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119 results on '"Mehta, Gaurang"'

1. Data Sharing Options for Scientific Workflows on Amazon EC2

Author

Juve, Gideon, Deelman, Ewa, Vahi, Karan, Mehta, Gaurang, Berriman, Bruce, Berman, Benjamin P., and Maechling, Phil

Subjects
Astrophysics - Instrumentation and Methods for Astrophysics, Computer Science - Distributed, Parallel, and Cluster Computing
Abstract

Efficient data management is a key component in achieving good performance for scientific workflows in distributed environments. Workflow applications typically communicate data between tasks using files. When tasks are distributed, these files are either transferred from one computational node to another, or accessed through a shared storage system. In grids and clusters, workflow data is often stored on network and parallel file systems. In this paper we investigate some of the ways in which data can be managed for workflows in the cloud. We ran experiments using three typical workflow applications on Amazon's EC2. We discuss the various storage and file systems we used, describe the issues and problems we encountered deploying them on EC2, and analyze the resulting performance and cost of the workflows., Comment: 9 pages, 7 figures. Accepted for publication in the Proceedings of Supercomputing 10

Published
2010

2. Pipeline-Centric Provenance Model

Author

Groth, Paul, Deelman, Ewa, Juve, Gideon, Mehta, Gaurang, and Berriman, Bruce

Subjects
Astrophysics - Instrumentation and Methods for Astrophysics, Computer Science - Information Retrieval
Abstract

In this paper we propose a new provenance model which is tailored to a class of workflow-based applications. We motivate the approach with use cases from the astronomy community. We generalize the class of applications the approach is relevant to and propose a pipeline-centric provenance model. Finally, we evaluate the benefits in terms of storage needed by the approach when applied to an astronomy application., Comment: 9 pages, 4 figures

Published
2010

3. Scientific Workflow Applications on Amazon EC2

Author

Juve, Gideon, Deelman, Ewa, Vahi, Karan, Mehta, Gaurang, Berriman, Bruce, Berman, Benjamin P., and Maechling, Phil

Subjects
Astrophysics - Instrumentation and Methods for Astrophysics, Computer Science - Distributed, Parallel, and Cluster Computing
Abstract

The proliferation of commercial cloud computing providers has generated significant interest in the scientific computing community. Much recent research has attempted to determine the benefits and drawbacks of cloud computing for scientific applications. Although clouds have many attractive features, such as virtualization, on-demand provisioning, and "pay as you go" usage-based pricing, it is not clear whether they are able to deliver the performance required for scientific applications at a reasonable price. In this paper we examine the performance and cost of clouds from the perspective of scientific workflow applications. We use three characteristic workflows to compare the performance of a commercial cloud with that of a typical HPC system, and we analyze the various costs associated with running those workflows in the cloud. We find that the performance of clouds is not unreasonable given the hardware resources provided, and that performance comparable to HPC systems can be achieved given similar resources. We also find that the cost of running workflows on a commercial cloud can be reduced by storing data in the cloud rather than transferring it from outside.

Published
2010
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4. Enabling Data and Compute Intensive Workflows in Bioinformatics

Author

Mehta, Gaurang, Deelman, Ewa, Knowles, James A., Chen, Ting, Wang, Ying, Vöckler, Jens, Buyske, Steven, Matise, Tara, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Alexander, Michael, editor, D’Ambra, Pasqua, editor, Belloum, Adam, editor, Bosilca, George, editor, Cannataro, Mario, editor, Danelutto, Marco, editor, Di Martino, Beniamino, editor, Gerndt, Michael, editor, Jeannot, Emmanuel, editor, Namyst, Raymond, editor, Roman, Jean, editor, Scott, Stephen L., editor, Traff, Jesper Larsson, editor, Vallée, Geoffroy, editor, and Weidendorfer, Josef, editor

Published
2012
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7. Pegasus: Mapping Scientific Workflows onto the Grid

Author

Deelman, Ewa, Blythe, James, Gil, Yolanda, Kesselman, Carl, Mehta, Gaurang, Patil, Sonal, Su, Mei-Hui, Vahi, Karan, Livny, Miron, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, and Dikaiakos, Marios D., editor

Published
2004
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8. Pegasus and the Pulsar Search: From Metadata to Execution on the Grid

