13,537 research outputs found
A Message-Passing Algorithm for Counting Short Cycles in a Graph
A message-passing algorithm for counting short cycles in a graph is
presented. For bipartite graphs, which are of particular interest in coding,
the algorithm is capable of counting cycles of length g, g +2,..., 2g - 2,
where g is the girth of the graph. For a general (non-bipartite) graph, cycles
of length g; g + 1, ..., 2g - 1 can be counted. The algorithm is based on
performing integer additions and subtractions in the nodes of the graph and
passing extrinsic messages to adjacent nodes. The complexity of the proposed
algorithm grows as , where is the number of edges in the
graph. For sparse graphs, the proposed algorithm significantly outperforms the
existing algorithms in terms of computational complexity and memory
requirements.Comment: Submitted to IEEE Trans. Inform. Theory, April 21, 2010
Deterministically Isolating a Perfect Matching in Bipartite Planar Graphs
We present a deterministic way of assigning small (log bit) weights to the
edges of a bipartite planar graph so that the minimum weight perfect matching
becomes unique. The isolation lemma as described in (Mulmuley et al. 1987)
achieves the same for general graphs using a randomized weighting scheme,
whereas we can do it deterministically when restricted to bipartite planar
graphs. As a consequence, we reduce both decision and construction versions of
the matching problem to testing whether a matrix is singular, under the promise
that its determinant is 0 or 1, thus obtaining a highly parallel SPL algorithm
for bipartite planar graphs. This improves the earlier known bounds of
non-uniform SPL by (Allender et al. 1999) and by (Miller and Naor 1995,
Mahajan and Varadarajan 2000). It also rekindles the hope of obtaining a
deterministic parallel algorithm for constructing a perfect matching in
non-bipartite planar graphs, which has been open for a long time. Our
techniques are elementary and simple
Fourier Domain Decoding Algorithm of Non-Binary LDPC codes for Parallel Implementation
For decoding non-binary low-density parity check (LDPC) codes,
logarithm-domain sum-product (Log-SP) algorithms were proposed for reducing
quantization effects of SP algorithm in conjunction with FFT. Since FFT is not
applicable in the logarithm domain, the computations required at check nodes in
the Log-SP algorithms are computationally intensive. What is worth, check nodes
usually have higher degree than variable nodes. As a result, most of the time
for decoding is used for check node computations, which leads to a bottleneck
effect. In this paper, we propose a Log-SP algorithm in the Fourier domain.
With this algorithm, the role of variable nodes and check nodes are switched.
The intensive computations are spread over lower-degree variable nodes, which
can be efficiently calculated in parallel. Furthermore, we develop a fast
calculation method for the estimated bits and syndromes in the Fourier domain.Comment: To appear in IEICE Trans. Fundamentals, vol.E93-A, no.11 November
201
Distributed Triangle Counting in the Graphulo Matrix Math Library
Triangle counting is a key algorithm for large graph analysis. The Graphulo
library provides a framework for implementing graph algorithms on the Apache
Accumulo distributed database. In this work we adapt two algorithms for
counting triangles, one that uses the adjacency matrix and another that also
uses the incidence matrix, to the Graphulo library for server-side processing
inside Accumulo. Cloud-based experiments show a similar performance profile for
these different approaches on the family of power law Graph500 graphs, for
which data skew increasingly bottlenecks. These results motivate the design of
skew-aware hybrid algorithms that we propose for future work.Comment: Honorable mention in the 2017 IEEE HPEC's Graph Challeng
A Multi-Core Solver for Parity Games
We describe a parallel algorithm for solving parity games,\ud
with applications in, e.g., modal mu-calculus model\ud
checking with arbitrary alternations, and (branching) bisimulation\ud
checking. The algorithm is based on Jurdzinski's Small Progress\ud
Measures. Actually, this is a class of algorithms, depending on\ud
a selection heuristics.\ud
\ud
Our algorithm operates lock-free, and mostly wait-free (except for\ud
infrequent termination detection), and thus allows maximum\ud
parallelism. Additionally, we conserve memory by avoiding storage\ud
of predecessor edges for the parity graph through strictly\ud
forward-looking heuristics.\ud
\ud
We evaluate our multi-core implementation's behaviour on parity games\ud
obtained from mu-calculus model checking problems for a set of\ud
communication protocols, randomly generated problem instances, and\ud
parametric problem instances from the literature.\ud
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