5,760 research outputs found
Dimension improvement in Dhar's refutation of the Eden conjecture
We consider the Eden model on the d-dimensional hypercubical unoriented
lattice , for large d. Initially, every lattice point is healthy, except the
origin which is infected. Then, each infected lattice point contaminates any of
its neighbours with rate 1. The Eden model is equivalent to first passage
percolation, with exponential passage times on edges. The Eden conjecture
states that the limit shape of the Eden model is a Euclidean ball. By putting
the computations of Dhar [Dha88] a little further with modern computers and
efficient implementation we obtain improved bounds for the speed of infection.
This shows that the Eden conjecture does not hold in dimension superior to 22
(the lower known dimension was 35)
Advances in the Design and Implementation of a Multi-Tier Architecture in the GIPSY Environment
We present advances in the software engineering design and implementation of
the multi-tier run-time system for the General Intensional Programming System
(GIPSY) by further unifying the distributed technologies used to implement the
Demand Migration Framework (DMF) in order to streamline distributed execution
of hybrid intensional-imperative programs using Java.Comment: 11 pages, 3 figure
Bayesian nonparametric Plackett-Luce models for the analysis of preferences for college degree programmes
In this paper we propose a Bayesian nonparametric model for clustering
partial ranking data. We start by developing a Bayesian nonparametric extension
of the popular Plackett-Luce choice model that can handle an infinite number of
choice items. Our framework is based on the theory of random atomic measures,
with the prior specified by a completely random measure. We characterise the
posterior distribution given data, and derive a simple and effective Gibbs
sampler for posterior simulation. We then develop a Dirichlet process mixture
extension of our model and apply it to investigate the clustering of
preferences for college degree programmes amongst Irish secondary school
graduates. The existence of clusters of applicants who have similar preferences
for degree programmes is established and we determine that subject matter and
geographical location of the third level institution characterise these
clusters.Comment: Published in at http://dx.doi.org/10.1214/14-AOAS717 the Annals of
Applied Statistics (http://www.imstat.org/aoas/) by the Institute of
Mathematical Statistics (http://www.imstat.org
A Protocol for the Atomic Capture of Multiple Molecules at Large Scale
With the rise of service-oriented computing, applications are more and more
based on coordination of autonomous services. Envisioned over largely
distributed and highly dynamic platforms, expressing this coordination calls
for alternative programming models. The chemical programming paradigm, which
models applications as chemical solutions where molecules representing digital
entities involved in the computation, react together to produce a result, has
been recently shown to provide the needed abstractions for autonomic
coordination of services. However, the execution of such programs over large
scale platforms raises several problems hindering this paradigm to be actually
leveraged. Among them, the atomic capture of molecules participating in concur-
rent reactions is one of the most significant. In this paper, we propose a
protocol for the atomic capture of these molecules distributed and evolving
over a large scale platform. As the density of possible reactions is crucial
for the liveness and efficiency of such a capture, the protocol proposed is
made up of two sub-protocols, each of them aimed at addressing different levels
of densities of potential reactions in the solution. While the decision to
choose one or the other is local to each node participating in a program's
execution, a global coherent behaviour is obtained. Proof of liveness, as well
as intensive simulation results showing the efficiency and limited overhead of
the protocol are given.Comment: 13th International Conference on Distributed Computing and Networking
(2012
A job response time prediction method for production Grid computing environments
A major obstacle to the widespread adoption of Grid Computing in both the scientific
community and industry sector is the difficulty of knowing in advance a job submission running
cost that can be used to plan a correct allocation of resources.
Traditional distributed computing solutions take advantage of homogeneous and open
environments to propose prediction methods that use a detailed analysis of the hardware and
software components. However, production Grid computing environments, which are large and
use a complex and dynamic set of resources, present a different challenge. In Grid computing
the source code of applications, programme libraries, and third-party software are not always
available. In addition, Grid security policies may not agree to run hardware or software analysis
tools to generate Grid components models.
The objective of this research is the prediction of a job response time in production Grid
computing environments. The solution is inspired by the concept of predicting future Grid
behaviours based on previous experiences learned from heterogeneous Grid workload trace
data. The research objective was selected with the aim of improving the Grid resource usability
and the administration of Grid environments. The predicted data can be used to allocate
resources in advance and inform forecasted finishing time and running costs before submission.
The proposed Grid Computing Response Time Prediction (GRTP) method implements
several internal stages where the workload traces are mined to produce a response time
prediction for a given job. In addition, the GRTP method assesses the predicted result against
the actual target jobâs response time to inference information that is used to tune the methods
setting parameters.
The GRTP method was implemented and tested using a cross-validation technique to assess
how the proposed solution generalises to independent data sets. The training set was taken from
the Grid environment DAS (Distributed ASCI Supercomputer). The two testing sets were taken
from AuverGrid and Grid5000 Grid environments
Three consecutive tests assuming stable jobs, unstable jobs, and using a job type method to
select the most appropriate prediction function were carried out. The tests offered a significant
increase in prediction performance for data mining based methods applied in Grid computing
environments. For instance, in Grid5000 the GRTP method answered 77 percent of job
prediction requests with an error of less than 10 percent. While in the same environment, the most effective and accurate method using workload traces was only able to predict 32 percent of
the cases within the same range of error.
The GRTP method was able to handle unexpected changes in resources and services which
affect the job response time trends and was able to adapt to new scenarios. The tests showed
that the proposed GRTP method is capable of predicting job response time requests and it also
improves the prediction quality when compared to other current solutions
Towards Causal Effect Estimation of Emotional Labeling of Watched Videos
Emotions play a crucial role in human life, they are measured using many approaches. There are also many methodologies for emotion elicitation. Emotion elicitation through video watching is one important approach used to create emotion datasets. However, the causation link between video content and elicited emotions was not well explained by scientific research. In this article, we present an approach for computing the causal effect of video content on elicited emotion. The Do-Calculus theory was employed for computing causal inference, and a SCM (Structured Causal Model) was proposed considering the following variables: EEG signal, age, gender, video content, like/dislike, and emotional quadrant. To evaluate the approach, EEG data were collected from volunteers watching a sample of videos from the LIRIS-ACCEDE dataset. A total of 48 causal effects was statistically evaluated in order to check the causal impact of age, gender, and video content on liking and emotion. The results show that the approach can be generalized for any dataset that contains the variables of the proposed SCM. Furthermore, the proposed approach can be applied to any other similar dataset if an appropriate SCM is provided
Kranc: a Mathematica application to generate numerical codes for tensorial evolution equations
We present a suite of Mathematica-based computer-algebra packages, termed
"Kranc", which comprise a toolbox to convert (tensorial) systems of partial
differential evolution equations to parallelized C or Fortran code. Kranc can
be used as a "rapid prototyping" system for physicists or mathematicians
handling very complicated systems of partial differential equations, but
through integration into the Cactus computational toolkit we can also produce
efficient parallelized production codes. Our work is motivated by the field of
numerical relativity, where Kranc is used as a research tool by the authors. In
this paper we describe the design and implementation of both the Mathematica
packages and the resulting code, we discuss some example applications, and
provide results on the performance of an example numerical code for the
Einstein equations.Comment: 24 pages, 1 figure. Corresponds to journal versio
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