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DTLMod: A simulation framework for in situ workflow optimization
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AI
DOI：10.1016/j.future.2026.108752.png)
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Abstract
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In situ processing workflows have become essential for coping with the explosion in data volume and velocity in large-scale scientific computing, providing domain scientists with early insights at runtime. Multiple frameworks implement this paradigm through a data transport layer (DTL), offering different data access modes and deployment schemes, but researchers currently lack the appropriate tools to assess design and deployment options before committing to costly real experiments.
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