Abstract
We present Mini-Combust, a representative mini-application to explore algorithms of interest for simulating combustion in aero turbine engines. Mini-Combust uses an asynchronous coupled Lagrangian-Eulerian (particle and FVM flow field solver) approach and incorporates basic models for heat transfer, turbulence, boundary conditions, convection schemes, fuel, spray atomisation and emissions. The mini-app is developed in a modular and scalable setup with highly optimized code-paths for executing the solvers on multi-core CPU systems and on CPU/GPU heterogeneous systems. We investigate its performance and scalability on two high-performance computing systems, exploring key performance profiles on up to 32k CPU cores and 128 GPUs, solving a test case representative of a bluff-body swirl burner from industry. Results demonstrate the highly memory-bound nature of the key kernels of the solvers. We see a speedup of 8.8× on an H100 node compared to a power-equivalent number of CPU nodes when offloading the most time-consuming component, the Eulerian solver, to GPUs, executing the asynchronous solvers in a hybrid CPU-GPU manner on an NVIDIA H100 GPU node. Additionally, we see how the communication overhead between the two solvers becomes more pronounced at increasing scale. Mini-Combust is available as open-source software.
| Original language | English |
|---|---|
| Title of host publication | 2024 IEEE 31st International Conference on High Performance Computing, Data, and Analytics (HiPC) |
| Publisher | Institute of Electrical and Electronics Engineers (IEEE) |
| Pages | 199-209 |
| Number of pages | 11 |
| ISBN (Electronic) | 9798331509095 |
| ISBN (Print) | 9798331509101 |
| DOIs | |
| Publication status | Published - 20 Feb 2025 |
| Event | 31st IEEE International Conference on High Performance Computing, Data, and Analytics - Bengaluru, India Duration: 18 Dec 2024 → 21 Dec 2024 https://www.hipc.org/ |
Publication series
| Name | IEEE International Conference on High Performance Computing, Data, and Analytics (HiPC) |
|---|---|
| Publisher | IEEE |
| ISSN (Print) | 1094-7256 |
| ISSN (Electronic) | 2640-0316 |
Conference
| Conference | 31st IEEE International Conference on High Performance Computing, Data, and Analytics |
|---|---|
| Country/Territory | India |
| City | Bengaluru |
| Period | 18/12/24 → 21/12/24 |
| Internet address |
Bibliographical note
Publisher Copyright:© 2024 IEEE.
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