| Posters | Poster-2019-942 |
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Support for HTCondor High-Throughput Computing Workflows in the REANA Reusable Analysis Platform |
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Creator(s): Maciulaitis, Rokas; Bremer, Paul; Hampton, Scott; Hildreth, Mike; Hurtado Anampa, Kenyi Paolo; Johnson, Irena Nona; Kankel, Cody; Okraska, Jan; Rodriguez Rodriguez, Diego; Simko, Tibor Created: 2019 Number of pages: 1 p Email: rokas.maciulaitis@cern.ch REANA is a reusable and reproducible data analysis platform allowing researchers to structure their analysis pipelines and run them on remote containerised compute clouds. REANA supports several different workflows systems (CWL, Serial, Yadage) and uses Kubernetes’ job execution backend. We have designed an abstract job execution component that extends the REANA platform job execution capabilities to support multiple compute backends. We have tested the abstract job execution component with HTCondor and verified the scalability of the designed solution. The results show that the REANA platform would be able to support hybrid scientific workflows where different parts of the analysis pipelines can be executed on multiple computing backends. Keywords: reproducible science computational workflows high-throughput computing high-performance computing data analysis Related links: eScience 2019 Poster Session
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Submitted by rokas.maciulaitis@cern.ch |
Access to files: PDF |
Record created 2019-10-22, last modified 2019-10-24