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Decaf: Decoupled Dataflows for In Situ Workflows · Study

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ChapterDecaf: Decoupled Dataflows for In Situ Workflows

Orçun Yildiz2022

Chapter2022

Decaf: Decoupled Dataflows for In Situ Workflows

Orçun Yildiz · Matthieu Dreher · Tom Peterka

8 citations·0/0 files stored·Mathematics and visualization

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Scientific Computing and Data Management Parallel Computing and Optimization Techniques Distributed and Parallel Computing Systems

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References

2012Combining in-situ and in-transit processing to enable extreme-scale scientific analysis 2014A Flexible Framework for Asynchronous in Situ and in Transit Analytics for Scientific Simulations 2017Decaf: Decoupled Dataflows for In Situ High-Performance Workflows 2015Lessons Learned from Building In Situ Coupling Frameworks 2016Bredala: Semantic Data Redistribution for In Situ Applications 2011In-situ I/O processing

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2023Melissa: coordinating large-scale ensemble runs for deep learning and sensitivity analyses

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2017Automatic Data Filtering for In Situ Workflowsother · 4 shared references 2022Accelerating Scientific Workflows on HPC Platforms with In Situ Processingother · 3 shared references 2021DEISA: Dask-Enabled In Situ Analyticsother · 3 shared references 2016Optimal Execution of Co-analysis for Large-Scale Molecular Dynamics Simulationsother · 2 shared references 2021Exploring the Role of Machine Learning in Scientific Workflows: Opportunities and Challengespreprint · 2 shared references 2017The future of scientific workflowsarticle · 1 shared reference

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Year2022

Typechapter

Published2022-01-01

VenueMathematics and visualization

ISSN-L1612-3786

Languageen

Citations8

Files0 public / 0

ShelfScientific Computing and Data Management

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doi10.1007/978-3-030-81627-8_7

openalex_workW4285202005

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