Author

Deelman, Ewa, Blythe, James, Gil, Yolanda, Kesselman, Carl, Koranda, Scott, Lazzarini, Albert, Mehta, Gaurang, Papa, Maria Alessandra, Vahi, Karan, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Wyrzykowski, Roman, editor, Dongarra, Jack, editor, Paprzycki, Marcin, editor, and Waśniewski, Jerzy, editor

Published
2004
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19. Pegasus: Mapping Scientific Workflows onto the Grid

Author

Deelman, Ewa, primary, Blythe, James, additional, Gil, Yolanda, additional, Kesselman, Carl, additional, Mehta, Gaurang, additional, Patil, Sonal, additional, Su, Mei-Hui, additional, Vahi, Karan, additional, and Livny, Miron, additional

Published
2004
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23. The First Provenance Challenge

Author

Moreau, Luc, Ludaescher, Bertram, Altintas, Ilkay, Barga, Roger S., Bowers, Shawn, Callahan, Steven, Chin Jr., George, Clifford, Ben, Cohen, Shirley, Cohen-Boulakia, Sarah, Davidson, Susan, Deelman, Ewa, Digiampietri, Luciano, Foster, Ian, Freire, Juliana, Frew, James, Futrelle, Joe, Gibson, Tara, Gil, Yolanda, Goble, Carole, Golbeck, Jennifer, Groth, Paul, Holland, David A., Jiang, Sheng, Kim, Jihie, Koop, David, Krenek, Ales, McPhillips, Timothy, Mehta, Gaurang, Miles, Simon, Metzger, Dominic, Munroe, Steve, Myers, Jim, Plale, Beth, Podhorszki, Norbert, Ratnakar, Varun, Santos, Emanuele, Scheidegger, Carlos, Schuchardt, Karen, Seltzer, Margo, Simmhan, Yogesh L., Silva, Claudio, Slaughter, Peter, Stephan, Eric, Stevens, Robert, Turi, Daniele, Vo, Huy, Wilde, Mike, and Zhao, Jun

Abstract

The first Provenance Challenge was set up in order to provide a forum for the community to help understand the capabilities of different provenance systems and the expressiveness of their provenance representations. To this end, a Functional Magnetic Resonance Imaging workflow was defined, which participants had to either simulate or run in order to produce some provenance representation, from which a set of identified queries had to be implemented and executed. Sixteen teams responded to the challenge, and submitted their inputs. In this paper, we present the challenge workflow and queries, and summarise the participants contributions.

Published
2008

25. SCEC CyberShake Workflows—Automating Probabilistic Seismic Hazard Analysis Calculations

Author

Maechling, Philip, primary, Deelman, Ewa, additional, Zhao, Li, additional, Graves, Robert, additional, Mehta, Gaurang, additional, Gupta, Nitin, additional, Mehringer, John, additional, Kesselman, Carl, additional, Callaghan, Scott, additional, Okaya, David, additional, Francoeur, Hunter, additional, Gupta, Vipin, additional, Cui, Yifeng, additional, Vahi, Karan, additional, Jordan, Thomas, additional, and Field, Edward, additional

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26. Scalable Knowledge Discovery Through Grid Workflows

Author

UNIVERSITY OF SOUTHERN CALIFORNIA MARINA DEL REY INFORMATION SCIENCES INST, Gil, Yolanda, Deelman, Ewa, Kim, Jihie, Groth, Paul, Mehta, Gaurang, Ratnakar, Varun, Vahi, Karan, UNIVERSITY OF SOUTHERN CALIFORNIA MARINA DEL REY INFORMATION SCIENCES INST, Gil, Yolanda, Deelman, Ewa, Kim, Jihie, Groth, Paul, Mehta, Gaurang, Ratnakar, Varun, and Vahi, Karan

Abstract

The goal of this effort was to drastically reduce the human effort required to configure and execute new workflows for data analysis from weeks to minutes by eliminating the need for costly human monitoring and intervention. This involves developing end-to-end data analysis systems to analyze data from many different sources and with many different algorithms and analytical tools. Their approach combined three central ideas: 1) workflows with rich representations of algorithmic requirements and data products, 2) semantic representations to enable automatic generation of complex workflows, and 3) grid computing to manage the high performance of many workflows in distributed cross-organization environments., The original document contains color images.

