Computational astrophysics is at the forefront of every major advance in modern astronomy, by linking together very different aspects of the physical world operating at different scales. The IAU Commission B1 on Computational Astrophysics was set up in 2015 in recognition of this, and today nearly 300 IAU members have joined the commission. A capacity building conference is long overdue, where participants take an active part in the coordination and furtherance of computational techniques in a wide range of research (stellar evolution, cosmology, accretion phenomena, planetology, etc.). The proposed workshop aims at building up momentum in this community around key computational challenges, such as:

• the on-set of turbulence, fluid dynamics in star and galaxy formation;
• three-dimensional stellar evolution, supergiants, massive stars and SN events;
• binary black holes, binary neutron stars, gravitational waves, numerical relativity;
• handling large data sets, analysis pipelines and optimization;
• micro and global physics, radiation fields, heat transfer;
• technology of special architecture computers;
• etc.
  

The workshop will bring together a number of experts in each of a broad range of fields, to set the stage for exchanges and collaborations between participants. An invitation is extended to all commission B1 members as well as interested colleagues. We particularly welcome participation of female and young researchers. A stated goal of the meeting is to promote cross-fertilization for better understanding of techniques applied in each field. By doing so, we hope to ensure the highest level of synergy between these various fields. This will give rise to new research programs and bolster scientific collaborations. The thematic contours of the meeting will remain flexible, but an emphasis will be put on computational methods applied to speed up and broaden the scope of scientific studies, such as finding trends from observational data, high performance computing, automated search algorithms, and emergent behavior (e.g., Artificial Intelligence methods).