Abstract
The data structures used to represent the multi-material state of a computational physics application can have a significant impact on its performance. We look at efficient data structures for applications where there may be many materials overall, but where most computational cells contain only one or a few of these materials. We develop simple performance models for selecting possible data structures and programming patterns. We verify the analytic performance models with a small test program of the representative cases. We discuss the impact of these techniques and analysis for multi-material physics applications, which are also applicable to a wide range of sparse computational data structures.
| Original language | English |
|---|---|
| Pages (from-to) | 565-581 |
| Number of pages | 17 |
| Journal | Computers and Mathematics with Applications |
| Volume | 78 |
| Issue number | 2 |
| Early online date | 28 Jun 2018 |
| DOIs | |
| Publication status | Published - 15 Jul 2019 |
Keywords
- Compact data structures
- Compressed sparse data structures
- Computational performance
- Data structures
- Multi-material physics