Registration information

The workshop is free of charge. Registration is closed. Please contact the organisers for questions. In order to make the workshop as productive as possible, please include the following information during the registration:

• Briefly describe your experience with GPAW and motivation for attending the workshop.
• Indicate which sections of the program you are interested to attend: talks, hands-on help, coding, and/or discussions.
• Are you interested in presenting a poster and/or giving a short one-slide introduction to your research or plans using GPAW?

Please also indicate if you are planning to attend only some days/parts of the workshop.

Description

Electronic Structure calculations stand out as a cornerstone for modern material development. GPAW is a popular open-source electronic structure code, utilizing a computationally efficient projector-augmented wave method, with a variety of descriptions of the wave functions (localized basis functions, planewaves, and finite-difference grids) [1]. This enables GPAW calculations with optimized accuracy-efficiency balance. GPAW supports a wide range of computation and analysis tools, and there is a continuous international effort to develop the code. Examples of the recent development are: excitation analysis from real-time TDDFT [2], GW and BSE state-of-art improvements [3], new QM/MM [4] and real-time TDDFT circular diochroim implementations [5]. The constrained DFT, orbital-free DFT, QED-DFT, nonlinear spectra simulations are also under development. These recent developments are planned to be presented and discussed in the meeting.

Furthermore, the GPAW code is written in the modern and flexible programming language Python, and it is tightly interfaced with Atomic Simulation Environment (ASE). The streamlined infrastruc- ture and overlapping developer communities are ready for future big data challenges. For example, high-throughput material databases have been built on top of this infrastructure [6]. In this meeting, we aspire to discussions on empowering future data-driven research and exascale/high-throughput computing, such as computational screening, machine learning, and other big data applications that require robust data stream handling and flexible programming environment by GPAW code.

The use of high-end Python language and clean code structure allow junior scientific members to start developing quickly. In this meeting, we will include development workshops and hands-on help sections for users. These sections are expected to encourage more people to develop GPAW features for their own research and improve user-friendliness of GPAW.