Name
Title | ||
|---|---|---|
Speeding up multi-objective optimization of liquid fossil fuel reserve exploitation with parallel hybrid memory integration |
Abstract | ||
|---|---|---|
In this paper, we show a hybrid parallelization method for reducing the computational cost of a solver using hybrid-memory parallel machines. We show how the hybrid parallelization can be utilized to speed up challenging computational applications. Namely, we focus on the liquid fossil fuel reservoir exploitation problem (LFFEP), the optimization inverse problem where we try to find the optimal locations of pumps and sinks during the oil exploitation technique with hydraulic fracturing to maximize the amount of oil and minimize groundwater contamination. In our simulations, we combine a hierarchical genetic search (HGS) with an isogeometric finite element method solver. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1016/j.jocs.2019.01.001 | Journal of Computational Science |
Keywords | DocType | Volume |
Isogeometric analysis,Hybrid parallelization,Inverse problems | Journal | 31 |
ISSN | Citations | PageRank |
1877-7503 | 0 | 0.34 |
References | Authors | |
3 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Barbara Barabasz | 1 | 0 | 0.68 |
| Stephen Barrett | 2 | 63 | 6.47 |
| Leszek Siwik | 3 | 67 | 13.85 |
| Marcin Los | 4 | 18 | 4.56 |
| Krzysztof Podsiadlo | 5 | 0 | 0.34 |
| M. Wozniak | 6 | 27 | 7.48 |