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The funding supports high-quality research related to high-performance computing and the introduction of the EuroHPC and quantum computers as well as the utilisation of high-performance computing in various fields. The projects to be funded effectively promote the renewal and diversity of science, the quality of research as well as scientific and societal impact.

In its review report, the review panel noted that the applications were of a high international standard. Professor Johanna Myllyharju, Chair of the Academy of Finland Board, in turn noted the importance of having the call focus on competence development.

– In line with the objectives of the call, the General Subcommittee wanted to support the development of the future computing ecosystem and the versatile expansion of related expertise and utilisation to new sectors, she said. Myllyharju chaired the General Subcommittee, which made the funding decisions.

Funded projects

Tuula Aalto (Finnish Meteorological Institute) heads a project that will employ new high-performance computing resources to estimate carbon dioxide and methane emissions and assess carbon sinks and the uncertainties related to them. The project will make use of atmospheric inverse modelling on a nationally significant scale.

Miguel Caro (Aalto University) received funding for a project that will develop the use of a method based on Gaussian approximation potentials (GAPs) for new supercomputers based on graphics processing, especially the LUMI supercomputer. Switching from ordinary processors (CPUs) to graphics processors (GPUs) is a challenge for computational scientists, as the existing codes need to be adapted to a different computational logic. The consortium led by Caro, backed by Aalto University and CSC – the IT Centre for Science, is a concerted effort between computational physicists and software experts.

Recent breakthroughs in population genomics have demonstrated that mapping and understanding pangenomic variation within a species is becoming essential for applications such as modelling tumour evolution and predicting treatment outcomes. Keijo Heljanko (University of Helsinki) heads a project that aims to ease the processing of data related to the screening of the pangenome of a species and will deliver improved, practical methods for the analysis, compression and indexing of massive genomic collections.

Antti Kemppinen (VTT Technical Research Centre of Finland Ltd) heads a project where researchers at VTT and Aalto University will join forces to develop an optically linked computing ecosystem for quantum machine learning (QML). The researchers will also develop QML algorithms, which can be exponentially faster than corresponding classical machine learning algorithms. Despite significant promise, QML in general suffers from the problem of transmitting classical data between high-performance and quantum computers.

Tommi Kärkkäinen (University of Jyväskylä) heads a project that was granted funding to develop a new concept for the design of catalysts. Catalysts can be used, for example, in the production of clean hydrogen. Cleanly produced hydrogen in turn is crucial for achieving a low-carbon society. The consortium led by Kärkkäinen is interdisciplinary, consisting of groups that have demonstrated complementary expertise in computational catalysis, materials science and computational science.

Minna Palmroth (University of Helsinki) heads a consortium of the University of Helsinki, the University of Oulu and CSC – the IT Centre for Science that aims to develop cutting-edge computational methods to fully exploit the LUMI supercomputer being installed at CSC in Finland. The research project will expand the Finnish high-performance computing field and take it to the next level. Modern society is completely dependent on power networks as well as satellite, radar and radio signals. All these are susceptible to disturbances in the ionosphere, the region between the atmosphere and space. Ionospheric situational awareness, achieved through accurate observations and numerical models, is therefore increasingly important.

Mikko Tolonen (University of Helsinki) heads a joint project between the University of Helsinki, the University of Turku and Aalto University that focuses on the use of high-performance computing in the detection and analysis of historical discourses. It will supplement historical scholarship, which often builds its cases from a limited number of documents and then makes generalisations from them. In addition, it will challenge recent uses of “big data” in history that perform analyses at aggregate level.