Large Scale Parallel Hybrid GMRES Method for the Linear System on Grid System

2008 ◽  
Author(s):  
Ye Zhang ◽  
Guy Bergere ◽  
Serge Petiton
Keyword(s):  
Linear System ◽  
Large Scale ◽  
Gmres Method ◽  
Grid System ◽  
Parallel Hybrid

The Linear System Solver of Programs Named CORTH and KYLIN2

2017 ◽  
Author(s):  
Pingzhou Ming ◽  
Junjie Pan ◽  
Xiaolan Tu ◽  
Dong Liu ◽  
Hongxing Yu
Keyword(s):  
Linear System ◽  
Linear Systems ◽  
Nuclear Power ◽  
Experimental Results ◽  
Gmres Method ◽  
Thermal Hydraulics ◽  
Lattice Calculation ◽  
Minimal Residual

Sub-channel thermal-hydraulics program named CORTH and assembly lattice calculation program named KYLIN2 have been developed in Nuclear Power Institute of China (NPIC). For the sake of promoting the computing efficiency of these programs and achieving the better description on fined parameters of reactor, the programs’ structure and details are interpreted. Then the characteristics of linear systems of these programs are analyzed. Based on the Generalized Minimal Residual (GMRES) method, different parallel schemes and implementations are considered. The experimental results show that calculation efficiencies of them are improved greatly compared with the serial situation.

Efficient and Secure Outsourcing of Large-Scale Linear System of Equations

2018 ◽  
pp. 1-1 ◽  
Author(s):  
Qi Ding ◽  
Guobiao Weng ◽  
Guohui Zhao ◽  
Changhui Hu
Keyword(s):  
Linear System ◽  
Large Scale ◽  
System Of Equations ◽  
Linear System Of Equations ◽  
Secure Outsourcing

Adaptive complex frequency with V-cycle GMRES for preconditioning 3D Helmholtz equation

Geophysics ◽  
2021 ◽  
pp. 1-40
Author(s):  
Wenhao Xu ◽  
Yang Zhong ◽  
Bangyu Wu ◽  
Jinghuai Gao ◽  
Qing Huo Liu
Keyword(s):  
Linear System ◽  
Helmholtz Equation ◽  
3D Models ◽  
Numerical Results ◽  
Spatial Sampling ◽  
Gmres Method ◽  
Complex Frequency ◽  
Iterative Solver ◽  
Helmholtz Equations ◽  
Sampling Density

Solving the Helmholtz equation has important applications in various areas, such as acoustics and electromagnetics. Using an iterative solver together with a proper preconditioner is key for solving large 3D Helmholtz equations. The performance of existing Helmholtz preconditioners usually deteriorates when the minimum spatial sampling density is small (approximately four points per wavelength [PPW]). To improve the efficiency of the Helmholtz preconditioner at a small minimum spatial sampling density, we have adopted a new preconditioner. In our scheme, the preconditioning matrix is constructed based on an adaptive complex frequency that varies with the minimum spatial sampling density in terms of the number of PPWs. Furthermore, the multigrid V-cycle with a GMRES smoother is adopted to effectively solve the corresponding preconditioning linear system. The adaptive complex frequency together with a GMRES smoother can work stably and efficiently at different minimum spatial sampling densities. Numerical results of three typical 3D models show that our scheme is more efficient than the multilevel GMRES method and shifted Laplacian with multigrid full V-cycle and a symmetric Gauss-Seidel smoother for preconditioning the 3D Helmholtz linear system, especially when the minimum spatial sampling density is large (approximately 120 PPW) or small (approximately 4 PPW).

Error Recovery for SLA-Based Workflows within the Business Grid

2012 ◽  
pp. 1349-1375
Author(s):  
Dang Minh Quan ◽  
Jörn Altmann ◽  
Laurence T. Yang
Keyword(s):  
Large Scale ◽  
Service Level Agreement ◽  
Error Recovery ◽  
Service Level ◽  
Small Scale ◽  
Grid System ◽  
Negative Effects ◽  
Recovery Mechanism ◽  
Recovery Mechanisms ◽  
Grid Based

This chapter describes the error recovery mechanisms in the system handling the Grid-based workflow within the Service Level Agreement (SLA) context. It classifies the errors into two main categories. The first is the large-scale errors when one or several Grid sites are detached from the Grid system at a time. The second is the small-scale errors which may happen inside an RMS. For each type of error, the chapter introduces a recovery mechanism with the SLA context imposing the goal to the mechanisms. The authors believe that it is very useful to have an error recovery framework to avoid or eliminate the negative effects of the errors.

Sharing of Distributed Geospatial Data through Grid Technology

2010 ◽  
pp. 222-228 ◽  
Author(s):  
Yaxing Wei ◽  
Liping Di ◽  
Guangxuan Liao ◽  
Baohua Zhao ◽  
Aijun Chen ◽  
...  
Keyword(s):  
Large Scale ◽  
Storage Systems ◽  
Distributed Storage ◽  
Geospatial Data ◽  
Grid Technology ◽  
Grid System ◽  
Multiple User ◽  
User Communities ◽  
Distributed Storage Systems ◽  
Critical Requirement

With the rapid accumulation of geospatial data and the advancement of geoscience, there is a critical requirement for an infrastructure that can integrate large-scale, heterogeneous, and distributed storage systems for the sharing of geospatial data within multiple user communities. This article probes into the feasibility to share distributed geospatial data through Grid computing technology by introducing several major issues (including system heterogeneity, uniform mechanism to publish and discover geospatial data, performance, and security) to be faced by geospatial data sharing and how Grid technology can help to solve these issues. Some recent research efforts, such as ESG and the Data Grid system in GMU CSISS, have proven that Grid technology provides a large-scale infrastructure which can seamlessly integrate dispersed geospatial data together and provide uniform and efficient ways to access the data.

Organization for large-scale grid system tests

1958 ◽  
Vol 105 (22) ◽  
pp. 363
Author(s):  
F.H. Last ◽  
E. Mills ◽  
N.D. Norris
Keyword(s):  
Large Scale ◽  
Grid System ◽  
Large Scale Grid ◽  
Scale Grid
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