Large sparse linear systems of equations are ubiquitous in science, engineering and
beyond. This open access monograph focuses on factorization algorithms for solving such …

The computation of matrix functions f(A), or related quantities like their trace, is an important
but challenging task, in particular, for large and sparse matrices A. In recent years, probing …

Deep graph generative modeling has proven capable of learning the distribution of complex,
multi-scale structures characterizing real-world graphs. However, one of the main limitations …

This paper is concerned with applying bandwidth and profile reduction reordering
algorithms prior to computing an incomplete Cholesky factorization and using this as a …

This paper considers the bandwidth reduction problem for large-scale matrices in serial
computations. A heuristic for bandwidth reduction reorders the rows and columns of a given …

This paper proposes a novel ant colony hyperheuristic approach for reordering the rows and
columns of symmetric positive definite matrices. This ant colony hyperheuristic approach …

This paper studies the bandwidth reduction problem for large-scale sparse matrices in serial
computations. A heuristic for bandwidth reduction reorders the rows and columns of a given …

Abstract The Graph Bandwidth Problem is a well-known and important graph layout problem
with a large number of applications in scientific and engineering fields. The problem is …

This paper studies heuristics for the bandwidth reduction of large-scale matrices in serial
computations. Bandwidth optimization is a demanding subject for a large number of …

In this work, four heuristics for bandwidth and profile reductions are evaluated. Specifically,
the results of a recent proposed heuristic for bandwidth and profile reductions of symmetric …