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Artificial intelligence and grids: workflow planning and beyond
2004
IEEE Intelligent Systems
Grid computing is emerging as key enabling infrastructure for science. A key challenge for distributed computation over the Grid is the synthesis on-demand of end-toend scientific applications of unprecedented scale that draw from pools of specialized scientific components to derive elaborate new results. In this paper, we outline the technical issues that need to be addressed in order to meet this challenge, including usability, robustness, and scale. We describe Pegasus, a system to generate
doi:10.1109/mis.2004.1265882
fatcat:p6ekxvjr2jcg7cenoi2gl6652q