235,384 research outputs found
The Localized Reduced Basis Multiscale method for two-phase flows in porous media
In this work, we propose a novel model order reduction approach for two-phase
flow in porous media by introducing a formulation in which the mobility, which
realizes the coupling between phase saturations and phase pressures, is
regarded as a parameter to the pressure equation. Using this formulation, we
introduce the Localized Reduced Basis Multiscale method to obtain a
low-dimensional surrogate of the high-dimensional pressure equation. By
applying ideas from model order reduction for parametrized partial differential
equations, we are able to split the computational effort for solving the
pressure equation into a costly offline step that is performed only once and an
inexpensive online step that is carried out in every time step of the two-phase
flow simulation, which is thereby largely accelerated. Usage of elements from
numerical multiscale methods allows us to displace the computational intensity
between the offline and online step to reach an ideal runtime at acceptable
error increase for the two-phase flow simulation
Particle Swarm Optimization: A survey of historical and recent developments with hybridization perspectives
Particle Swarm Optimization (PSO) is a metaheuristic global optimization
paradigm that has gained prominence in the last two decades due to its ease of
application in unsupervised, complex multidimensional problems which cannot be
solved using traditional deterministic algorithms. The canonical particle swarm
optimizer is based on the flocking behavior and social co-operation of birds
and fish schools and draws heavily from the evolutionary behavior of these
organisms. This paper serves to provide a thorough survey of the PSO algorithm
with special emphasis on the development, deployment and improvements of its
most basic as well as some of the state-of-the-art implementations. Concepts
and directions on choosing the inertia weight, constriction factor, cognition
and social weights and perspectives on convergence, parallelization, elitism,
niching and discrete optimization as well as neighborhood topologies are
outlined. Hybridization attempts with other evolutionary and swarm paradigms in
selected applications are covered and an up-to-date review is put forward for
the interested reader.Comment: 34 pages, 7 table
A Survey on Temporal Logics
This paper surveys main and recent studies on temporal logics in a broad
sense by presenting various logic systems, dealing with various time
structures, and discussing important features, such as decidability (or
undecidability) results, expressiveness and proof systems
Non-Linear Phase-Shifting of Haar Wavelets for Run-Time All-Frequency Lighting
This paper focuses on real-time all-frequency image-based rendering using an
innovative solution for run-time computation of light transport. The approach
is based on new results derived for non-linear phase shifting in the Haar
wavelet domain. Although image-based methods for real-time rendering of dynamic
glossy objects have been proposed, they do not truly scale to all possible
frequencies and high sampling rates without trading storage, glossiness, or
computational time, while varying both lighting and viewpoint. This is due to
the fact that current approaches are limited to precomputed radiance transfer
(PRT), which is prohibitively expensive in terms of memory requirements and
real-time rendering when both varying light and viewpoint changes are required
together with high sampling rates for high frequency lighting of glossy
material. On the other hand, current methods cannot handle object rotation,
which is one of the paramount issues for all PRT methods using wavelets. This
latter problem arises because the precomputed data are defined in a global
coordinate system and encoded in the wavelet domain, while the object is
rotated in a local coordinate system. At the root of all the above problems is
the lack of efficient run-time solution to the nontrivial problem of rotating
wavelets (a non-linear phase-shift), which we solve in this paper
A Survey on Mobile Edge Networks: Convergence of Computing, Caching and Communications
As the explosive growth of smart devices and the advent of many new
applications, traffic volume has been growing exponentially. The traditional
centralized network architecture cannot accommodate such user demands due to
heavy burden on the backhaul links and long latency. Therefore, new
architectures which bring network functions and contents to the network edge
are proposed, i.e., mobile edge computing and caching. Mobile edge networks
provide cloud computing and caching capabilities at the edge of cellular
networks. In this survey, we make an exhaustive review on the state-of-the-art
research efforts on mobile edge networks. We first give an overview of mobile
edge networks including definition, architecture and advantages. Next, a
comprehensive survey of issues on computing, caching and communication
techniques at the network edge is presented respectively. The applications and
use cases of mobile edge networks are discussed. Subsequently, the key enablers
of mobile edge networks such as cloud technology, SDN/NFV and smart devices are
discussed. Finally, open research challenges and future directions are
presented as well
Ultimate physical limits to computation
Computers are physical systems: what they can and cannot do is dictated by
the laws of physics. In particular, the speed with which a physical device can
process information is limited by its energy and the amount of information that
it can process is limited by the number of degrees of freedom it possesses.
This paper explores the physical limits of computation as determined by the
speed of light , the quantum scale and the gravitational constant
. As an example, quantitative bounds are put to the computational power of
an `ultimate laptop' with a mass of one kilogram confined to a volume of one
liter.Comment: 22 pages, plain TeX, submitted to Nature, replaced to incorporate
additional content and reference
Distributed Sensor Selection using a Truncated Newton Method
We propose a new distributed algorithm for computing a truncated Newton
method, where the main diagonal of the Hessian is computed using belief
propagation. As a case study for this approach, we examine the sensor selection
problem, a Boolean convex optimization problem. We form two distributed
algorithms. The first algorithm is a distributed version of the interior point
method by Joshi and Boyd, and the second algorithm is an order of magnitude
faster approximation. As an example application we discuss distributed anomaly
detection in networks. We demonstrate the applicability of our solution using
both synthetic data and real traffic logs collected from the Abilene Internet
backbone.Comment: Submitted for publicatio
Omega and the time evolution of the N-body problem
The series solution of the behavior of a finite number of physical bodies and
Chaitin's Omega number share quasi-algorithmic expressions; yet both lack a
computable radius of convergence.Comment: Contribution to the collection of papers "Randomness and Complexity,
from Leibniz to Chaitin," ed. by Cristian S. Calud
Chapter 10: Algebraic Algorithms
Our Chapter in the upcoming Volume I: Computer Science and Software
Engineering of Computing Handbook (Third edition), Allen Tucker, Teo Gonzales
and Jorge L. Diaz-Herrera, editors, covers Algebraic Algorithms, both symbolic
and numerical, for matrix computations and root-finding for polynomials and
systems of polynomials equations. We cover part of these large subjects and
include basic bibliography for further study. To meet space limitation we cite
books, surveys, and comprehensive articles with pointers to further references,
rather than including all the original technical papers.Comment: 41.1 page
PARAVT: Parallel Voronoi Tessellation code
We present a new open source code for massive parallel computation of Voronoi
tessellations(VT hereafter) in large data sets. The code is focused for
astrophysical purposes where VT densities and neighbors are widely used. There
are several serial Voronoi tessellation codes, however no open source and
parallel implementations are available to handle the large number of
particles/galaxies in current N-body simulations and sky surveys.
Parallelization is implemented under MPI and VT using Qhull library. Domain
decomposition takes into account consistent boundary computation between tasks,
and includes periodic conditions. In addition, the code computes neighbors
list, Voronoi density, Voronoi cell volume, density gradient for each particle,
and densities on a regular grid.Comment: Accepted for publication in Astronomy and Computing. Code available
at https://github.com/regonzar/parav
- …