7,668 research outputs found
A Quantitative Study of Pure Parallel Processes
In this paper, we study the interleaving -- or pure merge -- operator that
most often characterizes parallelism in concurrency theory. This operator is a
principal cause of the so-called combinatorial explosion that makes very hard -
at least from the point of view of computational complexity - the analysis of
process behaviours e.g. by model-checking. The originality of our approach is
to study this combinatorial explosion phenomenon on average, relying on
advanced analytic combinatorics techniques. We study various measures that
contribute to a better understanding of the process behaviours represented as
plane rooted trees: the number of runs (corresponding to the width of the
trees), the expected total size of the trees as well as their overall shape.
Two practical outcomes of our quantitative study are also presented: (1) a
linear-time algorithm to compute the probability of a concurrent run prefix,
and (2) an efficient algorithm for uniform random sampling of concurrent runs.
These provide interesting responses to the combinatorial explosion problem
Contribution Ă l'Ă©tude de l'Ă©chantillonnage non uniforme dans le domaine de la radio intelligente.
In this work we consider the problem of designing an effective sampling scheme for sparse multi-band signals. Based on previous results on periodic non-uniform sampling (Multi-Coset) and using the well known Non-Uniform Fourier Transform through Bartlett’s method for Power Spectral Density estimation, we propose a new sampling scheme named the Dynamic Single Branch Non-uniform Sampler (DSB-NUS). The idea of the proposed scheme is to reduce the average sampling frequency, the number of samples collected, and consequently the power consumption of the Analog to Digital Converter (ADC). In addition to that our proposed method detects the location of the bands in order to adapt the sampling rate. In this thesis, we show through simulation results that compared to existing multi-coset based samplers, our proposed sampler provides superior performance, both in terms of sampling rate and energy consumption. It is notconstrained by the inflexibility of hardware circuitry and is easily reconfigurable. We also show the effect of the false detection of active bands on the average sampling rate of our new adaptive non-uniform sub-Nyquist sampler scheme.Nous proposons un nouveau schéma d’échantillonnage non uniforme périodique appelé Système d’Échantillonnage Non Uniforme en Radio Intelligente (SENURI). Notre schéma détecte la localisation spectrale des bandes actives dans la bande totale échantillonnée afin de réduire la fréquence moyenne d’échantillonnage, le nombre d’échantillons prélevé et par conséquent la consommation d’énergie au niveau du traitement numérique. La fréquence moyenne d’échantillonnage du SENURI dépend uniquement du nombre de bandes contenues dans le signal d’entrée x(t). Il est nettement plus performant, en termes d’erreur quadratique, qu’une architecture classique d’échantillonnage non uniforme périodique constituée de p branches, lorsque le spectre de x(t) change dynamiquement
Metropolis-Hastings prefetching algorithms
Prefetching is a simple and general method for single-chain parallelisation of the Metropolis-Hastings algorithm based on the idea of evaluating the posterior in parallel and ahead of time. In this paper improved Metropolis-Hastings prefetching algorithms are presented and evaluated. It is shown how to use available information to make better predictions of the future states of the chain and increase the efficiency of prefetching considerably. The optimal acceptance rate for the prefetching random walk Metropolis-Hastings algorithm is obtained for a special case and it is shown to decrease in the number of processors employed. The performance of the algorithms is illustrated using a well-known macroeconomic model. Bayesian estimation of DSGE models, linearly or nonlinearly approximated, is identified as a potential area of application for prefetching methods. The generality of the proposed method, however, suggests that it could be applied in many other contexts as well.Prefetching; Metropolis-Hastings; Parallel Computing; DSGE models; Optimal acceptance rate
Evolutionary Inference via the Poisson Indel Process
We address the problem of the joint statistical inference of phylogenetic
trees and multiple sequence alignments from unaligned molecular sequences. This
problem is generally formulated in terms of string-valued evolutionary
processes along the branches of a phylogenetic tree. The classical evolutionary
process, the TKF91 model, is a continuous-time Markov chain model comprised of
insertion, deletion and substitution events. Unfortunately this model gives
rise to an intractable computational problem---the computation of the marginal
likelihood under the TKF91 model is exponential in the number of taxa. In this
work, we present a new stochastic process, the Poisson Indel Process (PIP), in
which the complexity of this computation is reduced to linear. The new model is
closely related to the TKF91 model, differing only in its treatment of
insertions, but the new model has a global characterization as a Poisson
process on the phylogeny. Standard results for Poisson processes allow key
computations to be decoupled, which yields the favorable computational profile
of inference under the PIP model. We present illustrative experiments in which
Bayesian inference under the PIP model is compared to separate inference of
phylogenies and alignments.Comment: 33 pages, 6 figure
Inferring Species Trees Directly from Biallelic Genetic Markers: Bypassing Gene Trees in a Full Coalescent Analysis
The multi-species coalescent provides an elegant theoretical framework for
estimating species trees and species demographics from genetic markers.
Practical applications of the multi-species coalescent model are, however,
limited by the need to integrate or sample over all gene trees possible for
each genetic marker. Here we describe a polynomial-time algorithm that computes
the likelihood of a species tree directly from the markers under a finite-sites
model of mutation, effectively integrating over all possible gene trees. The
method applies to independent (unlinked) biallelic markers such as well-spaced
single nucleotide polymorphisms (SNPs), and we have implemented it in SNAPP, a
Markov chain Monte-Carlo sampler for inferring species trees, divergence dates,
and population sizes. We report results from simulation experiments and from an
analysis of 1997 amplified fragment length polymorphism (AFLP) loci in 69
individuals sampled from six species of {\em Ourisia} (New Zealand native
foxglove)
On the enumeration of closures and environments with an application to random generation
Environments and closures are two of the main ingredients of evaluation in
lambda-calculus. A closure is a pair consisting of a lambda-term and an
environment, whereas an environment is a list of lambda-terms assigned to free
variables. In this paper we investigate some dynamic aspects of evaluation in
lambda-calculus considering the quantitative, combinatorial properties of
environments and closures. Focusing on two classes of environments and
closures, namely the so-called plain and closed ones, we consider the problem
of their asymptotic counting and effective random generation. We provide an
asymptotic approximation of the number of both plain environments and closures
of size . Using the associated generating functions, we construct effective
samplers for both classes of combinatorial structures. Finally, we discuss the
related problem of asymptotic counting and random generation of closed
environemnts and closures
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