likelihood computations on large vector-like processors such as GPUs. We present a novel scheme for vectorizing computations and organizing conditional likelihood arrays (CLAs) in such a way that they do not need to be transferred at all between the GPU and the CPU. We compare the performance of our GPU implementation for DNA data with a highly optimized x86 version of the PLL that relies on manually tuned AVX intrinsics. Our GPU implementation accelerates the likelihood computations by a factor of two compared to the, most probably, currently fastest available x86 implementation. We conclude that, a hybrid GPU-CPU version needs to be developed and integrated into the PLL to leverage the computational power of modern desktop systems and clusters.

Original languageEnglish
Title of host publicationProceedings - IEEE 27th International Parallel and Distributed Processing Symposium Workshops and PhD Forum, IPDPSW 2013
PublisherIEEE Computer Society
Pages530-538
Number of pages9
ISBN (Print)9780769549798
DOIs
Publication statusPublished - 1 Jan 2013
Externally publishedYes
Event2013 IEEE 37th Annual Computer Software and Applications Conference, COMPSAC 2013 - Boston, MA, Japan
Duration: 22 Jul 201326 Jul 2013

Publication series

NameProceedings - IEEE 27th International Parallel and Distributed Processing Symposium Workshops and PhD Forum, IPDPSW 2013

Conference

Conference2013 IEEE 37th Annual Computer Software and Applications Conference, COMPSAC 2013
CountryJapan
CityBoston, MA
Period22/07/1326/07/13

Keywords

  • GPU
  • maximum likelihood
  • OpenCL
  • phylogenetics
  • vector intrinsics

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