Comparing FutureGrid, Amazon EC2, and Open Science Grid for Scientific Workflows

Scientists have a number of computing infrastructures available to conduct their research, including grids and public or private clouds. This paper explores the use of these cyberinfrastructures to execute scientific workflows, an important class of scientific applications. It examines the benefits and drawbacks of cloud and grid systems using the case study of an astronomy application. The application analyzes data from the NASA Kepler mission in order to compute periodograms, which help astronomers detect the periodic dips in the intensity of starlight caused by exoplanets as they transit their host star. In this paper we describe our experiences modeling the periodogram application as a scientific workflow using Pegasus, and deploying it on the FutureGrid scientific cloud testbed, the Amazon EC2 commercial cloud, and the Open Science Grid. We compare and contrast the infrastructures in terms of setup, usability, cost, resource availability and performance

Guest Editors Introduction: Cloud Computing

The guest editors discuss this special issue on cloud computing, exploring how cloud platforms and abstractions can be effectively used to support real-world science and engineering applications

A scientist's guide to cloud computing

New tools (some commercial and even public), have made it so that dealing with the cloud and running large-scale processing can be rather easy and efficient. Cloud's appeal for science is clear: simplicity, elasticity (that is, the availability of large resources on the spot by launching as many instances as needed), true reproducibility (the virtual machine and the code running on that machine can be made public together with the data, when necessary), the ability to cover a large span of open questions previously unattainable due to a possible lack of computing power, and most importantly, democratization of science (since anyone has access to large computing power). PiCloud (www.multyvac.com) is one of the first commercial entities with a special focus on making scientific computing in the cloud simple for the users. PiCloud provisions AWS instances transparently to the user, acting as a middleware between AWS and the user. Their provisioning technology allows PiCloud to compete for the lower cost spot instances on Amazon