Name
Abstract | ||
|---|---|---|
During LHC's Run-2 ATLAS has been developing and evaluating new fine-grained approaches to workflows and dataflows able to better utilize computing resources in terms of storage, processing and networks. The compute-limited physics of ATLAS has driven the collaboration to aggressively harvest opportunistic cycles from what are often transiently available resources, including HPCs, clouds, volunteer computing, and grid resources in transitional states. Fine-grained processing (with typically a few minutes' granularity, corresponding to one event for the present ATLAS full simulation) enables agile workflows with a light footprint on the resource such that cycles can be more fully and efficiently utilized than with conventional workflows processing O(GB) files per job. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/eScience.2018.00083 | 2018 IEEE 14th International Conference on e-Science (e-Science) |
Keywords | Field | DocType |
workflow,dataflow,streaming,fine-grained,processing | Large Hadron Collider,Grid computing,Computer science,Agile software development,Dataflow,Granularity,Distributed database,Workflow,Payload,Distributed computing | Conference |
ISSN | ISBN | Citations |
2325-372X | 978-1-5386-9157-1 | 0 |
PageRank | References | Authors |
0.34 | 0 | 16 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Doug Benjamin | 1 | 0 | 0.34 |
| p calafiura | 2 | 2 | 1.10 |
| J. T. Childers | 3 | 1 | 1.37 |
| Kaushik De | 4 | 171 | 23.99 |
| Alessandro Di Girolamo | 5 | 1 | 1.36 |
| Esteban Fullana | 6 | 0 | 0.34 |
| Wen Guan | 7 | 0 | 0.34 |
| Tadashi Maeno | 8 | 0 | 0.34 |
| Nicolò Magini | 9 | 1 | 0.71 |
| Paul Nilsson | 10 | 0 | 0.34 |
| Danila Oleynik | 11 | 0 | 0.68 |
| Shaojun Sun | 12 | 0 | 0.34 |
| Vakho Tsulaia | 13 | 0 | 0.34 |
| Peter van Gemmeren | 14 | 3 | 1.53 |
| Torre J. Wenaus | 15 | 2 | 1.29 |
| Wei Yang | 16 | 0 | 0.34 |