<b><i>Purpose:</i></b> The purpose of this study was to identify factors associated with the initiation or continuation systemic treatment after brain irradiation. outcome interest a utilization rate at least 75%, given that active extracranial disease is common in patients metastases. If left untreated, limits survival, regardless successful local In context, therapy ha...

The partitioning of an adaptive grid for distribution over parallel processors is considered in the context of adaptive multilevel methods for solving partial differential equations. A partitioning method based on the refinement-tree is presented. This method applies to most types of grids in two and three dimensions. For triangular and tetrahedral grids, it is guaranteed to produce connected p...

In this paper we prove two results on partitioning the edges of a planar graph into two partial k-trees, for fixed values of k. Interest in this class of partitioning problems arises since many intractable graph and network problems admit polynomial time solutions on k-trees and their subgraphs (partial k-trees). The first result shows that every planar graph is a union of two partial 3-trees. ...

Parallel graph partitioning is a difficult issue, because the best sequential graph partitioning methods known to date are based on iterative local optimization algorithms that do not parallelize nor scale well. On the other hand, evolutionary algorithms are highly parallel and scalable, but converge very slowly as problem size increases. This paper presents methods that can be used to reduce p...

We consider how to distribute sparse matrices among processes to reduce communication costs in parallel sparse matrix computations, specifically, sparse matrix-vector multiplication. Our main contributions are: (i) an exact graph model for communication with general (two-dimensional) matrix distribution, and (ii) a recursive partitioning algorithm based on nested dissection (substructuring). We...

Parallel graph partitioning is a di cult issue, because the best sequential graph partitioning methods known to date are based on iterative local optimization algorithms that do not parallelize nor scale well. On the other hand, evolutionary algorithms are highly parallel and scalable, but converge very slowly as problem size increases. This paper presents methods that can be used to reduce pro...