Conveners
Computational Materials Science towards the Exascale: performance portability and use cases
- Andrea Ferretti (CNR Nano)
- Ivan Marri (University of Modena and Reggio Emilia)
- Elisa Molinari (University of Modena and Reggio Emilia)
- Maria Celeste Maschio (CNR Nano)
Computational Materials Science towards the Exascale: performance portability and use cases
- Maria Celeste Maschio (CNR Nano)
- Andrea Ferretti (CNR Nano)
- Ivan Marri (University of Modena and Reggio Emilia)
- Elisa Molinari (University of Modena and Reggio Emilia)
Description
Materials design at the exascale: success cases using HPC and HTC
Performance portability of legacy scientific codes on HPC architectures, co-design, and energy efficiency
In today's data-driven world, High-Performance Computing (HPC) is an emerging reference platform that drives scientific research and enables industrial innovations. This is articularly true for the research in Materials Science, in which, by simply applying the equations of quantum mechanics in large HPC calculations, scientists are able to study and design new materials, before running actual experiments, decreasing costs and enhancing performance.
MaX CoE – ‘Materials design at the eXascale’ - is devoted to enable materials modelling, simulations, discovery and design at the frontiers of the current and future pre-exascale and exascale HPC architectures.
MaX workshop, that gathers scientists and organisations active in the field of materials modelling, aims at discussing the performance and portability of MaX flagship codes (Quantum ESPRESSO, Yambo, Siesta, Fleur, CP2K, BigDFT and AiiDA) and the recent advances in computational materials research based on quantum physics and electronic structure methods.
In particular we will focus on:
● advances in high-performance computing for materials science,
● high throughput computing for materials discovery,
● new avenues from data analytics/artificial intelligence in materials science,
● trends in high-performance computing and codesign towards exascale,
● energy efficiency strategy in HPC systems
● novel algorithms for first-principles simulations.
Furthermore, some success cases of materials simulations will be presented.
