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An early performance analysis of cloud computing services for scientific computing
| Content Provider | CiteSeerX |
|---|---|
| Author | Epema, Dick Prodan, Radu Iosup, Ru Yigitbasi, Nezih Fahringer, Thomas Ostermann, Simon |
| Abstract | Abstract—Cloud computing is an emerging commercial infrastructure paradigm that promises to eliminate the need for maintaining expensive computing facilities by companies and institutes alike. Through the use of virtualization and resource time-sharing, clouds serve with a single set of physical resources a large user base with different needs. Thus, clouds have the potential to provide to their owners the benefits of an economy of scale and, at the same time, become an alternative for scientists to clusters, grids, and parallel production environments. However, the current commercial clouds have been built to support web and small database workloads, which are very different from typical scientific computing workloads. Moreover, the use of virtualization and resource time-sharing may introduce significant performance penalties for the demanding scientific computing workloads. In this work we analyze the performance of cloud computing services for scientific computing workloads. We quantify the presence in real scientific computing workloads of Many-Task Computing (MTC) users, that is, of users who employ loosely coupled applications comprising many tasks to achieve their scientific goals. Then, we perform an empirical evaluation of the performance of four commercial cloud computing services including Amazon EC2, which is currently the largest commercial cloud. Last, we compare through trace-based simulation the performance characteristics and cost models of clouds and other scientific computing platforms, for general and MTC-based scientific computing workloads. Our results indicate that the current clouds need an order of magnitude in performance improvement to be useful to the scientific community, and show which improvements should be considered first to address this discrepancy between offer and demand. |
| File Format | |
| Publisher Institution | TU Delft, Tech. Rep., Dec 2008, [Online] Available |
| Access Restriction | Open |
| Subject Keyword | Commercial Cloud Different Need Performance Improvement Current Commercial Cloud Large User Base Commercial Infrastructure Paradigm Parallel Production Environment Many-task Computing Current Cloud Scientific Community Many Task Physical Resource Amazon Ec2 Single Set Trace-based Simulation Empirical Evaluation Scientific Computing Early Performance Analysis Small Database Workload Abstract Cloud Computing Resource Time-sharing Cloud Computing Service Performance Characteristic Significant Performance Penalty Cost Model Scientific Goal |
| Content Type | Text |
