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The correct definition and execution of scientific responsibilities depends not only on the legal framework.
The execution of scientific research in such facilities is considered to be a demanding secondary task.
Hence, proactive fault tolerance is required for the execution of scientific workflows.
Rodriguez and Buyya [95] propose a resource provisioning and scheduling solution for execution of scientific workflows on cloud infrastructures.
The execution of scientific codes will introdu ce a number of new challenges and intensify some old ones on new high-performance computing infrastructures.
We evaluate their applicability to more compute- and data-intensive scientific workflows and discuss possible ways to repurpose serverless architectures for execution of scientific workflows.
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While automated tuning is an established method for minimising the execution time of scientific applications, it has rarely been used for an automated minimisation of the energy consumption.
Firstly, the semantics of atomicity needs to be defined in a dataflow-oriented scientific workflow model, particularly for pipelined execution of hierarchical scientific workflows.
The latter is an important tool for the execution of the scientific objectives.
We propose a workflow system architecture which enforces QoS for the simultaneous execution of multiple scientific workflows over a shared infrastructure (such as a Cloud environment).
The first is based on our previous work, in particular the e-Science Life Cycle Ontology, which traces semantics about procedures a researcher is conducting during the execution of a scientific study.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com