Name
Abstract | ||
|---|---|---|
Scientific simulations on high performance computing (HPC) platforms generate large quantities of data. To bridge the widening gap between compute and I/O, and enable data to be more efficiently stored and analyzed, simulation outputs need to be refactored, reduced, and appropriately mapped to storage tiers. However, a systematic solution to support these steps has been lacking in the current HPC ... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/TMSCS.2018.2886851 | IEEE Transactions on Multi-Scale Computing Systems |
Keywords | Field | DocType |
Data analysis,Computational modeling,Data models,Analytical models,High performance computing,Feature extraction | Data modeling,Data mining,Decimation,Data analysis,Supercomputer,Computer data storage,Computer science,Feature extraction,Data management,Data model | Journal |
Volume | Issue | ISSN |
4 | 4 | 2332-7766 |
Citations | PageRank | References |
1 | 0.35 | 0 |
Authors | ||
7 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhenbo Qiao | 1 | 9 | 1.50 |
| Tao Lu | 2 | 23 | 8.00 |
| Huizhang Luo | 3 | 16 | 3.96 |
| Qing Liu | 4 | 389 | 25.62 |
| Scott Klasky | 5 | 1547 | 99.00 |
| Norbert Podhorszki | 6 | 1046 | 83.84 |
| Jinzhen Wang | 7 | 1 | 2.38 |