scholarly journals Load balancing using Hilbert space-filling curves for parallel shallow water simulations

Author(s):  
А.В. Чаплыгин ◽  
Н.А. Дианский ◽  
А.В. Гусев

Представлен метод балансировки нагрузки вычислений с использованием кривых Гильберта применительно к параллельному алгоритму решения уравнений мелкой воды. Рассматриваемая система уравнений мелкой воды возникает в сигма-модели общей циркуляции океана INMOM (Institute of Numerical Mathematics Ocean Model) при разрешении гравитационных волн и является одним из основных блоков модели. Из-за наличия в океанах островов и берегов балансировка нагрузки вычислений на процессоры является особенно актуальной задачей. В качестве одного из таких методов был выбран метод балансировки нагрузки вычислений с использованием кривых Гильберта. Продемонстрирована большая эффективность этого метода по сравнению с равномерным разбиением без балансировки нагрузки и показано, что этот метод служит хорошей альтернативой библиотеке разбиений METIS. Оптимальность реализованного разбиения для мелкой воды точно соответствует оптимальности и для трехмерной сигма-модели INMOM в силу одинакового количества вертикальных уровней во всей расчетной области. This paper presents a method of load balancing using Hilbert space-filling curves applied to a parallel algorithm for solving shallow water equations. We consider the system of shallow water equations in the form presented in the ocean general circulation sigma-model INMOM (Institute of Numerical Mathematics Ocean Model). This system of equations is one of the basic blocks of the model. Due to land points in the computational grid, the load balancing is an especially urgent task. The method of load balancing using Hilbert space-filling curves is chosen as one of such methods. The paper demonstrates the greater efficiency of this method in comparison with the uniform partitioning without load balancing. It is shown that this method is a good alternative to the METIS standard library. Moreover, the optimality of the implemented partition for the shallow water equations exactly corresponds to the optimality for the INMOM three-dimensional sigma-model due to the same number of vertical levels in the entire computational domain.

Author(s):  
Paulo Costa ◽  
João Barroso ◽  
Hugo Fernandes ◽  
Leontios J Hadjileontiadis

2020 ◽  
pp. short52-1-short52-9
Author(s):  
Aleksandr Bragin ◽  
Vladimir Spitsyn

The article is devoted to the problem of recognition of motor imagery based on electroencephalogram (EEG) signals, which is associated with many difficulties, such as the physical and mental state of a person, measurement accuracy, etc. Artificial neural networks are a good tool in solving this class of problems. Electroencephalograms are time signals, Gramian Angular Fields (GAF), Markov Transition Field (MTF) and Hilbert space-filling curves transformations are used to represent time series as images. The paper shows the possibility of using GAF, MTF and Hilbert space-filling curves EEG signal transforms for recognizing motor patterns, which is further applicable, for example, in building a brain-computer interface.


Computation ◽  
2019 ◽  
Vol 7 (1) ◽  
pp. 9 ◽  
Author(s):  
Christoph Rettinger ◽  
Ulrich Rüde

Parallel multiphysics simulations often suffer from load imbalances originating from the applied coupling of algorithms with spatially and temporally varying workloads. It is, thus, desirable to minimize these imbalances to reduce the time to solution and to better utilize the available hardware resources. Taking particulate flows as an illustrating example application, we present and evaluate load balancing techniques that tackle this challenging task. This involves a load estimation step in which the currently generated workload is predicted. We describe in detail how such a workload estimator can be developed. In a second step, load distribution strategies like space-filling curves or graph partitioning are applied to dynamically distribute the load among the available processes. To compare and analyze their performance, we employ these techniques to a benchmark scenario and observe a reduction of the load imbalances by almost a factor of four. This results in a decrease of the overall runtime by 14% for space-filling curves.


2003 ◽  
Author(s):  
Arturo Pacheco-Vega ◽  
J. Rafael Pacheco ◽  
Tamara Rodic´

We present a flux vector splitting (FVS) for the solution of the shallow water equations with emphasis in their application to film flows for which a hydraulic jump may exist. The governing equations and boundary conditions are transformed from the physical to the computational domain and solved in a rectangular grid. A first-order upwind finite difference scheme is used at the point of the shock while a second-order upwind differentiation is applied elsewhere. Higher-order spatial accuracy is achieved by using a MUSCL approach. Two problems, (a) one-dimensional dam break problem and (b) radial flow with jump, are investigated to show the usefulness and accuracy of the method. Results demonstrate that the method is able to predict accuratelly the hydraulic jump using shallow water theory.


2010 ◽  
Vol E93-D (7) ◽  
pp. 1807-1815
Author(s):  
Chih-Sheng CHEN ◽  
Shen-Yi LIN ◽  
Min-Hsuan FAN ◽  
Chua-Huang HUANG

Sign in / Sign up

Export Citation Format

Share Document