Performance Debugging and Tuning of Flash-X with Data Analysis Tools
State-of-the-art multiphysics simulations running on large scale leadership computing platforms have many variables contributing to their performance and scaling behavior. We recently encountered an interesting performance anomaly in Flash-X, a multiphysics multicomponent simulation software, when characterizing its performance behavior on several large-scale HPC platforms. The anomaly was tracked down to the interaction between the use of dynamic allocation of scratch data and data locality in the cache hierarchy. In this paper we present the details of unexpected performance variability of Flash-X, its extensive analysis using the performance measurement tool TAU to collect the data and Python data analysis libraries to explore the data, and our insights from this experience. In this process, we discovered and removed or mitigated two additional performance limiting bottlenecks for performance tuning.
- Research Organization:
- Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
- Sponsoring Organization:
- USDOE Office of Science (SC)
- DOE Contract Number:
- AC05-00OR22725
- OSTI ID:
- 2000270
- Resource Relation:
- Conference: ProTools 2022: Workshop on Programming and Performance Visualization Tools - Dallas, Texas, United States of America - 11/13/2022 5:00:00 AM-11/18/2022 5:00:00 AM
- Country of Publication:
- United States
- Language:
- English
Similar Records
Developing And Scaling an OpenFOAM Model to Study Turbulent Flow in a HFIR Coolant Channel
Active Flash: Out-of-core Data Analytics on Flash Storage