activity
20162023
most citedAlgebraic multigrid block preconditioning for multi-group radiation diffusion equations

11 citations · 16 across the 6 of their papers we have counts for

collaborators

6 papers

cs.AR2023★ 1 cited

Implementing Performance Portability of High Performance Computing Programs in the New Golden Age of Chip Architecture

Weifeng Liu, Linping Wu, Xiaowen Xu +1

As an important goal of high-performance computing, the concept of performance portability has been around for many years. As the failure of Moore's Law, it is no longer feasible t…

math.NA2023

AutoAMG(): An Auto-tuned AMG Method Based on Deep Learning for Strong Threshold

Haifeng Zou, Xiaowen Xu, Chen-Song Zhang +1

Algebraic Multigrid (AMG) is one of the most used iterative algorithms for solving large sparse linear equations . In AMG, the coarse grid is a key component that affects the…

math.NA2022

Convergence estimation and characteristic analysis of a two-level iterative algorithm for the discretized three-temperature energy linear systems

Yue Hao, Silu Huang, Xiaowen Xu

For solving the discretized three-temperature energy linear systems, Xu et al. proposed a physical-variable based coarsening two-level iterative method (PCTL algorithm) in 2009 and…

math.NA2020★ 11 cited

Algebraic multigrid block preconditioning for multi-group radiation diffusion equations

Xiaoqiang Yue, Shulei Zhang, Xiaowen Xu +2

The paper focuses on developing and studying efficient block preconditioners based on classical algebraic multigrid for the large-scale sparse linear systems arising from the fully…

math.NA2018★ 2 cited

Parallel-in-Time with Fully Finite Element Multigrid for 2-D Space-fractional Diffusion Equations

Xiaoqiang Yue, Shi Shu, Xiaowen Xu +2

The paper investigates a non-intrusive parallel time integration with multigrid for space-fractional diffusion equations in two spatial dimensions. We firstly obtain a fully discre…

stat.CO2016★ 2 cited

Information Splitting for Big Data Analytics

Shengxin Zhu, Tongxiang Gu, Xiaowen Xu +1

Many statistical models require an estimation of unknown (co)-variance parameter(s) in a model. The estimation usually obtained by maximizing a log-likelihood which involves log de…