Published
2009

27. Scientific workflow applications on Amazon EC2

Author

Juve, Gideon, Deelman, Ewa, Vahi, Karan, Mehta, Gaurang, Berriman, Bruce, Berman, Benjamin P., Maechling, Phil, Juve, Gideon, Deelman, Ewa, Vahi, Karan, Mehta, Gaurang, Berriman, Bruce, Berman, Benjamin P., and Maechling, Phil

Abstract

The proliferation of commercial cloud computing providers has generated significant interest in the scientific computing community. Much recent research has attempted to determine the benefits and drawbacks of cloud computing for scientific applications. Although clouds have many attractive features, such as virtualization, on-demand provisioning, and “pay as you go” usage-based pricing, it is not clear whether they are able to deliver the performance required for scientific applications at a reasonable price. In this paper we examine the performance and cost of clouds from the perspective of scientific workflow applications. We use three characteristic workflows to compare the performance of a commercial cloud with that of a typical HPC system, and we analyze the various costs associated with running those workflows in the cloud. We find that the performance of clouds is not unreasonable given the hardware resources provided, and that performance comparable to HPC systems can be achieved given similar resources. We also find that the cost of running workflows on a commercial cloud can be reduced by storing data in the cloud rather than transferring it from outside.

Published
2009

28. Workflow task clustering for best effort systems with Pegasus

Author

Katz, Daniel S., Singh, Gurmeet, Su, Mei-Hui, Vahi, Karan, Deelman, Ewa, Berriman, Bruce, Good, John, Mehta, Gaurang, Katz, Daniel S., Singh, Gurmeet, Su, Mei-Hui, Vahi, Karan, Deelman, Ewa, Berriman, Bruce, Good, John, and Mehta, Gaurang

Abstract

Many scientific workflows are composed of fine computational granularity tasks, yet they are composed of thousands of them and are data intensive in nature, thus requiring resources such as the TeraGrid to execute efficiently. In order to improve the performance of such applications, we often employ task clustering techniques to increase the computational granularity of workflow tasks. The goal is to minimize the completion time of the workflow by reducing the impact of queue wait times. In this paper, we examine the performance impact of the clustering techniques using the Pegasus workflow management system. Experiments performed using an astronomy workflow on the NCSA TeraGrid cluster show that clustering can achieve a significant reduction in the workflow completion time (up to 97%).

Published
2008

29. On the Use of Cloud Computing for Scientific Workflows

Author

Hoffa, Christina, Mehta, Gaurang, Freeman, Tim, Deelman, Ewa, Keahey, Kate, Berriman, Bruce, Good, John, Hoffa, Christina, Mehta, Gaurang, Freeman, Tim, Deelman, Ewa, Keahey, Kate, Berriman, Bruce, and Good, John

Abstract

This paper explores the use of cloud computing for scientific workflows, focusing on a widely used astronomy application-Montage. The approach is to evaluate from the point of view of a scientific workflow the tradeoffs between running in a local environment, if such is available, and running in a virtual environment via remote, wide-area network resource access. Our results show that for Montage, a workflow with short job runtimes, the virtual environment can provide good compute time performance but it can suffer from resource scheduling delays and wide-area communications.

Published
2008

30. A General Approach to Real-Time Workflow Monitoring

Author

Vahi, Karan, primary, Harvey, Ian, additional, Samak, Taghrid, additional, Gunter, Daniel, additional, Evans, Kieran, additional, Rogers, Dave, additional, Taylor, Ian, additional, Goode, Monte, additional, Silva, Fabio, additional, Al-Shakarchi, Eddie, additional, Mehta, Gaurang, additional, Jones, Andrew, additional, and Deelman, Ewa, additional

Published
2012
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39. CyberShake: A Physics-Based Seismic Hazard Model for Southern California

Author

Graves, Robert, primary, Jordan, Thomas H., additional, Callaghan, Scott, additional, Deelman, Ewa, additional, Field, Edward, additional, Juve, Gideon, additional, Kesselman, Carl, additional, Maechling, Philip, additional, Mehta, Gaurang, additional, Milner, Kevin, additional, Okaya, David, additional, Small, Patrick, additional, and Vahi, Karan, additional

Published
2010
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46. Reducing Time-to-Solution Using Distributed High-Throughput Mega-Workflows - Experiences from SCEC CyberShake

Author

Callaghan, Scott, primary, Maechling, Philip, additional, Deelman, Ewa, additional, Vahi, Karan, additional, Mehta, Gaurang, additional, Juve, Gideon, additional, Milner, Kevin, additional, Graves, Robert, additional, Field, Edward, additional, Okaya, David, additional, Gunter, Dan, additional, Beattie, Keith, additional, and Jordan, Thomas, additional

Published
2008
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