Scalable adaptive optimizations for stream-based workflows in multi-HPC-clusters and cloud infrastructures-Reference-Cited by-同舟云学术

Scalable adaptive optimizations for stream-based workflows in multi-HPC-clusters and cloud infrastructures

Author:

Liang Liang^ORCID,Filgueira Rosa^ORCID,Yan Yan,Heinis Thomas

Publisher

Elsevier BV

Subject

Computer Networks and Communications,Hardware and Architecture,Software

Reference36 articles.

2. The future of scientific workflows;Deelman;Int. J. High Perform. Comput. Appl.,2018

3. Scientific workflows: Past, present and future;Atkinson,2017

4. The world beyond batch: Streaming 101, A high-level tour of modern data-processing concepts;Akidau,2015

5. dispel4py: A Python framework for data-intensive scientific computing;Filgueira;Int. J. High Perform. Comput. Appl.,2016

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