The Experts below are selected from a list of 78033 Experts worldwide ranked by ideXlab platform

Kenneth Chiu - One of the best experts on this subject based on the ideXlab platform.

  • a grid workflow environment for brain imaging analysis on distributed systems
    Concurrency and Computation: Practice and Experience, 2009
    Co-Authors: Suraj Pandey, William Voorsluys, Rajkumar Buyya, James E. Dobson, Mustafizur Rahman, Kenneth Chiu
    Abstract:

    Scientific Applications like neuroscience data analysis are usually compute and data-intensive. With the use of the additional capacity offered by distributed resources and suitable middlewares, we can achieve much shorter execution time, distribute compute and storage load, and add greater flexibility to the execution of these scientific Applications than we could ever achieve in a single compute resource. In this paper, we present the processing of image registration (IR) for functional magnetic resonance imaging studies on Global Grids. We characterize the Application, List its requirements and then transform it to a workflow. We use Gridbus Broker and Gridbus Workflow Engine technologies for executing the neuroscience Application on the Grid. We developed a complete web-based portal integrating GUI-based workflow editor, execution management, monitoring and visualization of tasks and resources. We describe each component of the system in detail. We then execute the Application on Grid'5000 platform and present extensive performance results. We show that the IR Application can have (1) significantly improved makespan, (2) distribution of compute and storage load among resources used, and (3) flexibility when executing multiple times on Grid resources. Copyright © 2009 John Wiley & Sons, Ltd.

  • Brain Image Registration Analysis Workflow for fMRI Studies on Global Grids
    2009
    Co-Authors: Suraj Pandey, William Voorsluys, Rajkumar Buyya, James Dobson, Kenneth Chiu
    Abstract:

    Scientific Applications like neuroscience data analysis are usually compute and data-intensive. With the use of globally distributed resources and suitable middlewares, we can achieve much shorter execution time, distribute compute and storage load, and add greater flexibility to the execution of these scientific Applications than we could ever achieve in a single compute resource.In this paper, we present the processing of image registration (IR) for functional magnetic resonance imaging(fMRI) studies on global grids. We characterize the Application, List its requirements and transform it to a workflow. We then execute the Application on Gridpsila5000 platform and present extensive performance results. We show that the IR Application can have 1) significantly improved makespan, 2) distribution of compute and storage load among resources used, and 3) flexibility when executing multiple times on global Grids.

  • AINA - Brain Image Registration Analysis Workflow for fMRI Studies on Global Grids
    2009 International Conference on Advanced Information Networking and Applications, 2009
    Co-Authors: Suraj Pandey, William Voorsluys, Musta Zur Rahman, Rajkumar Buyya, James E. Dobson, Kenneth Chiu
    Abstract:

    Scientific Applications like neuroscience data analysis are usually compute and data-intensive. With the use of globally distributed resources and suitable middlewares, we can achieve much shorter execution time, distribute compute and storage load, and add greater flexibility to the execution of these scientific Applications than we could ever achieve in a single compute resource.In this paper, we present the processing of Image Registration (IR) for Functional Magnetic Resonance Imaging(fMRI) studies on global Grids. We characterize the Application, List its requirements and transform it to a workflow. We then execute the Application on Grid’5000 platform and present extensive performance results. We show that the IR Application can have 1) significantly improved makespan, 2) distribution of compute and storage load among resources used, and 3) flexibility when executing multiple times on global Grids.

Suraj Pandey - One of the best experts on this subject based on the ideXlab platform.

