A cluster-based solution for high performance hmmpfam using EARTH execution model

Author

Zhu, Weirong ; Niu, Yanwei ; Lu, Jizhu ; Shen, Chuan ; Gao, Guang R.

Author_Institution

Dept. of Electr. & Comput. Eng., Delaware Univ., Newark, DE, USA

fYear

2003

fDate

1-4 Dec. 2003

Firstpage

30

Lastpage

37

Abstract

Hmmpfam is a widely used computation-intensive bioinformatics software for sequence classification. The contribution of this paper is the first largely scalable and robust cluster-based solution of parallel hmmpfam based on EARTH (Efficient Architecture for Running Threads), which is an event-driven fine-grain multi-threaded programming execution model. Compared with the original PVM implementation, our implementation shows notable improvements on absolute speed-up and better scalability. Experiments on two advanced supercomputing clusters at Argonne National Laboratory (ANL) achieve an absolute speedup of 222.8 on 128 dual-CPU nodes for a representative data set, which means that the total execution time is reduced from 15.9 hours (serial program) to only 4.3 minutes.

Keywords

biology computing; hidden Markov models; multi-threading; sequences; workstation clusters; EARTH execution model; Efficient Architecture for Runnning Threads; PVM implementation; cluster-based solution; computation-intensive bioinformatics software; high performance hmmpfam; multithreaded programming execution; parallel hmmpfam; sequence classification; supercomputing clusters; Application software; Bioinformatics; Biomedical computing; Computer architecture; Databases; Drugs; Earth; Hidden Markov models; Packaging; Proteins; Sequences;

fLanguage

English

Publisher

ieee

Conference_Titel

Cluster Computing, 2003. Proceedings. 2003 IEEE International Conference on

Print_ISBN

0-7695-2066-9

Type

conf

DOI

10.1109/CLUSTR.2003.1253296

Filename

1253296