33,559 research outputs found
PT-Scotch: A tool for efficient parallel graph ordering
The parallel ordering of large graphs is a difficult problem, because on the
one hand minimum degree algorithms do not parallelize well, and on the other
hand the obtainment of high quality orderings with the nested dissection
algorithm requires efficient graph bipartitioning heuristics, the best
sequential implementations of which are also hard to parallelize. This paper
presents a set of algorithms, implemented in the PT-Scotch software package,
which allows one to order large graphs in parallel, yielding orderings the
quality of which is only slightly worse than the one of state-of-the-art
sequential algorithms. Our implementation uses the classical nested dissection
approach but relies on several novel features to solve the parallel graph
bipartitioning problem. Thanks to these improvements, PT-Scotch produces
consistently better orderings than ParMeTiS on large numbers of processors
Rearranging trees for robust consensus
In this paper, we use the H2 norm associated with a communication graph to
characterize the robustness of consensus to noise. In particular, we restrict
our attention to trees and by systematic attention to the effect of local
changes in topology, we derive a partial ordering for undirected trees
according to the H2 norm. Our approach for undirected trees provides a
constructive method for deriving an ordering for directed trees. Further, our
approach suggests a decentralized manner in which trees can be rearranged in
order to improve their robustness.Comment: Submitted to CDC 201
Weighted graphs defining facets: a connection between stable set and linear ordering polytopes
A graph is alpha-critical if its stability number increases whenever an edge
is removed from its edge set. The class of alpha-critical graphs has several
nice structural properties, most of them related to their defect which is the
number of vertices minus two times the stability number. In particular, a
remarkable result of Lov\'asz (1978) is the finite basis theorem for
alpha-critical graphs of a fixed defect. The class of alpha-critical graphs is
also of interest for at least two topics of polyhedral studies. First,
Chv\'atal (1975) shows that each alpha-critical graph induces a rank inequality
which is facet-defining for its stable set polytope. Investigating a weighted
generalization, Lipt\'ak and Lov\'asz (2000, 2001) introduce critical
facet-graphs (which again produce facet-defining inequalities for their stable
set polytopes) and they establish a finite basis theorem. Second, Koppen (1995)
describes a construction that delivers from any alpha-critical graph a
facet-defining inequality for the linear ordering polytope. Doignon, Fiorini
and Joret (2006) handle the weighted case and thus define facet-defining
graphs. Here we investigate relationships between the two weighted
generalizations of alpha-critical graphs. We show that facet-defining graphs
(for the linear ordering polytope) are obtainable from 1-critical facet-graphs
(linked with stable set polytopes). We then use this connection to derive
various results on facet-defining graphs, the most prominent one being derived
from Lipt\'ak and Lov\'asz's finite basis theorem for critical facet-graphs. At
the end of the paper we offer an alternative proof of Lov\'asz's finite basis
theorem for alpha-critical graphs
Cutwidth: obstructions and algorithmic aspects
Cutwidth is one of the classic layout parameters for graphs. It measures how
well one can order the vertices of a graph in a linear manner, so that the
maximum number of edges between any prefix and its complement suffix is
minimized. As graphs of cutwidth at most are closed under taking
immersions, the results of Robertson and Seymour imply that there is a finite
list of minimal immersion obstructions for admitting a cut layout of width at
most . We prove that every minimal immersion obstruction for cutwidth at
most has size at most .
As an interesting algorithmic byproduct, we design a new fixed-parameter
algorithm for computing the cutwidth of a graph that runs in time , where is the optimum width and is the number of vertices.
While being slower by a -factor in the exponent than the fastest known
algorithm, given by Thilikos, Bodlaender, and Serna in [Cutwidth I: A linear
time fixed parameter algorithm, J. Algorithms, 56(1):1--24, 2005] and [Cutwidth
II: Algorithms for partial -trees of bounded degree, J. Algorithms,
56(1):25--49, 2005], our algorithm has the advantage of being simpler and
self-contained; arguably, it explains better the combinatorics of optimum-width
layouts
The Reverse Cuthill-McKee Algorithm in Distributed-Memory
Ordering vertices of a graph is key to minimize fill-in and data structure
size in sparse direct solvers, maximize locality in iterative solvers, and
improve performance in graph algorithms. Except for naturally parallelizable
ordering methods such as nested dissection, many important ordering methods
have not been efficiently mapped to distributed-memory architectures. In this
paper, we present the first-ever distributed-memory implementation of the
reverse Cuthill-McKee (RCM) algorithm for reducing the profile of a sparse
matrix. Our parallelization uses a two-dimensional sparse matrix decomposition.
We achieve high performance by decomposing the problem into a small number of
primitives and utilizing optimized implementations of these primitives. Our
implementation shows strong scaling up to 1024 cores for smaller matrices and
up to 4096 cores for larger matrices
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