ACM Transactions on Mathematical Software (TOMS)
The three R's of engineering analysis and error estimation and adaptivity
Computer Methods in Applied Mechanics and Engineering
SIAM Journal on Scientific and Statistical Computing
Scientific computing: an introduction with parallel computing
Scientific computing: an introduction with parallel computing
Smoothed particle hydrodynamics stability analysis
Journal of Computational Physics
Error estimates for interpolation by compactly supported radial basis functions of minimal degree
Journal of Approximation Theory
Designing and Building Parallel Programs: Concepts and Tools for Parallel Software Engineering
Designing and Building Parallel Programs: Concepts and Tools for Parallel Software Engineering
MPI: The Complete Reference
Scientific Computing: An Introductory Survey
Scientific Computing: An Introductory Survey
A parallelized meshfree method with boundary enrichment for large-scale CFD
Journal of Computational Physics
SuperLU_DIST: A scalable distributed-memory sparse direct solver for unsymmetric linear systems
ACM Transactions on Mathematical Software (TOMS)
Handbook of Mathematical Functions, With Formulas, Graphs, and Mathematical Tables,
Handbook of Mathematical Functions, With Formulas, Graphs, and Mathematical Tables,
Geometric Data Structures for Computer Graphics
Geometric Data Structures for Computer Graphics
Review: Meshless methods: A review and computer implementation aspects
Mathematics and Computers in Simulation
Parallel performance of large scale impact simulations on Linux cluster super computer
Computers and Structures
Parallel performances of a multigrid poisson solver
ISPDC'03 Proceedings of the Second international conference on Parallel and distributed computing
Super linear speedup in a local parallel meshless solution of thermo-fluid problems
Computers and Structures
Solving numerical difficulties for element-free Galerkin analyses
Computational Mechanics
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The computational complexity of the meshless local Petrov-Galerkin method (MLPG) has been analyzed and compared with the finite difference (FDM) and finite element methods (FEM) from the user point of view. Theoretically, MLPG is the most complex of the three methods. Experimental results show that MLPG, with appropriately selected integration order and dimensions of support and quadrature domains, achieves similar accuracy to that of FEM. The measurements of parallel complexity and speed-up indicate that parallel MLPG scales well on larger systems. The normalized computational complexity makes FEM the best choice. MLPG remains competitive if human assistance is needed for meshing.