About this Abstract |
Meeting |
2023 TMS Annual Meeting & Exhibition
|
Symposium
|
Algorithm Development in Materials Science and Engineering
|
Presentation Title |
An OpenMP GPU-Offload Implementation of a Cellular Automata Solidification Model for Laser Fusion Additive Manufacturing |
Author(s) |
Adrian S. Sabau, Lang Yuan, Jean-Luc Fattebert |
On-Site Speaker (Planned) |
Adrian S. Sabau |
Abstract Scope |
A cellular automata (CA) solidification code, which takes into account alloy segregation, diffusion and external temperature distributions, was used to simulate the formation of solidification microstructures for laser powder bed fusion additive manufacturing (LPBFAM). OpenMP offloading was used to accelerate simulations on GPU-based HPC platforms. Data on code speed-up and scalability is presented. The performance results on Summit at the Oak Ridge Leadership Computing Facility indicate that using a precomputed list of interface cells significantly decreased the wall-clock time on GPUs. A rapid directional solidification problem, representative of LPBFAM, was considered to demonstrate the CA code capability on Summit. A mesh size of 0.05µm was found to yield accurate elongated grain microstructure and elongated subgrain features, in qualitative good agreement with experimental data. The results presented in this study indicate that the implementation strategies on GPU-based HPC platforms for the CA code are appropriate for novel HPC exascale platforms. |
Proceedings Inclusion? |
Planned: |
Keywords |
Additive Manufacturing, Computational Materials Science & Engineering, Solidification |