Name
Abstract | ||
|---|---|---|
Cosmological N-body simulations on parallel computers produce large datasets--gigabytes at each instant of simulated cosmological
time, and hundreds of gigabytes over the course of a simulation. These large datasets require further analysis before they
can be compared to astronomical observations. The “Halo World” tools include two methods for performing halo finding: identifying
all of the gravitationally stable clusters in a point-sampled density field. One of these methods is a parallel implementation
of the friends of friends (FOF) algorithm, widely used in the field of N-body cosmology. The new IsoDen method based on isodensity
surfaces has been developed to overcome some of the shortcomings of FOF. Parallel processing is the only viable way of obtaining
the necessary performance and storage capacity to carry out these analysis tasks. Ultimately, we must also plan to use disk
storage as the only economically viable alternative for storing and manipulating such large data sets. Both IsoDen and friends
of friends have been implemented on a variety of computer systems, with parallelism up to 512 processors, and successfully
used to extract halos from simulations with up to 16.8 million particles. |
Year | DOI | Venue |
|---|---|---|
1997 | 10.1023/A:1009729602855 | Data Min. Knowl. Discov. |
Keywords | Field | DocType |
clustering,density estimation,parallel computation,astrophysics,N-body simulation | Disk storage,Density estimation,Cluster (physics),Cosmology,Computer science,N-body simulation,Parallel computing,Gigabyte,Halo,Cluster analysis | Journal |
Volume | Issue | ISSN |
1 | 4 | 1573-756X |
Citations | PageRank | References |
3 | 0.54 | 2 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| david pfitzner | 1 | 5 | 1.33 |
| John K. Salmon | 2 | 410 | 46.45 |
| Thomas L. Sterling | 3 | 565 | 99.77 |
| Paul E. Stolorz | 4 | 138 | 46.77 |
| Ron Musick | 5 | 146 | 32.49 |