Paper Info
Title
A Lightweight, Scalable Grid Computing Framework for Parallel Bioinformatics Applications
Abstract
In recent years our society has witnessed an unprecedented growth in computing power available to tackle important problems in science, engineering and medicine. For example, the SHARCNET network links large computing resources in 11 leading academic institutions in South Central Ontario, thus providing access to thousands of compute processors. It is a continuous challenge to develop efficient and scalable algorithms and methods for solving large scientific and engineering problems on such parallel and distributed computers. If the computing power available in such computational grids can be unleashed effectively in a scalable way, large scientific problems can be solved that would otherwise be hard to solve using the machines available in a stand-alone way. This paper describes techniques and software developed that allow to apply the power of computational grids to large-scale, loosely coupled parallel bioinformatics problems. Our approach is based on decentralization and implemented in Java, leading to a flexible, portable and scalable software solution for parallel bioinformatics. We discuss advantages and disadvantages of this approach, and demonstrate seamless performance on an ad-hoc grid composed of a wide variety of hardware for a real-life parallel bioinformatics problem. The bioinformatics problem described consists of virtual experiments in RNA folding executed on hundreds of compute processors concurrently, which may establish one of the missing links in the chain of events that led to the origin of life.
Year
DOI
Venue
2005
10.1109/HPCS.2005.7
HPCS
Keywords
Field
DocType
parallel bioinformatics,large scientific problem,scalable algorithm,computing power,bioinformatics problem,scalable grid computing framework,large computing resource,computational grid,real-life parallel bioinformatics problem,parallel bioinformatics problem,parallel bioinformatics applications,scalable software solution,distributed computing,concurrent computing,bioinformatics,software development,grid computing,hardware,macromolecules,rna,origin of life,java,computer networks
Grid computing,Computer science,Parallel computing,Rna folding,Software,Scalable algorithms,Bioinformatics,Concurrent computing,Java,Grid,Distributed computing,Scalability
Conference
ISBN
Citations 
PageRank 
0-7695-2343-9
1
0.36
References 
Authors
2
3
Name
Order
Citations
PageRank
Hans De Sterck120426.14
Rob Markel210.36
Rob Knight336626.19