Title :
MeDiCi-Cloud: A Workflow Infrastructure for Large-scale Scientific Applications
Author :
Yin, Jian ; Lin, Guang ; Gorton, Ian ; Binh Han
Abstract :
Cloud computing is attractive for large-scale scientific applications. However, unlike typical commercial applications, large-scale scientific applications often need to process enormous amount of data in the terabyte or even petabyte range and require special high performance hardware with low latency connections to complete computation in a reasonable amount of time. To address these challenges, we build an infrastructure that can dynamically select high performance computing hardware across institutions and dynamically adapt the computation to the selected resources to achieve high performance. We have also demonstrated the effectiveness of our infrastructure by building a system biology application and an uncertainty quantification application for carbon sequestration, which can efficiently utilize data and computation resources across several institutions.
Keywords :
cloud computing; natural sciences computing; resource allocation; MeDiCi-Cloud; carbon sequestration; cloud computing; computation resource utilization; high performance computing hardware; large-scale scientific applications; low latency connections; quantification application; system biology application; workflow infrastructure; Biomedical imaging; Cloud computing; Data processing; Laboratories; Systems biology; Virtual machining; cloud computing; scientific computing; workflow;
Conference_Titel :
Utility and Cloud Computing (UCC), 2011 Fourth IEEE International Conference on
Conference_Location :
Victoria, NSW
Print_ISBN :
978-1-4577-2116-8
DOI :
10.1109/UCC.2011.56