257 research outputs found
A New Implementation and Detailed Study of Breakpoint Analysis
Phylogenies derived from gene order data may prove crucial in answering some fundamental open questions in biomolecular evolution. Yet very few techniques are available for such phylogenetic reconstructions. One method is breakpoint analysis, developed by Blanchette and Sankoff 2 for solving the breakpoint phylogeny.\u27 Our earlier studies 5;6 confirmed the usefulness of this approach, but also found that BPAnalysis, the implementation developed by Sankoff and Blanchette, was too slow to use on all but very small datasets. We report here on a reimplementation of BPAnalysis using the principles of algorithmic engineering. Our faster (by 2 to 3 orders of magnitude) and flexible implementation allowed us to conduct studies on the characteristics of breakpoint analysis, in terms of running time, quality, and robustness, as well as to analyze datasets that had so far been considered out of reach. We report on these findings and also discuss future directions for our new implementation.\u2
Towards Distributed Petascale Computing
In this chapter we will argue that studying such multi-scale multi-science
systems gives rise to inherently hybrid models containing many different
algorithms best serviced by different types of computing environments (ranging
from massively parallel computers, via large-scale special purpose machines to
clusters of PC's) whose total integrated computing capacity can easily reach
the PFlop/s scale. Such hybrid models, in combination with the by now
inherently distributed nature of the data on which the models `feed' suggest a
distributed computing model, where parts of the multi-scale multi-science model
are executed on the most suitable computing environment, and/or where the
computations are carried out close to the required data (i.e. bring the
computations to the data instead of the other way around). We presents an
estimate for the compute requirements to simulate the Galaxy as a typical
example of a multi-scale multi-physics application, requiring distributed
Petaflop/s computational power.Comment: To appear in D. Bader (Ed.) Petascale, Computing: Algorithms and
Applications, Chapman & Hall / CRC Press, Taylor and Francis Grou
Fully-dynamic Approximation of Betweenness Centrality
Betweenness is a well-known centrality measure that ranks the nodes of a
network according to their participation in shortest paths. Since an exact
computation is prohibitive in large networks, several approximation algorithms
have been proposed. Besides that, recent years have seen the publication of
dynamic algorithms for efficient recomputation of betweenness in evolving
networks. In previous work we proposed the first semi-dynamic algorithms that
recompute an approximation of betweenness in connected graphs after batches of
edge insertions.
In this paper we propose the first fully-dynamic approximation algorithms
(for weighted and unweighted undirected graphs that need not to be connected)
with a provable guarantee on the maximum approximation error. The transfer to
fully-dynamic and disconnected graphs implies additional algorithmic problems
that could be of independent interest. In particular, we propose a new upper
bound on the vertex diameter for weighted undirected graphs. For both weighted
and unweighted graphs, we also propose the first fully-dynamic algorithms that
keep track of such upper bound. In addition, we extend our former algorithm for
semi-dynamic BFS to batches of both edge insertions and deletions.
Using approximation, our algorithms are the first to make in-memory
computation of betweenness in fully-dynamic networks with millions of edges
feasible. Our experiments show that they can achieve substantial speedups
compared to recomputation, up to several orders of magnitude
High Performance Computing Applications in Remote Sensing Studies for Land Cover Dynamics
Global and regional land cover studies require the ability to apply complex models on selected subsets of large amounts of multi-sensor and multi-temporal data sets that have been derived from raw instrument measurements using widely accepted pre-processing algorithms. The computational and storage requirements of most such studies far exceed what is possible on a single workstation environment. We have been pursuing a new approach that couples scalable and open distributed heterogeneous hardware with the development of high performance software for processing, indexing, and organizing remotely sensed data. Hierarchical data management tools are used to ingest raw data, create metadata, and organize the archived data so as to automatically achieve computational load balancing among the available nodes and minimize I/O overheads. We illustrate our approach with four specific examples. The first is the development of the first fast operational scheme for the atmospheric correction of Landsat TM scenes, while the second example focuses on image segmentation using a novel hierarchical connected components algorithm. Retrieval of global BRDF (Bidirectional Reflectance Distribution Function) in the red and near infrared wavelengths using four years (1983 to 1986) of Pathfinder AVHRR Land (PAL) data set is the focus of our third example. The fourth example is the development of a hierarchical data organization scheme that allows on-demand processing and retrieval of regional and global AVHRR data sets. Our results show that substantial improvements in computational times can be achieved by using the high performance computing technology
Tooth-surface-specific Effects of Xylitol: Randomized Trial Results
The Xylitol for Adult Caries Trial was a three-year, double-blind, multi-center, randomized clinical trial that evaluated the effectiveness of xylitol vs. placebo lozenges in the prevention of dental caries in caries-active adults. The purpose of this secondary analysis was to investigate whether xylitol lozenges had a differential effect on cumulative caries increments on different tooth surfaces. Participants (ages 21-80 yrs) with at least one follow-up visit (n = 620) were examined at baseline, 12, 24, and 33 months. Negative binomial and zero-inflated negative binomial regression models were used to estimate incidence rate ratios (IRR) for xylitol’s differential effect on cumulative caries increments on root and coronal surfaces and, among coronal surfaces, on smooth (buccal and lingual), occlusal, and proximal surfaces. Participants in the xylitol arm developed 40% fewer root caries lesions (0.23 D2FS/year) than those in the placebo arm (0.38 D2FS/year; IRR = 0.60; 95% CI [0.44, 0.81]; p < .001). There was no statistically significant difference between xylitol and control participants in the incidence of smooth-surface caries (p = .100), occlusal-surface caries (p = .408), or proximal-surface caries (p = .159). Among these caries-active adults, xylitol appears to have a caries-preventive effect on root surfaces (ClinicalTrials.gov NCT00393055)
- …