Schendel, U., Introduction to Numerical Methods for Parallel Computers. Chichester, Ellis Horwood Ltd. 1984. 151 S., £ 15.00. ISBN 0-85312-597-X (Mathematics and Its Applications)

Author(s):  
F. Grund
1985 ◽  
Vol 69 (449) ◽  
pp. 238
Author(s):  
Richard Walker ◽  
U. Schendel

2003 ◽  
Vol 210 ◽  
pp. 157-167 ◽  
Author(s):  
A. Vögler ◽  
S. Shelyag ◽  
M. Schüssler ◽  
F. Cattaneo ◽  
T. Emonet ◽  
...  

We present a new 3D MHD code for the simulation of solar magnetoconvection. The code is designed for use on parallel computers and in the choice of methods emphasis has been laid on efficient parallelization. We give a description of the numerical methods and discuss the non-local and non-grey treatment of the radiative transfer. Test calculations underlining the importance of non-grey effects and first results of the simulation of a solar plage region are shown.


Fluids ◽  
2021 ◽  
Vol 6 (11) ◽  
pp. 395
Author(s):  
Hui Liu ◽  
Zhangxin Chen ◽  
Xiaohu Guo ◽  
Lihua Shen

Reservoir simulation is to solve a set of fluid flow equations through porous media, which are partial differential equations from the petroleum engineering industry and described by Darcy’s law. This paper introduces the model, numerical methods, algorithms and parallel implementation of a thermal reservoir simulator that is designed for numerical simulations of a thermal reservoir with multiple components in three-dimensional domain using distributed-memory parallel computers. Its full mathematical model is introduced with correlations for important properties and well modeling. Efficient numerical methods (discretization scheme, matrix decoupling methods, and preconditioners), parallel computing technologies, and implementation details are presented. The numerical methods applied in this paper are suitable for large-scale thermal reservoir simulations with dozens of thousands of CPU cores (MPI processes), which are efficient and scalable. The simulator is designed for giant models with billions or even trillions of grid blocks using hundreds of thousands of CPUs, which is our main focus. The validation part is compared with CMG STARS, which is one of the most popular and mature commercial thermal simulators. Numerical experiments show that our results match commercial simulators, which confirms the correctness of our methods and implementations. SAGD simulation with 7406 well pairs is also presented to study the effectiveness of our numerical methods. Scalability testings demonstrate that our simulator can handle giant models with billions of grid blocks using 100,800 CPU cores and the simulator has good scalability.


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