Overview

Summary

• The practice of implementing cloud computing in Environmental science area is focused on modeling such as ocean climate modeling (Evangelinos et al. 2008) and groundwater modeling (Hunt et al. 2010).
• Cloud computing is also used in data analysis such as parallelize sequential data analysis tasks (Hasenkamp et al. 2010).

Workflow

Data

• Example: Analyzing 500GB repository on Magellan with 8 VM instances: 9hrs, on single-processor workstation: 90~95hrs (Hasenkamp et al. 2010)

Cloud platform

• Amazon EC2 (Evangelinos et al. 2008, He et al. 2010)
• GoGrid (Hunt et al. 2010, He et al. 2010)
• FutureGrid with Nimbus and Eucalyptus (Fox et al. 2011)
• Azure (Eye on Earth)
• Magellan with Eucalyptus (Hasenkamp et al. 2010)

Issues/Gaps

• Performance of Cloud is limited by messaging performance (Evangelinos et al. 2008)
• Lack of robust script/batch programs (Hunt et al. 2010)
• Most public clouds are optimized for running business applications instead of HPC (He et al. 2010)

Running Coupled Atmosphere-Ocean Climate Models on Amazon's EC2 ¹

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