GLU3.0: Fast GPU-based Parallel Sparse LU Factorization for Circuit Simulation
Shaoyi Peng, Sheldon X.-D. Tan · IEEE Design and Test · 2020
Editor's note: Many scientific computing problems, including circuit simulations, rely on efficient lower-upper (LU) decomposition of sparse matrices. Prior studies took advantage of GPUs to parallelize LU decomposition, but they suffer from nontrivial data dependencies. This article presents a new method, called GLU3.0, to accelerate GPU-based sparse LU factorization. -Umit Ogras, Arizona State University.