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Streaming I/O for scientific workflow engine acceleration
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DOI：10.1016/j.future.2025.107978.png)
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Abstract
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• Integration of memory-based streaming I/O in workflow engines. • Auto-generation of sync rules via DAGonStar dependency analysis. • Faster pipeline task execution via CAPIO system call interception. • Benchmark shows up to 33% execution time reduction with DAGonCAPIO. • Support for local batch and SLURM-based distributed runs.
Keywords:
High-performance computing
Workflow optimization
Scientific workflows
Streaming I/O
In-memory file systems
File-based pipeline acceleration
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