{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,23]],"date-time":"2025-06-23T08:27:44Z","timestamp":1750667264286},"reference-count":23,"publisher":"Springer Science and Business Media LLC","issue":"10","license":[{"start":{"date-parts":[[2023,2,15]],"date-time":"2023-02-15T00:00:00Z","timestamp":1676419200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2023,2,15]],"date-time":"2023-02-15T00:00:00Z","timestamp":1676419200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"name":"EUROCC \u2013 National Competence Centres in the framework of EuroHPC","award":["951732","951732"],"award-info":[{"award-number":["951732","951732"]}]},{"name":"NCSR - Demokritos Library"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Supercomput"],"published-print":{"date-parts":[[2023,7]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>HPC is a key tool for processing and analyzing the constantly growing volume of data, from 64.2 zettabytes in 2020 to an expected 180 zettabytes in 2025 (1 zettabyte is equal to 1 trillion gigabytes). As such, HPC has a large number of application areas that range from climate change, monitoring and mitigating planning to the production of safer and greener vehicles and treating COVID-19 pandemic to the advancement of knowledge in almost every scientific field and industrial domain. The current work presents an HPC Training Mapping Framework and the relevant findings and processed data of an online Training Needs Analysis (TNA) survey. The latter was used to map the training demands and gaps of existing skills and future ones. The participants consist of academia and industry and the data were utilized to find the profile of HPC user alongside the best training practices that are in need. It is found that in Greece during the year 2021, the stakeholder segment with the highest number of respondents was from academia and research with a total of 74%. The vast majority appear to have basic information accounting for 37% of the respondents. In terms of familiarity, users with intermediate familiarity with HPC represented 21% of respondents, followed by non-familiar users that accounted in total for 16.1. Advanced and highly advanced user segments account only for 8.6% and 7.4% accordingly. Overall, it is found that a: (1) fast-pace, (2) entry level, (3) applied HPC training but (4) not focused only on HPC, that will (5) provide some kind of certification, by the Greek HPC ecosystem.<\/jats:p>","DOI":"10.1007\/s11227-023-05080-y","type":"journal-article","created":{"date-parts":[[2023,2,15]],"date-time":"2023-02-15T17:46:50Z","timestamp":1676483210000},"page":"10691-10705","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Mapping the national HPC ecosystem and training needs: The Greek paradigm"],"prefix":"10.1007","volume":"79","author":[{"given":"Stelios","family":"Karozis","sequence":"first","affiliation":[]},{"given":"Xenia","family":"Ziouvelou","sequence":"additional","affiliation":[]},{"given":"Vangelis","family":"Karkaletsis","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,2,15]]},"reference":[{"key":"5080_CR1","doi-asserted-by":"publisher","DOI":"10.1201\/b18322","volume-title":"Industrial applications of high performance computing: best global practices","author":"A Osseyran","year":"2015","unstructured":"Osseyran A, Giles ME (2015) Industrial applications of high performance computing: best global practices. 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