A Global Grid for Analysis of Arthropod Evolution

• Published in: Fifth IEEE/ACM International Workshop on Grid Computing pp. 328 - 337
• Main Authors: Stewart, Craig A., Keller, Rainer, Repasky, Richard, Hess, Matthias, Hart, David, Muller, Matthias, Sheppard, Ray, Wossner, Uwe, Aumuller, Martin, Li, Huian, Berry, Donald K., Colbourne, John
• Format: Conference Proceeding
• Language: English
• Published: Washington, DC, USA IEEE Computer Society 08-11-2004; IEEE
• Series: ACM Conferences
• Subjects: Applied computing; Applied computing > Life and medical sciences; Applied computing > Life and medical sciences > Genetics; Applied computing > Life and medical sciences > Systems biology; Biology computing; Computer systems organization; Computer systems organization > Dependable and fault-tolerant systems and networks; Distributed computing; Evolution (biology); General and reference; General and reference > Cross-computing tools and techniques; General and reference > Cross-computing tools and techniques > Performance; Genetics; Grid computing; High performance computing; History; Networks; Networks > Network performance evaluation; Organisms; Phylogeny; Software and its engineering; Software and its engineering > Software organization and properties; Software and its engineering > Software organization and properties > Software system structures; Software and its engineering > Software organization and properties > Software system structures > Distributed systems organizing principles; Supercomputers
• ISBN: 0769522564; 9780769522562
• ISSN: 1550-5510; 2377-6374
• DOI: 10.1109/GRID.2004.1

Maximum likelihood analysis is a powerful technique for inferring evolutionary histories from genetic sequence data. During the fall of 2003, an international team of computer scientists, biologists, and computer centers created a global grid to analyze the evolution of hexapods (arthropods with six legs). We created a global grid of computers using systems located in eight countries, spread across six continents (every continent but Antarctica). This work was done as part of the SC03 HPC Challenge, and this project was given an HPC Challenge award for the "Most Distributed Application." More importantly, the creation of this computing grid enabled investigation of important questions regarding the evolution of arthropods - research that would not have otherwise been undertaken. Grid computing will thus lead directly to new scientific insights.