Wilkinson defined a sparse matrix as one with enough zeros that it pays to take advantage of
them. 1 This informal yet practical definition captures the essence of the goal of direct …

The classification problem is closely related to the clustering problem discussed in Chaps. 6
and 7. While the clustering problem is that of determining similar groups of data points, the …

We describe the University of Florida Sparse Matrix Collection, a large and actively growing
set of sparse matrices that arise in real applications. The Collection is widely used by the …

Supernode partitioning for unsymmetric matrices together with complete block diagonal
supernode pivoting and asynchronous computation can achieve high gigaflop rates for …

In this paper we present a parallel formulation of a multilevel k-way graph partitioning
algorithm. The multilevel k-way partitioning algorithm reduces the size of the graph by …

During the past few years, algorithmic improvements alone have reduced the time required
for the direct solution of unsymmetric sparse systems of linear equations by almost an order …

Delineating the tremendous growth in this area, the Handbook of Approximation Algorithms
and Metaheuristics covers fundamental, theoretical topics as well as advanced, practical …

Traditional graph partitioning algorithms compute a k-way partitioning of a graph such that
the number of edges that are cut by the partitioning is minimized and each partition has an …

Algorithms that find good partitionings of unstructured and irregular graphs are critical for the
efficient execution of scientific simulations on high performance parallel computers. This …

Algorithms for Graph Partitioning: A Survey Page 1 Link oping Electronic Articles in Computer
and Information Science Vol. 3(1998): nr 10 Link oping University Electronic Press Link oping …