Name
Abstract | ||
|---|---|---|
DiscFinder is a scalable approach for identifying large-scale astronomical structures, such as galaxy clusters, in massive observation and simulation astrophysics datasets. It is designed to operate on datasets with tens of billions of astronomical objects, even in the case when the dataset is much larger than the aggregate memory of compute cluster used for the processing. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1145/1851476.1851527 | HPDC |
Keywords | Field | DocType |
scalable approach,data-intensive scalable cluster finder,astronomical object,large-scale astronomical structure,galaxy cluster,aggregate memory,massive observation,simulation astrophysics datasets,text analysis,galaxy clusters | Astrophysics,Computer science,Galaxy cluster,Astronomical Objects,Sextant (astronomical),Computer cluster,Scalability | Conference |
Citations | PageRank | References |
7 | 0.73 | 10 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Bin Fu | 1 | 204 | 8.25 |
| Kai Ren | 2 | 229 | 12.85 |
| Julio López | 3 | 165 | 11.33 |
| Eugene Fink | 4 | 18 | 2.20 |
| Garth Gibson | 5 | 257 | 13.77 |