Scaling Computational Fluid Dynamics: In Situ Visualization of NekRS using SENSEI
SC-W '23: Proceedings of the SC '23 Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis(2023)
摘要
In the realm of Computational Fluid Dynamics (CFD), the demand for memory and
computation resources is extreme, necessitating the use of leadership-scale
computing platforms for practical domain sizes. This intensive requirement
renders traditional checkpointing methods ineffective due to the significant
slowdown in simulations while saving state data to disk. As we progress towards
exascale and GPU-driven High-Performance Computing (HPC) and confront larger
problem sizes, the choice becomes increasingly stark: to compromise data
fidelity or to reduce resolution. To navigate this challenge, this study
advocates for the use of \textit{in situ} analysis and visualization
techniques. These allow more frequent data "snapshots" to be taken directly
from memory, thus avoiding the need for disruptive checkpointing. We detail our
approach of instrumenting NekRS, a GPU-focused thermal-fluid simulation code
employing the spectral element method (SEM), and describe varied \textit{in
situ} and in transit strategies for data rendering. Additionally, we provide
concrete scientific use-cases and report on runs performed on Polaris, Argonne
Leadership Computing Facility's (ALCF) 44 Petaflop supercomputer and J\"ulich
Wizard for European Leadership Science (JUWELS) Booster, J\"ulich
Supercomputing Centre's (JSC) 71 Petaflop High Performance Computing (HPC)
system, offering practical insight into the implications of our methodology.
更多查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要