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Enregistrement W6912680732 · doi:10.5281/zenodo.7461705

D4.1: Interim PRACE Training Report

2020· article· en· W6912680732 sur OpenAlexaboutno aff

Notice bibliographique

RevueZenodo (CERN European Organization for Nuclear Research) · 2020
Typearticle
Langueen
DomaineComputer Science
ThématiqueOnline Learning and Analytics
Établissements canadiensnon disponible
Organismes subventionnairesHorizon 2020 Framework Programme
Mots-clésDeliverableTraining (meteorology)InterimSummitWork (physics)Pandemic

Résumé

récupéré en direct d'OpenAlex

The Training Work Package (WP4) of the PRACE-6IP project is responsible for the design and execution of a comprehensive range of HPC training activities. This includes an extensive, annual programme of short courses that are delivered by a network of now 14 PRACE Training Centres (PTCs), a series of Seasonal Schools, on-demand events, Massive Open Online Courses (MOOCs) which are underpinned by the PRACE Training Portal. This deliverable is the interim, mid-term report of all PRACE-6IP training activities up to Month 18 of the project. The COVID-19 pandemic has had an obvious effect on training activities, in particular face-to-face courses and schools that are no longer feasible due to travel and social distancing restrictions. While this had caused disruptions and the postponement and cancellations of some 20+ events (PTC courses, a Seasonal School, the 2019 International HPC Summer School, the EuroHPC Summit Week 2020 hands-on workshops), there has been a quick pivot to providing courses online. Since the onset of the pandemic in March 2019, WP4 had still managed to deliver 29 PTC courses and the PRACE Autumn School 2020 online, not the mention converting the PRACE Summer of HPC into a virtual mentoring programme and continuing the Massive Open Online Courses (MOOCs). The network of PTCs has expanded by four new members (from Austria, Belgium, Slovenia and Sweden) in late 2019 for a total of 14 partners who are involved in delivering an annual joint programme of courses. From May 2019 to September 2020, the PTCs have collectively delivered 119 courses, representing 326 days of training with 3,549 participants. This includes the 2019-2020 PTC programme in which almost a quarter of its courses had to be delivered online. As trainers continue to learn and improve the online learning experience, indications are that online courses have proven to be attractive to participants from all over Europe including non-PTC hosting countries. These lessons will be brought into the 2020-2021 programme with a target of 138 courses, representing 338 training days. WP4 had targeted the delivery of eight Seasonal Schools during the course of the PRACE-6IP project. The first PRACE Autumn School in 2019 was held in Slovenia organised in a fast-tracked manner. While the schedule of Seasonal Schools, including location and organising partners, were finalised by early 2020, the COVID-19 pandemic caused the 2020 PRACE Winter School in Austria to be aborted after its first day. The subsequent 2020 Autumn School in Slovenia was successfully delivered in a hybrid face-to-face and online format. Therefore, two Seasonal Schools have been fully delivered with a total of 128 participants. A modified schedule is being finalised for delivery of remaining Seasonal Schools in 2021. Apart from Seasonal Schools, two on-demand events have been held in 2019 that involved collaborations with the EUDAT and the BioExcel CoE projects. Meanwhile, WP4 has co-organised another successful International HPC Summer School 2019, in collaboration with partners from Canada, Japan and the U.S., which was held in Kobe, Japan in July 2019, with 80 participants including 30 from Europe. The 2020 International HPC Summer School was planned to take place in Toronto, July 2020 but has been cancelled due to the COVID-19 pandemic; the event is being rescheduled to 2021 in the same venue. Plans are ongoing to organise an advanced PRACE extreme-scale workshop, taught by a pool of instructors from PRACE partners, in 2021. The PRACE Summer of HPC programme, where European students are mentored by HPC experts across participating PRACE partner sites, hosted 25 projects for 25 visiting students at HPC centres in 2019. While travel restrictions in summer 2020 had looked to curtail this programme in 2020, WP4 managed to transform it into a remote mentoring programme where 50 students partnered up to partake in 25 projects across HPC partners. With the addition of another new MOOC developed by WP4, PRACE now has a repertoire of six MOOCs that are being run on the FutureLearn platform on a periodic basis. During the first half of the project, 5 MOOCs were delivered across 8 instances (i.e. some repeat runs of the same MOOC), which had attracted a total of 7,475 active learners (16,568 enrolments). Development of new MOOCs are planned for the second half of the project. Training collaboration has always been an important aspect of PRACE. WP4 has engaged with a variety of external projects and research infrastructures to identify potential synergistic activities. Some of the engagements so far include the planning of joint training event with RedCLARA (South America), potential joint activities with CERN / GÉANT / SKA and working with FocusCoE and CASTIEL to ensure alignment in activities and providing a platform for exchange of ideas and best practices. New approaches to develop basic training materials are being investigated with the intention to contribute towards the collaborative efforts of HPC Carpentry. Finally, the PRACE Training Portal and Events Portal have been updated and improved with new functionalities to improve the user experience. The Training Portal underwent a redesign to be consistent with the main PRACE web site, with the adoption of a new events registry system with additional metadata that makes it easier for users to identify relevant courses.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,011
score de la tête « metaresearch » (Gemma)0,016
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesCharge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Autre · Signal consensuel: Autre
Score de désaccord entre enseignants0,318
Score d'incertitude au seuil0,973

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0110,016
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0000,001
Bibliométrie0,0030,002
Études des sciences et des technologies0,0020,001
Communication savante0,0050,003
Science ouverte0,0030,005
Intégrité de la recherche0,0020,003
Charge utile insuffisante (le modèle a refusé de juger)0,3180,240

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,092
Tête enseignante GPT0,292
Écart entre enseignants0,200 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Devis d'étudeSans objet
Domainenon disponible
GenreAutre

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2020
Routes d'admission1
Résumé présentoui

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