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Large-scale data-intensive streaming applications in various science fields feature complex DAG-structured workflows comprised of distributed computing modules with intricate inter-module dependencies. Supporting such workflows in high-performance network environments and optimizing their throughput are crucial to collaborative scientific exploration and discovery. We formulate workflow mapping as...
Supporting high-performance computing pipelines in wide-area networks is crucial to enabling large-scale distributed scientific applications that require minimizing end-to-end delay for fast user interaction or maximizing frame rate for smooth data flow. We formulate and categorize the linear pipeline configuration problems into six classes with two mapping objectives, i.e. minimum end-to-end delay...
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