Computational Materials Science Summer School - Fostering Accelerated Scientific Techniques (CMS3 - FAST)

Abstract

The integration of Computational Materials Science (CMS) and Machine Learning (ML)/Artificial Intelligence (AI) techniques, along with Accelerated High-Performance Computing (AHPC) achieved using modern hardware accelerators such as GPUs, provides a powerful platform for researchers to accelerate advancements in Materials Science and Engineering. However, the rapid advancement of these fields has also created a gap in the workforce, with a shortage of researchers who are simultaneously trained in all three areas: CMS, ML/AI, and AHPC. Thus, the specific objectives of the CMS3-FAST program are to: (i) Integrate CMS, ML/AI techniques, and AHPC into one comprehensive education and hands-on training program. (ii) Leverage immersive visualization through virtual and augmented reality (VR/AR) tools and AI-based natural language generation tools to provide a tailored environment for participants with different backgrounds and learning styles. (iii) Rigorously test and enhance the scaling of the education and hands-on training components, while also broadening access to enable large-scale and unrestricted workforce development. (iv) Develop studio-based curricula that integrate CMS, ML/AI techniques, and AHPC at various levels of complexity for both undergraduate and graduate students. (v) Expand the current network of CI professionals and contributors to establish a powerful platform that accelerates advancements in Materials Science and Engineering through continuous training and development. By achieving these objectives, the CMS3-FAST program will create a new generation of highly skilled CI users, equipped with cutting-edge tools and techniques to drive innovation in Materials Science and Engineering.