Parallel dynamic programming for multi-reservoir system optimization
被引:0
作者:
Li, Xiang
论文数: 0引用数: 0
h-index: 0
机构:
State Key Laboratory of Hydroscience and Engineering, Tsinghua University, Beijing 100084, ChinaState Key Laboratory of Hydroscience and Engineering, Tsinghua University, Beijing 100084, China
Li, Xiang
[1
]
Wei, Jiahua
论文数: 0引用数: 0
h-index: 0
机构:
State Key Laboratory of Hydroscience and Engineering, Tsinghua University, Beijing 100084, ChinaState Key Laboratory of Hydroscience and Engineering, Tsinghua University, Beijing 100084, China
Wei, Jiahua
[1
]
Yao, Chenchen
论文数: 0引用数: 0
h-index: 0
机构:
HydroChina Investment Co., Ltd, East China Investigation and Design Institute, Hangzhou 310014, ChinaState Key Laboratory of Hydroscience and Engineering, Tsinghua University, Beijing 100084, China
Yao, Chenchen
[2
]
Li, Tiejian
论文数: 0引用数: 0
h-index: 0
机构:
State Key Laboratory of Hydroscience and Engineering, Tsinghua University, Beijing 100084, ChinaState Key Laboratory of Hydroscience and Engineering, Tsinghua University, Beijing 100084, China
Li, Tiejian
[1
]
Liu, Ronghua
论文数: 0引用数: 0
h-index: 0
机构:
State Key Laboratory of Hydroscience and Engineering, Tsinghua University, Beijing 100084, ChinaState Key Laboratory of Hydroscience and Engineering, Tsinghua University, Beijing 100084, China
Liu, Ronghua
[1
]
机构:
[1] State Key Laboratory of Hydroscience and Engineering, Tsinghua University, Beijing 100084, China
[2] HydroChina Investment Co., Ltd, East China Investigation and Design Institute, Hangzhou 310014, China
来源:
Qinghua Daxue Xuebao/Journal of Tsinghua University
|
2013年
/
53卷
/
09期
The paper shows how high performance computing can solve the multi-reservoir system optimization problem. A multi-dimensional dynamic programming (DP) model is developed for the four-reservoir problem. Then, the master-slave parallelization strategy is used to parallelize the serial DP algorithm. A high performance parallel computer is then used to solve the four-reservoir system with various numbers of cores (up to 300 cores). The results show that distributed computing effectively shortens the computation time for the algorithm, the speedup further increase as the number of cores increases and parallel efficiency decreases very slowly. Future work should use the distributed computer memory to alleviate DP's large computer memory requirements.