Descrizione del progetto
Un flusso di lavoro intelligente per ecosistemi di calcolo ad alte prestazioni
La proliferazione dell’uso di computer, elettronica e Internet delle cose, richiede sviluppo e innovazione ulteriori nell’ambito dell’informatica e del calcolo ad alte prestazioni. Per superare le attuali sfide degli ecosistemi di calcolo ad alte prestazioni e spianare la strada a una maggiore innovazione, il progetto eFlows4HPC, finanziato dall’UE, affronterà la mancanza di strumenti necessari allo sviluppo di flussi di lavoro complessi riguardanti il calcolo ad alte prestazioni. Esso fornirà una metodologia che amplia e agevola l’impiego di flussi di lavoro da parte di comunità di calcolo esistenti e nuove, ovvero flussi di lavoro di calcolo ad alte prestazioni come servizio. Ciò comprenderà un software di flusso di lavoro e diversi servizi che permetteranno l’applicazione efficiente di simulazioni, modellizzazione, apprendimento automatico e analisi di megadati basati sul calcolo ad alte prestazioni nel settore scientifico e industriale.
Obiettivo
Today, developers lack tools that enable the development of complex workflows involving HPC simulation and modelling with data analytics (DA) and machine learning (ML). TheFlows4HPC aims to deliver a workflow software stack and an additional set of services to enable the integration of HPC simulation and modelling with big data analytics and machine learning in scientific and industrial applications. The software stack will allow to develop innovative adaptive workflows that efficiently use the computing resources and also considering innovative storage solutions.
To widen the access to HPC to newcomers, the project will provide HPC Workflows as a Service (HPCWaaS), an environment for sharing, reusing, deploying and executing existing workflows on HPC systems. The workflow technologies, associated machine learning and big data libraries used in the project leverages previous open source European initiatives. Specific optimization tasks for the use of accelerators (FPGAs, GPUs) and the EPI will be performed in the project use cases.
To demonstrate the workflow software stack, use cases from three thematic pillars have been selected. Pillar I 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. Pillar II 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. Pillar III explores the modelling of natural catastrophes - in particular, earthquakes and their associated tsunamis- shortly after such an event is recorded. Leveraging two existing workflows, the Pillar will work of integrating them with the eFlows4HPC software stack and on producing policies for urgent access to supercomputers. The pillar results will be demonstrated in the target community CoEs to foster adoption and get feedback.
Campo scientifico
- natural sciencescomputer and information sciencessoftware
- natural sciencescomputer and information sciencesdata sciencebig data
- natural sciencesearth and related environmental sciencesgeologyseismology
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringcomputer hardwaresupercomputers
- natural sciencescomputer and information sciencesartificial intelligencemachine learning
Parole chiave
Programma(i)
Meccanismo di finanziamento
IA - Innovation actionCoordinatore
08034 Barcelona
Spagna