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ENABLING DYNAMIC AND INTELLIGENT WORKFLOWS FOR HPC, DATA ANALYTICS AND AI CONVERGENCE

ENABLING DYNAMIC AND INTELLIGENT WORKFLOWS FOR HPC, DATA ANALYTICS AND AI CONVERGENCE

by eFlow4HPC | Jun 9, 2022 | Uncategorized

Eflows4HPC LAUNCHES ITS REFERENCE PUBLICATION

The publication focuses on the life cycle management of complex workflows that integrate HPC simulations with Data Analytics and AI algorithms. It includes use cases on climate modelling and the prototyping of complex manufactured objects.

Managing complex workflows with our first software stack release

Managing complex workflows with our first software stack release

by eFlow4HPC | Mar 30, 2022 | news, Uncategorized

First release of a set of integrated components to allow users to build and manage complex workflows. It provides the integration of TOSCA, PyCOMPs and Data Logistic Pipelines. Following the European Commission Open Source Software Strategy 2020-2023 to further...
Women in STEM interview series #1 – Rosa M. Badia

Women in STEM interview series #1 – Rosa M. Badia

by Luciana Marques | Mar 8, 2022 | Uncategorized

  Rosa M. Badia is the manager of the Workflows and Distributed computing group at the Barcelona Supercomputing Center (BSC) and the eFlows4HPC coordinator. She is also a lecturer at the Computer Architecture Department (DAC) at the Polytechnic University of Catalonia...
Towards dynamic workflows for Earth System Modelling and extreme events analysis

Towards dynamic workflows for Earth System Modelling and extreme events analysis

by eFlow4HPC | Feb 18, 2022 | Uncategorized

Earth System Models (ESM) simulations represent one of the most challenging HPC use cases due to very high computational cost, intensive Input/Output patterns, very large data volumes produced, and the necessity of post-processing them to distill knowledge and extract...
eFlows4HPC contributes to develop complex workflows for earthquakes

eFlows4HPC contributes to develop complex workflows for earthquakes

by Luciana Marques | Jan 28, 2022 | Uncategorized

 eflows4HPC supports the HPC CoE ChEESE by developing complex workflows for the geoscience community, in particular, for earthquakes. During last week, the ChEESE organized a live demo of the UCIS4EQ User Portal, an interface that has a particular interest for...
Building a framework for reduced order models for digital twins in manufacturing

Building a framework for reduced order models for digital twins in manufacturing

by eFlow4HPC | Oct 5, 2021 | Uncategorized

In the last decades, the level of accuracy of numerical simulations of physical assets within the manufacturing industry has allowed their throughout study and improvement.

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This project has received funding from the European High-Performance Computing Joint Undertaking (JU) under grant agreement No 955558. The JU receives support from the European Union’s Horizon 2020 research and innovation programme and Spain, Germany, France, Italy, Poland, Switzerland, Norway. All rights reserved. Legal Notice | Privacy Policy | Funding |