|
BEACON eSpace at Jet Propulsion Laboratory >
JPL Technical Report Server >
JPL TRS 1992+ >
Please use this identifier to cite or link to this item:
http://hdl.handle.net/2014/24994
|
| Title: | Parallel Climate Data Assimilation PSAS Package |
| Authors: | Ding, Hong Q.
Chan, Clara
Gennery, Donald B.
Ferraro, Robert D. |
| Issue Date: | Jun-1996 |
| Citation: | Knoxville, Tennessee, USA |
| Abstract: | We have designed and implemented a set of highly efficient and highly scalable algorithms for an unstructured computational package, the PSAS data assimilation package, as demonstrated by detailed performance analysis of systematic runs on up to 512node Intel Paragon. The equation solver achieves a sustained 18 Gflops performance. As the results, we achieved an unprecedented 100-fold solution time reduction on the Intel Paragon parallel platform over the Cray C90. This not only meets and exceeds the DAO time requirements, but also significantly enlarges the window of exploration in climate data assimilations. |
| URI: | http://hdl.handle.net/2014/24994 |
| Appears in Collections: | JPL TRS 1992+
|
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.
|
