The Helmholtz Artificial Intelligence Cooperation Unit (Helmholtz AI) is one of five platforms initiated by the Helmholtz Information and Data Science Incubator. Its main goal is to become a driver for applied artificial intelligence (AI) through the development and distribution of AI methods across all Helmholtz centres, effectively combining AI-based analytics with the Helmholtz Association’s unique research questions and datasets.

The objective of the project “AlphaNumerics Zero” (ɑN0), led by JSC together with researchers from the Steinbuch Centre for Computing at KIT, is to rethink numerical methods on high-performance computers. Traditionally, a lot of effort goes into the design, implementation, and optimization of solvers for differential equations, numerical libraries, etc. Furthermore, performance engineering is necessary to scale simulation codes onto supercomputers. New ideas are urgently needed as developing methods for the upcoming extreme-scale supercomputers is becoming increasingly challenging. Our goal is to use reinforcement learning techniques so that the computer learns the on-average optimal numerical solution method for a given simulation problem by itself. The deliverables for the project will be a working framework and a demonstration in one application case using a time-dependent partial differential equation. This is a moonshot project that – if successful – will be the first step to changing the paradigm of how numerical simulations are designed and performed on extreme-scale computers. It would have an impact on all research fields that rely on numerical simulations.