Name
Abstract | ||
|---|---|---|
We present a fast linear time algorithm that uses a block-cut tree for identifying upstream features from a set of starting points in a network. Our implementation has been parallelized and it can process a dataset with 32 million features in less than 8 seconds on a 8-core workstation. This problem is the 2018 ACM SIGSPATIAL CUP challenge and presents several applications mainly on the field of utility networks. Our code is freely available for nonprofit research and education at https://github.com/sallesviana/FastUpstream
|
Year | DOI | Venue |
|---|---|---|
2018 | 10.1145/3274895.3276474 | SIGSPATIAL/GIS |
Keywords | Field | DocType |
Graph algorithms, GISCUP, parallel programming, spatial networks | Graph algorithms,Data mining,Computer science,Workstation,Time complexity | Conference |
ISBN | Citations | PageRank |
978-1-4503-5889-7 | 0 | 0.34 |
References | Authors | |
1 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Salles V. G. Magalhães | 1 | 49 | 10.37 |
| W. Randolph Franklin | 2 | 72 | 16.49 |
| Ricardo Ferreira | 3 | 49 | 13.81 |