eFlows4HPC
eFlows4HPC project aims at providing workflow software stack and an additional set of services to enable the integration of HPC simulations and modelling with big data analytics and machine learning in scientific and industrial applications. The project is also developing the HPC Workflows as a Service (HPCWaaS) methodology that aims at providing tools to simplify the development, deployment, execution and reuse of workflows. The project demonstrates its advances through three application Pillars with high industrial and social relevance: manufacturing, climate and urgent computing for natural hazards; these applications will help to prove how the realization of forthcoming efficient HPC and data-centric applications can be developed with new workflow technologies.
Web page: https://eflows4hpc.eu
Funding codes:- 955558
- MCIN/AEI/10.13039/501100011033 and the European Union NextGenerationEU/PRTR (PCI2021-121957)
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.
Related items
Teams: eFlows4HPC general
Organizations: Barcelona Supercomputing Center (BSC-CNS)
https://orcid.org/0000-0003-0790-1832
Teams: Cluster Emergent del Cervell Humà, Workflows and Distributed Computing, WP6 - Tsunamis, WP7 - Earthquakes, WP8 - Anthropogenic geophysical extremes, WP5 - Volcanoes, Pillar I: Manufacturing, Pillar II: Climate, Pillar III: Urgent computing for natural hazards, eFlows4HPC general
Organizations: Barcelona Supercomputing Center (BSC-CNS)
https://orcid.org/0000-0003-0606-2512
Established Researcher at Workflows and Distributed Computing Group, Computer Sciences department, Barcelona Supercomputing Center.
It focuses on the construction of DigitalTwins for the prototyping of complex manufactured objects integrating state-of-the-art adaptive solvers with machine learning and data-mining, contributing to the Industry 4.0 vision.
Space: eFlows4HPC
Public web page: https://eflows4hpc.eu/pillars/
It develops innovative adaptive workflows for climate and for the study of Tropical Cyclones (TC) in the context of the CMIP6 experiment, including in-situ analytics.
Space: eFlows4HPC
Public web page: https://eflows4hpc.eu/pillars/
This team is to publish workflows executed from WPs that are not the three main pillars of the project.
Space: eFlows4HPC
Public web page: https://eflows4hpc.eu/
It explores the modelling of natural catastrophes – in particular, earthquakes and their associated tsunamis shortly after such an event is recorded.
Space: eFlows4HPC
Public web page: https://eflows4hpc.eu/pillars/
Distributed computing aims to offer tools and mechanisms that enable the sharing, selection, and aggregation of a wide variety of geographically distributed computational resources in a transparent way. The research done in this team is based on the past expertise of the group, and on extending it towards the aspects of distributed computing that can benefit from this expertise. The team at BSC has a strong focus on programming models and resource management and scheduling in distributed computing ...
Project that aims to create the NeuroPlat portal for neurodrug design
Space: eFlows4HPC
Public web page: https://www.upf.edu/web/cech
Abstract (Expand)
Authors: Raul Sirvent, Javier Conejero, Francesc Lordan, Jorge Ejarque, Laura Rodriguez-Navas, Jose M. Fernandez, Salvador Capella-Gutierrez, Rosa M. Badia
Date Published: 1st Nov 2022
Publication Type: Proceedings
Provenance registration is becoming more and more important, as we increase the size and number of experiments performed using computers. In particular, when provenance is recorded in HPC environments, it must be efficient and scalable. In this paper, we propose a provenance registration method for scientific workflows, efficient enough to run in supercomputers (thus, it could run in other environments with more relaxed restrictions, such as distributed ones). It also must be scalable in order ...
Creator: Raül Sirvent
Submitter: Raül Sirvent
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Sample workflow template that combines simulations with data analytics. It is not a real workflow, but it mimics this type of workflows. It illustrates how COMPSs invokes binaries. It can be extended to invoke MPI applications.
BackTrackBB is a program for detection and space-time location of seismic sources based on multi-scale, frequency-selective statistical coherence of the wave field recorded by dense large-scale seismic networks and local antennas. The method is designed to enhance coherence of the signal statistical features across the array of sensors and consists of three steps. They are signal processing, space-time imaging and detection and location.
Source with inputs and outputs included (too big for ...
Detailed description of your COMPSs application
Name: SparseLU Contact Person: support-compss@bsc.es Access Level: public License Agreement: Apache2 Platform: COMPSs
Description
The Sparse LU application computes an LU matrix factorization on a sparse blocked matrix. The matrix size (number of blocks) and the block size are parameters of the application.
As the algorithm progresses, the area of the matrix that is accessed is smaller; concretely, at each iteration, the 0th row and column of the current matrix are discarded. ...
Name: Matrix multiplication with Files Contact Person: support-compss@bsc.es Access Level: public License Agreement: Apache2 Platform: COMPSs
Description
Matrix multiplication is a binary operation that takes a pair of matrices and produces another matrix.
If A is an n×m matrix and B is an m×p matrix, the result AB of their multiplication is an n×p matrix defined only if the number of columns m in A is equal to the number of rows m in B. When multiplying A and B, the elements ...
Name: Matrix Multiplication Contact Person: support-compss@bsc.es Access Level: public License Agreement: Apache2 Platform: COMPSs
Description
Matrix multiplication is a binary operation that takes a pair of matrices and produces another matrix.
If A is an n×m matrix and B is an m×p matrix, the result AB of their multiplication is an n×p matrix defined only if the number of columns m in A is equal to the number of rows m in B. When multiplying A and B, the elements of the ...
Lysozyme in Water simplest version, from COMPSs Tutorial. The original idea of this worklfow comes from http://www.mdtutorials.com/gmx/lysozyme/index.html
