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A Run-time System for Efficient Execution of Scientific Workflows on Distributed Environments.

George Teodoro¹, Tulio Tavares, Renato Ferreira

¹Department of Computer Science, Universidade Federal de Minas Gerais, 31270-010 Belo Horizonte, MG - Brazil, tel +55(31)3499-5860 - fax +55(31)3499-5858.

International Journal of Parallel Programming

|May 15, 2012

Summary

This summary is machine-generated.

This study introduces a new runtime system for scientific workflow systems, optimizing data-intensive computations in distributed environments. The system achieves linear speedups for complex data analysis applications, enhancing research efficiency.

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Area of Science:

Computational science
Data science
Scientific computing

Background:

Increasingly large datasets necessitate advanced scientific workflow systems.
Data analysis applications are often structured as computational pipelines or networks.
Distributed computing environments present unique challenges for data-intensive tasks.

Purpose of the Study:

To present a novel runtime support system for scientific workflow systems.
To optimize the execution of data-intensive workflows in distributed environments.
To address critical issues in data management, processing, and movement.

Main Methods:

Development of a runtime support system tailored for data-intensive scientific workflows.
Implementation of efficient data management, retrieval, and movement strategies.
Integration of check-pointing mechanisms for intermediate results.

Main Results:

The system demonstrates optimized performance for data-intensive workflows.
Efficient management and coordination of data processing and movement are achieved.
Experimental evaluation shows linear speedups for sophisticated, multi-component applications.

Conclusions:

The developed runtime system effectively supports complex data-intensive scientific workflows.
Linear speedups are attainable for sophisticated applications in distributed computing.
The system enhances the efficiency and scalability of scientific data analysis.