  • a grid workflow environment for brain imaging analysis on distributed systems
    Concurrency and Computation: Practice and Experience, 2009
    Co-Authors: Suraj Pandey, William Voorsluys, Rajkumar Buyya, James E. Dobson, Mustafizur Rahman, Kenneth Chiu
    Abstract:

    Scientific Applications like neuroscience data analysis are usually compute and data-intensive. With the use of the additional capacity offered by distributed resources and suitable middlewares, we can achieve much shorter execution time, distribute compute and storage load, and add greater flexibility to the execution of these scientific Applications than we could ever achieve in a single compute resource. In this paper, we present the processing of image registration (IR) for functional magnetic resonance imaging studies on Global Grids. We characterize the Application, List its requirements and then transform it to a workflow. We use Gridbus Broker and Gridbus Workflow Engine technologies for executing the neuroscience Application on the Grid. We developed a complete web-based portal integrating GUI-based workflow editor, execution management, monitoring and visualization of tasks and resources. We describe each component of the system in detail. We then execute the Application on Grid'5000 platform and present extensive performance results. We show that the IR Application can have (1) significantly improved makespan, (2) distribution of compute and storage load among resources used, and (3) flexibility when executing multiple times on Grid resources. Copyright © 2009 John Wiley & Sons, Ltd.

  • Brain Image Registration Analysis Workflow for fMRI Studies on Global Grids
    2009
    Co-Authors: Suraj Pandey, William Voorsluys, Rajkumar Buyya, James Dobson, Kenneth Chiu
    Abstract:

    Scientific Applications like neuroscience data analysis are usually compute and data-intensive. With the use of globally distributed resources and suitable middlewares, we can achieve much shorter execution time, distribute compute and storage load, and add greater flexibility to the execution of these scientific Applications than we could ever achieve in a single compute resource.In this paper, we present the processing of image registration (IR) for functional magnetic resonance imaging(fMRI) studies on global grids. We characterize the Application, List its requirements and transform it to a workflow. We then execute the Application on Gridpsila5000 platform and present extensive performance results. We show that the IR Application can have 1) significantly improved makespan, 2) distribution of compute and storage load among resources used, and 3) flexibility when executing multiple times on global Grids.

  • AINA - Brain Image Registration Analysis Workflow for fMRI Studies on Global Grids
    2009 International Conference on Advanced Information Networking and Applications, 2009
    Co-Authors: Suraj Pandey, William Voorsluys, Musta Zur Rahman, Rajkumar Buyya, James E. Dobson, Kenneth Chiu
    Abstract:

    Scientific Applications like neuroscience data analysis are usually compute and data-intensive. With the use of globally distributed resources and suitable middlewares, we can achieve much shorter execution time, distribute compute and storage load, and add greater flexibility to the execution of these scientific Applications than we could ever achieve in a single compute resource.In this paper, we present the processing of Image Registration (IR) for Functional Magnetic Resonance Imaging(fMRI) studies on global Grids. We characterize the Application, List its requirements and transform it to a workflow. We then execute the Application on Grid’5000 platform and present extensive performance results. We show that the IR Application can have 1) significantly improved makespan, 2) distribution of compute and storage load among resources used, and 3) flexibility when executing multiple times on global Grids.

William Voorsluys - One of the best experts on this subject based on the ideXlab platform.

  • a grid workflow environment for brain imaging analysis on distributed systems
    Concurrency and Computation: Practice and Experience, 2009
    Co-Authors: Suraj Pandey, William Voorsluys, Rajkumar Buyya, James E. Dobson, Mustafizur Rahman, Kenneth Chiu
    Abstract:

    Scientific Applications like neuroscience data analysis are usually compute and data-intensive. With the use of the additional capacity offered by distributed resources and suitable middlewares, we can achieve much shorter execution time, distribute compute and storage load, and add greater flexibility to the execution of these scientific Applications than we could ever achieve in a single compute resource. In this paper, we present the processing of image registration (IR) for functional magnetic resonance imaging studies on Global Grids. We characterize the Application, List its requirements and then transform it to a workflow. We use Gridbus Broker and Gridbus Workflow Engine technologies for executing the neuroscience Application on the Grid. We developed a complete web-based portal integrating GUI-based workflow editor, execution management, monitoring and visualization of tasks and resources. We describe each component of the system in detail. We then execute the Application on Grid'5000 platform and present extensive performance results. We show that the IR Application can have (1) significantly improved makespan, (2) distribution of compute and storage load among resources used, and (3) flexibility when executing multiple times on Grid resources. Copyright © 2009 John Wiley & Sons, Ltd.

