.png){kind=icon}
返回
Reordering sparse matrices into block-diagonal column-overlapped form
.png){kind=icon}
PRE
AI
DOI：10.1016/j.jpdc.2020.03.002.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Many scientific and engineering applications necessitate computing the minimum norm solution of a sparse underdetermined linear system of equations. The minimum 2-norm solution of such systems can be obtained by a recent parallel algorithm, whose numerical effectiveness and parallel scalability are validated in both shared- and distributed-memory architectures. This parallel algorithm assumes the coefficient matrix in a block-diagonal column-overlapped (BDCO) form, which is a variant of the block-diagonal form where the successive diagonal blocks may overlap along their columns. The total overlap size of the BDCO form is an important metric in the performance of the subject parallel algorithm since it determines the size of the reduced system, solution of which is a bottleneck operation in the parallel algorithm. In this work, we propose a hypergraph partitioning model for reordering sparse matrices into BDCO form with the objective of minimizing the total overlap size and the constraint of maintaining balance on the number of nonzeros of the diagonal blocks. Our model makes use of existing partitioning tools that support fixed vertices in the recursive bipartitioning paradigm. Experimental results validate the use of our model as it achieves small overlap size and balanced diagonal blocks. (C) 2020 Elsevier Inc. All rights reserved.
Keyword:
Underdetermined systems
Sparse matrices
Block-diagonal form
Column overlap
Hypergraph partitioning
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
4
论文数:
3.8K
被引数:
4.8K
机构
引用论文
.png){kind=icon}
分享收藏La metáfora energética del ser humano y su incidencia en el auge de la neurastenia, la neurosis y la depresión人类能量隐喻及其对神经衰弱、神经症和抑郁症兴起的影晌
OAAI
OAAI分享收藏
查看更多内容