Iterative Solver for Linear System Obtained by Edge Element: Variable Preconditioned Method With Mixed Precision on GPU

High Performance Computing of Meshless Time Domain Method on Multi-GPU Cluster

“…Each Rank is associated a cell, and data are communicated between neighboring cells using Peer to Peer communication (GPU Direct) to reduce the communication time [5]. Note that PML calculation is achieved at same time of data communication for overlapped region to hide the transmission time of the data.…”

The Parallelized Automatic Mesh Generation Using Dynamic Bubble System With GPGPU

“…The GPGPU shows so high performance of a parallel computing that it can shorten the computation time of the bubbles' movement mentioned above. So far, a few solvers with GPGPU for FEA have been proposed [5]- [8], however a method of mesh generation with GPU has not been reported yet.…”

Computação paralela em GPU para resolução de sistemas de equações algébricas resultantes da aplicação do método de elementos finitos em eletromagnetismo.

“…Thenceforth, GPUs have been used successfully for solving large-scale sparse linear systems of algebraic equations arising in the FEA of 3D Electromagnetic phenomena [3], especially in parallel implementations of Krylov subspace iterative methods, the class of methods that are the most widespread for solving systems generated by partial differential equations (PDE) [14].…”

“…There are several works which attempt to optimize the PCG method [12], [13], [14]. In the first one, the authors analyze the performance of the GPU using the Incomplete Cholesky CG method (ICCG) and incomplete LU (ILU) preconditioned GMRES method.…”

“…The second one presents an ICCG implementation optimized on both multi-core and GPU architectures by using domain decomposition. In [14], the authors implemented a variable preconditioned Krylov subspace method with mixed precision on GPU for solving the linear system obtained from the edge finite element formulation in steady state. The execution times of various VP Krylov subspace methods using Single-GPU and Multi-GPU were analyzed.…”