GPFS: A Shared-Disk File System for Large Computing Clusters
FAST '02 Proceedings of the Conference on File and Storage Technologies
HPDC '96 Proceedings of the 5th IEEE International Symposium on High Performance Distributed Computing
Grid'5000: A Large Scale And Highly Reconfigurable Experimental Grid Testbed
International Journal of High Performance Computing Applications
Case study for running HPC applications in public clouds
Proceedings of the 19th ACM International Symposium on High Performance Distributed Computing
BlobSeer: Next-generation data management for large scale infrastructures
Journal of Parallel and Distributed Computing
Exploring the Performance Fluctuations of HPC Workloads on Clouds
CLOUDCOM '10 Proceedings of the 2010 IEEE Second International Conference on Cloud Computing Technology and Science
Cost-Effective HPC: The Community or the Cloud?
CLOUDCOM '10 Proceedings of the 2010 IEEE Second International Conference on Cloud Computing Technology and Science
Cumulus: an open source storage cloud for science
Proceedings of the 2nd international workshop on Scientific cloud computing
Analysis of Virtualization Technologies for High Performance Computing Environments
CLOUD '11 Proceedings of the 2011 IEEE 4th International Conference on Cloud Computing
State of the Practice Reports
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The emergence of Cloud computing has given rise to numerous attempts to study the portability of scientific applications to this new paradigm. Tightly-coupled applications are a common class of scientific HPC applications, which exhibit specific requirements previously addressed by supercomputers. A key challenge towards the adoption of the Cloud paradigm for such applications is data management. In this paper, we argue that Cloud storage services represent a suitable data storage and sharing option for Cloud applications. We evaluate a distributed storage plugin for Cumulus, an S3-compatible open-source Cloud service, and we conduct a series of experiments with an atmospheric modeling application running in a private Cloud deployed on the Grid'5000 testbed. Our results, obtained on up to 144 parallel processes, show that the application is able to scale with the size of the data and the number of processes, while storing 50 GB of output data on a Cloud storage service.