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- W3203753634 abstract "Modern scientific workflows are increasing in complexity with growth in computation power, incorporation of non-traditional computation methods, and advances in technologies enabling data streaming to support on-the-fly computation. These workflows have unpredictable runtime behaviors, and a fixed, predetermined resource assignment on supercomputers can be inefficient for overall performance and throughput. Inability to change resource assignments further limits the scientists to avail of science-driven opportunities or respond to failures." @default.
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- W3203753634 date "2021-08-09" @default.
- W3203753634 modified "2023-09-23" @default.
- W3203753634 title "DYFLOW: A flexible framework for orchestrating scientific workflows on supercomputers" @default.
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- W3203753634 doi "https://doi.org/10.1145/3458744.3474037" @default.
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