  • Brain Image Registration Analysis Workflow for fMRI Studies on Global Grids
    2009
    Co-Authors: Suraj Pandey, William Voorsluys, Rajkumar Buyya, James Dobson, Kenneth Chiu
    Abstract:

    Scientific Applications like neuroscience data analysis are usually compute and data-intensive. With the use of globally distributed resources and suitable middlewares, we can achieve much shorter execution time, distribute compute and storage load, and add greater flexibility to the execution of these scientific Applications than we could ever achieve in a single compute resource.In this paper, we present the processing of image registration (IR) for functional magnetic resonance imaging(fMRI) studies on global grids. We characterize the Application, List its requirements and transform it to a workflow. We then execute the Application on Gridpsila5000 platform and present extensive performance results. We show that the IR Application can have 1) significantly improved makespan, 2) distribution of compute and storage load among resources used, and 3) flexibility when executing multiple times on global Grids.

  • AINA - Brain Image Registration Analysis Workflow for fMRI Studies on Global Grids
    2009 International Conference on Advanced Information Networking and Applications, 2009
    Co-Authors: Suraj Pandey, William Voorsluys, Musta Zur Rahman, Rajkumar Buyya, James E. Dobson, Kenneth Chiu
    Abstract:

    Scientific Applications like neuroscience data analysis are usually compute and data-intensive. With the use of globally distributed resources and suitable middlewares, we can achieve much shorter execution time, distribute compute and storage load, and add greater flexibility to the execution of these scientific Applications than we could ever achieve in a single compute resource.In this paper, we present the processing of Image Registration (IR) for Functional Magnetic Resonance Imaging(fMRI) studies on global Grids. We characterize the Application, List its requirements and transform it to a workflow. We then execute the Application on Grid’5000 platform and present extensive performance results. We show that the IR Application can have 1) significantly improved makespan, 2) distribution of compute and storage load among resources used, and 3) flexibility when executing multiple times on global Grids.

Rajkumar Buyya - One of the best experts on this subject based on the ideXlab platform.

  • a grid workflow environment for brain imaging analysis on distributed systems
    Concurrency and Computation: Practice and Experience, 2009
    Co-Authors: Suraj Pandey, William Voorsluys, Rajkumar Buyya, James E. Dobson, Mustafizur Rahman, Kenneth Chiu
    Abstract:

    Scientific Applications like neuroscience data analysis are usually compute and data-intensive. With the use of the additional capacity offered by distributed resources and suitable middlewares, we can achieve much shorter execution time, distribute compute and storage load, and add greater flexibility to the execution of these scientific Applications than we could ever achieve in a single compute resource. In this paper, we present the processing of image registration (IR) for functional magnetic resonance imaging studies on Global Grids. We characterize the Application, List its requirements and then transform it to a workflow. We use Gridbus Broker and Gridbus Workflow Engine technologies for executing the neuroscience Application on the Grid. We developed a complete web-based portal integrating GUI-based workflow editor, execution management, monitoring and visualization of tasks and resources. We describe each component of the system in detail. We then execute the Application on Grid'5000 platform and present extensive performance results. We show that the IR Application can have (1) significantly improved makespan, (2) distribution of compute and storage load among resources used, and (3) flexibility when executing multiple times on Grid resources. Copyright © 2009 John Wiley & Sons, Ltd.

