As a part of the EuroCC project DTU, AAU and UCPH conducted a survey of HPC resource usage at Danish Universities. The intention was to get insights on the state of HPC, AI and HPDA provision, training offerings and needs within the Danish Universities. This report represents the results from the survey and is a contribution to the overall aim to support that a sufficient number of people are trained for expanding HPC demands in academia and industry.
The survey was conducted in the autumn 2021, and sent to all Danish Universities. 201 questionnaires was answered and returned, even though some was only partly answered. There is a clear overrepresentation of respondents from DTU and science in general, just as other universities only have few or no answers at all. Still the report gives useful knowledge of how the respondents find the supply, content, format and quality of HPC, AI and HPDA provision and training at the Danish universities.
Key Findings
The main results from the report are:
- The respondents expect increased demand for HPC resources, especially for GPUs.
- Even though many respondents find no significant challenges using HPC, AI and HPDA, many more cannot locate sufficent support or guidance in order to either access or utilise existing resources.
- Most respondents have the right knowledge and skills to participate in offered HPC, AI and HPDA courses
- The respondents prefer shorter and self-paced learning over longer and structured courses
- The available courses seems to favour theoretical aspects over practical, where course participant prefer an equal balance.
- The reports identify that the respondents at universities find shortcomings in access to computer resources and the need for more visibility for both access to HPC resources and courses with a changed format.
- It must be taken into account, that the respondents are spread across all sciences and largely already users of HPC, AI and HPDA.
- It is expected that there will be an increased demand for HPC, AI and HPDA within other disciplines that may not be reflected in the respondents.
Download the full report here.
This project has received funding from the European High-Performance Computing Joint Undertaking (JU) under grant agreement No 951732. The JU receives support from the European Union’s Horizon 2020 research and innovation programme and Germany, Bulgaria, Austria, Croatia, Cyprus, Czech Republic, Denmark, Estonia, Finland, Greece, Hungary, Ireland, Italy, Lithuania, Latvia, Poland, Portugal, Romania, Slovenia, Spain, Sweden, United Kingdom, France, Netherlands, Belgium, Luxembourg, Slovakia, Norway, Switzerland, Turkey, Republic of North Macedonia, Iceland, Montenegro.