About this Abstract |
Meeting |
2022 TMS Annual Meeting & Exhibition
|
Symposium
|
Algorithm Development in Materials Science and Engineering
|
Presentation Title |
OpenMP GPU Offloading for Cellular Automaton Solidification Microstructural Model |
Author(s) |
Lang Yuan, Adrian S Sabau, Jean-Luc Fattebert |
On-Site Speaker (Planned) |
Lang Yuan |
Abstract Scope |
The state-of-the-art supercomputers implements a hybrid architecture where general-purpose host CPUs couple with specialized computing devices, GPUs, allowing significant acceleration of computations. In this study, a CPU-based solidification microstructure code that simulates dendritic growth was parallelized with Open MPI with implementation of OpenMP GPU offloading. This development allows the code to take the advantages of exascale computing without significantly restructuring the original code. The offloading strategy, unique data structure inherited to cellular automation methods and memory access will be discussed for the improvement of GPU utilization. Two cases, unconstrained dendritic growth under the equilibrium condition and constrained growth during rapid solidification, were examined in detail to evaluate its performance. Individual computational modules, e.g., nucleation, diffusion, interface capture, can be accelerated from 1 to 100 times, depending on the computational intensity. Overall performance was improved ranging from 2.5 times to 30 times based on the baseline conditions and solidification cases. |
Proceedings Inclusion? |
Planned: |
Keywords |
Computational Materials Science & Engineering, Modeling and Simulation, Other |