Parallelization Efficiency of Multi-GPU In-Core LU-Decomposition of Dense Matrices

Acceleration of in-core LU decomposition of a dense MoM matrix by using multiple GPUs in parallel, is presented in this paper. Results for nonsymmetrical and symmetrical matrices are shown. Limitations for further increasing the parallelization efficiency and the ways for overcoming these limitations are discussed. The achieved acceleration efficiency is high (about 65%), but remains limited by the speed of data transfers between CPU RAM and GPUs VRAM.