HPC Application Cloudification: The StreamFlow Toolkit (Invited Paper)

Authors Iacopo Colonnelli , Barbara Cantalupo , Roberto Esposito , Matteo Pennisi , Concetto Spampinato , Marco Aldinucci

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Iacopo Colonnelli
  • Computer Science Department, University of Torino, Italy
Barbara Cantalupo
  • Computer Science Department, University of Torino, Italy
Roberto Esposito
  • Computer Science Department, University of Torino, Italy
Matteo Pennisi
  • Electrical Engineering Department, University of Catania, Italy
Concetto Spampinato
  • Electrical Engineering Department, University of Catania, Italy
Marco Aldinucci
  • Department of Computer Science, University of Pisa, Italy


We want to thank Emanuela Girardi and Gianluca Bontempi who are coordinating the CLAIRE task force on COVID-19 for their support, and the group of volunteer researchers who contributed to the development of CLAIRE COVID-19 universal pipeline, they are: Marco Calandri and Piero Fariselli (Radiomics & medical science, University of Torino, Italy); Marco Grangetto, Enzo Tartaglione (Digital image processing Lab, University of Torino, Italy); Simone Palazzo, Isaak Kavasidis (PeRCeiVe Lab, University of Catania, Italy); Bogdan Ionescu, Gabriel Constantin (Multimedia Lab @ CAMPUS Research Institute, University Politechnica of Bucharest, Romania); Miquel Perello Nieto (Computer Science, University of Bristol, UK); Inês Domingues (School of Sciences University of Porto, Portugal).

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Iacopo Colonnelli, Barbara Cantalupo, Roberto Esposito, Matteo Pennisi, Concetto Spampinato, and Marco Aldinucci. HPC Application Cloudification: The StreamFlow Toolkit (Invited Paper). In 12th Workshop on Parallel Programming and Run-Time Management Techniques for Many-core Architectures and 10th Workshop on Design Tools and Architectures for Multicore Embedded Computing Platforms (PARMA-DITAM 2021). Open Access Series in Informatics (OASIcs), Volume 88, pp. 5:1-5:13, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)


Finding an effective way to improve accessibility to High-Performance Computing facilities, still anchored to SSH-based remote shells and queue-based job submission mechanisms, is an open problem in computer science. This work advocates a cloudification of HPC applications through a cluster-as-accelerator pattern, where computationally demanding portions of the main execution flow hosted on a Cloud Finding an effective way to improve accessibility to High-Performance Computing facilities, still anchored to SSH-based remote shells and queue-based job submission mechanisms, is an open problem in computer science. This work advocates a cloudification of HPC applications through a cluster-as-accelerator pattern, where computationally demanding portions of the main execution flow hosted on a Cloud infrastructure can be offloaded to HPC environments to speed them up. We introduce StreamFlow, a novel Workflow Management System that supports such a design pattern and makes it possible to run the steps of a standard workflow model on independent processing elements with no shared storage. We validated the proposed approach’s effectiveness on the CLAIRE COVID-19 universal pipeline, i.e. a reproducible workflow capable of automating the comparison of (possibly all) state-of-the-art pipelines for the diagnosis of COVID-19 interstitial pneumonia from CT scans images based on Deep Neural Networks (DNNs).

Subject Classification

ACM Subject Classification
  • Computer systems organization → Cloud computing
  • Computing methodologies → Distributed computing methodologies
  • cloud computing
  • distributed computing
  • high-performance computing
  • streamflow
  • workflow management systems


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