Grid workflows can be seen as special scientific workflows involving high performance and/or high throughput computational tasks. Much work in grid workflows has focused on improving application performance through schedulers that optimize the use of computational resources and bandwidth. As high-end computing resources are becoming more of a commodity that is available to new scientific communities, there is an increasing need to also improve the design and reusability "performance" of scientific workflow systems. To this end, a framework is developed that supports the design and reuse of grid workflows.
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