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What our Clients say

• Andrzej J. Kałka, PhD

  "While modeling experimental data using a ‘regular’ computer should not, in practice, pose major difficulties, I cannot imagine performing quantum-chemical calculations – a crucial aspect of my research – without advanced computing resources. Therefore, I can confidently describe the provided computational infrastructure as invaluable.”

• Tomasz Szołdra, PhD

  "Some signals, especially those coming from such counterintuitive areas as quantum mechanics, sometimes prove too complex for humans to analyze. This is where machine learning comes in handy, allowing us to automate data analysis processes to a certain extent. (…). I used GPU cards available at Cyfronet to train and test my models.”

• Yizhi Xu, PhD

  "Cyfronet’s supercomputing infrastructure played a critical role in my research for executing all necessary calculations for the design of MOFs computationally with desired properties. (…) Moreover, the GPU cores offered by the Ares supercomputer were essential for training machine learning potentials, in order to further speed up the CSP calculations for MOF design.”