85,156 research outputs found
Task-based Augmented Contour Trees with Fibonacci Heaps
This paper presents a new algorithm for the fast, shared memory, multi-core
computation of augmented contour trees on triangulations. In contrast to most
existing parallel algorithms our technique computes augmented trees, enabling
the full extent of contour tree based applications including data segmentation.
Our approach completely revisits the traditional, sequential contour tree
algorithm to re-formulate all the steps of the computation as a set of
independent local tasks. This includes a new computation procedure based on
Fibonacci heaps for the join and split trees, two intermediate data structures
used to compute the contour tree, whose constructions are efficiently carried
out concurrently thanks to the dynamic scheduling of task parallelism. We also
introduce a new parallel algorithm for the combination of these two trees into
the output global contour tree. Overall, this results in superior time
performance in practice, both in sequential and in parallel thanks to the
OpenMP task runtime. We report performance numbers that compare our approach to
reference sequential and multi-threaded implementations for the computation of
augmented merge and contour trees. These experiments demonstrate the run-time
efficiency of our approach and its scalability on common workstations. We
demonstrate the utility of our approach in data segmentation applications
A multi-scale, multi-wavelength source extraction method: getsources
We present a multi-scale, multi-wavelength source extraction algorithm called
getsources. Although it has been designed primarily for use in the far-infrared
surveys of Galactic star-forming regions with Herschel, the method can be
applied to many other astronomical images. Instead of the traditional approach
of extracting sources in the observed images, the new method analyzes fine
spatial decompositions of original images across a wide range of scales and
across all wavebands. It cleans those single-scale images of noise and
background, and constructs wavelength-independent single-scale detection images
that preserve information in both spatial and wavelength dimensions. Sources
are detected in the combined detection images by following the evolution of
their segmentation masks across all spatial scales. Measurements of the source
properties are done in the original background-subtracted images at each
wavelength; the background is estimated by interpolation under the source
footprints and overlapping sources are deblended in an iterative procedure. In
addition to the main catalog of sources, various catalogs and images are
produced that aid scientific exploitation of the extraction results. We
illustrate the performance of getsources on Herschel images by extracting
sources in sub-fields of the Aquila and Rosette star-forming regions. The
source extraction code and validation images with a reference extraction
catalog are freely available.Comment: 31 pages, 27 figures, to be published in Astronomy & Astrophysic
Algorithms For Extracting Timeliness Graphs
We consider asynchronous message-passing systems in which some links are
timely and processes may crash. Each run defines a timeliness graph among
correct processes: (p; q) is an edge of the timeliness graph if the link from p
to q is timely (that is, there is bound on communication delays from p to q).
The main goal of this paper is to approximate this timeliness graph by graphs
having some properties (such as being trees, rings, ...). Given a family S of
graphs, for runs such that the timeliness graph contains at least one graph in
S then using an extraction algorithm, each correct process has to converge to
the same graph in S that is, in a precise sense, an approximation of the
timeliness graph of the run. For example, if the timeliness graph contains a
ring, then using an extraction algorithm, all correct processes eventually
converge to the same ring and in this ring all nodes will be correct processes
and all links will be timely. We first present a general extraction algorithm
and then a more specific extraction algorithm that is communication efficient
(i.e., eventually all the messages of the extraction algorithm use only links
of the extracted graph)
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