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- W1999597918 abstract "Cloud computing has drawn increasing attention from the scientific computing community due to its ease of use, elasticity, and relatively low cost. Because a high-performance computing (HPC) application is usually resource demanding, without careful planning, it can incur a high monetary expense even in Cloud. We design a tool called CAP3 (Cloud Auto-Provisioning framework for Parallel Processing) to help a user minimize the expense of running an HPC application in Cloud, while meeting the user-specified job deadline. Given an HPC application, CAP3 automatically profiles the application, builds a model to predict its performance, and infers a proper cluster size that can finish the job within its deadline while minimizing the total cost. To further reduce the cost, CAP3 intelligently chooses the Cloud's reliable on-demand instances or low-cost spot instances, depending on whether the remaining time is tight in meeting the application's deadline. Experiments on Amazon EC2 show that the execution strategy given by CAP3 is cost-effective, by choosing a proper cluster size and a proper instance type (on-demand or spot)." @default.
- W1999597918 created "2016-06-24" @default.
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- W1999597918 date "2013-06-01" @default.
- W1999597918 modified "2023-09-26" @default.
- W1999597918 title "CAP3: A Cloud Auto-Provisioning Framework for Parallel Processing Using On-Demand and Spot Instances" @default.
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- W1999597918 doi "https://doi.org/10.1109/cloud.2013.41" @default.
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