| Abstract: |
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The last 30 years have seen the development of powerful quantum-mechanical simulation engines dedicated to the solution of the electronic-structure problem in atoms, molecules, and materials. Their implementation on massively parallel architectures, now leveraging also GPUs and accelerators, has started a massive effort in the prediction from first principles of many complex properties, pushing the field of materials modelling into design and discovery, and aiming at exascale computing through the combination of HPC (high-performance computing) and HTC (high-throughput computing). Challenges and opportunities abound: complementing hardware and software investments and design; developing the materials’ informatics infrastructure needed to encode knowledge into complex protocols and workflows of calculations; managing and curating data; resisting the complacency that we have already reached the predictive accuracy needed for materials design, or a robust level of verification of the different quantum engines. In this talk I will provide an overview of these challenges, with the ultimate prize being the computational understanding, prediction, and design of properties and performance for novel or complex materials and devices. |
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