  • Brain Image Registration Analysis Workflow for fMRI Studies on Global Grids
    2009
    Co-Authors: Suraj Pandey, William Voorsluys, Rajkumar Buyya, James Dobson, Kenneth Chiu
    Abstract:

    Scientific Applications like neuroscience data analysis are usually compute and data-intensive. With the use of globally distributed resources and suitable middlewares, we can achieve much shorter execution time, distribute compute and storage load, and add greater flexibility to the execution of these scientific Applications than we could ever achieve in a single compute resource.In this paper, we present the processing of image registration (IR) for functional magnetic resonance imaging(fMRI) studies on global grids. We characterize the Application, List its requirements and transform it to a workflow. We then execute the Application on Gridpsila5000 platform and present extensive performance results. We show that the IR Application can have 1) significantly improved makespan, 2) distribution of compute and storage load among resources used, and 3) flexibility when executing multiple times on global Grids.

  • AINA - Brain Image Registration Analysis Workflow for fMRI Studies on Global Grids
    2009 International Conference on Advanced Information Networking and Applications, 2009
    Co-Authors: Suraj Pandey, William Voorsluys, Musta Zur Rahman, Rajkumar Buyya, James E. Dobson, Kenneth Chiu
    Abstract:

    Scientific Applications like neuroscience data analysis are usually compute and data-intensive. With the use of globally distributed resources and suitable middlewares, we can achieve much shorter execution time, distribute compute and storage load, and add greater flexibility to the execution of these scientific Applications than we could ever achieve in a single compute resource.In this paper, we present the processing of Image Registration (IR) for Functional Magnetic Resonance Imaging(fMRI) studies on global Grids. We characterize the Application, List its requirements and transform it to a workflow. We then execute the Application on Grid’5000 platform and present extensive performance results. We show that the IR Application can have 1) significantly improved makespan, 2) distribution of compute and storage load among resources used, and 3) flexibility when executing multiple times on global Grids.

James E. Dobson - One of the best experts on this subject based on the ideXlab platform.

  • a grid workflow environment for brain imaging analysis on distributed systems
    Concurrency and Computation: Practice and Experience, 2009
    Co-Authors: Suraj Pandey, William Voorsluys, Rajkumar Buyya, James E. Dobson, Mustafizur Rahman, Kenneth Chiu
    Abstract:

    Scientific Applications like neuroscience data analysis are usually compute and data-intensive. With the use of the additional capacity offered by distributed resources and suitable middlewares, we can achieve much shorter execution time, distribute compute and storage load, and add greater flexibility to the execution of these scientific Applications than we could ever achieve in a single compute resource. In this paper, we present the processing of image registration (IR) for functional magnetic resonance imaging studies on Global Grids. We characterize the Application, List its requirements and then transform it to a workflow. We use Gridbus Broker and Gridbus Workflow Engine technologies for executing the neuroscience Application on the Grid. We developed a complete web-based portal integrating GUI-based workflow editor, execution management, monitoring and visualization of tasks and resources. We describe each component of the system in detail. We then execute the Application on Grid'5000 platform and present extensive performance results. We show that the IR Application can have (1) significantly improved makespan, (2) distribution of compute and storage load among resources used, and (3) flexibility when executing multiple times on Grid resources. Copyright © 2009 John Wiley & Sons, Ltd.

  • AINA - Brain Image Registration Analysis Workflow for fMRI Studies on Global Grids
    2009 International Conference on Advanced Information Networking and Applications, 2009
    Co-Authors: Suraj Pandey, William Voorsluys, Musta Zur Rahman, Rajkumar Buyya, James E. Dobson, Kenneth Chiu
    Abstract:

    Scientific Applications like neuroscience data analysis are usually compute and data-intensive. With the use of globally distributed resources and suitable middlewares, we can achieve much shorter execution time, distribute compute and storage load, and add greater flexibility to the execution of these scientific Applications than we could ever achieve in a single compute resource.In this paper, we present the processing of Image Registration (IR) for Functional Magnetic Resonance Imaging(fMRI) studies on global Grids. We characterize the Application, List its requirements and transform it to a workflow. We then execute the Application on Grid’5000 platform and present extensive performance results. We show that the IR Application can have 1) significantly improved makespan, 2) distribution of compute and storage load among resources used, and 3) flexibility when executing multiple times on global Grids.