936,472 research outputs found
Active Width at a Slanted Active Boundary in Directed Percolation
The width W of the active region around an active moving wall in a directed
percolation process diverges at the percolation threshold p_c as W \simeq A
\epsilon^{-\nu_\parallel} \ln(\epsilon_0/\epsilon), with \epsilon=p_c-p,
\epsilon_0 a constant, and \nu_\parallel=1.734 the critical exponent of the
characteristic time needed to reach the stationary state \xi_\parallel \sim
\epsilon^{-\nu_\parallel}. The logarithmic factor arises from screening of
statistically independent needle shaped sub clusters in the active region.
Numerical data confirm this scaling behaviour.Comment: 5 pages, 5 figure
Optimal expression evaluation for data parallel architectures
A data parallel machine represents an array or other composite data structure by allocating one processor (at least conceptually) per data item. A pointwise operation can be performed between two such arrays in unit time, provided their corresponding elements are allocated in the same processors. If the arrays are not aligned in this fashion, the cost of moving one or both of them is part of the cost of the operation. The choice of where to perform the operation then affects this cost. If an expression with several operands is to be evaluated, there may be many choices of where to perform the intermediate operations. An efficient algorithm is given to find the minimum-cost way to evaluate an expression, for several different data parallel architectures. This algorithm applies to any architecture in which the metric describing the cost of moving an array is robust. This encompasses most of the common data parallel communication architectures, including meshes of arbitrary dimension and hypercubes. Remarks are made on several variations of the problem, some of which are solved and some of which remain open
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ExaHDF5: Delivering Efficient Parallel I/O on Exascale Computing Systems
Scientific applications at exascale generate and analyze massive amounts of data. A critical requirement of these applications is the capability to access and manage this data efficiently on exascale systems. Parallel I/O, the key technology enables moving data between compute nodes and storage, faces monumental challenges from new applications, memory, and storage architectures considered in the designs of exascale systems. As the storage hierarchy is expanding to include node-local persistent memory, burst buffers, etc., as well as disk-based storage, data movement among these layers must be efficient. Parallel I/O libraries of the future should be capable of handling file sizes of many terabytes and beyond. In this paper, we describe new capabilities we have developed in Hierarchical Data Format version 5 (HDF5), the most popular parallel I/O library for scientific applications. HDF5 is one of the most used libraries at the leadership computing facilities for performing parallel I/O on existing HPC systems. The state-of-the-art features we describe include: Virtual Object Layer (VOL), Data Elevator, asynchronous I/O, full-featured single-writer and multiple-reader (Full SWMR), and parallel querying. In this paper, we introduce these features, their implementations, and the performance and feature benefits to applications and other libraries
Target Selection by Frontal Cortex During Coordinated Saccadic and Smooth Pursuit Eye Movement
Oculomotor tracking of moving objects is an important component of visually based cognition and planning. Such tracking is achieved by a combination of saccades and smooth pursuit eye movements. In particular, the saccadic and smooth pursuit systems interact to often choose the same target, and to maximize its visibility through time. How do multiple brain regions interact, including frontal cortical areas, to decide the choice of a target among several competing moving stimuli? How is target selection information that is created by a bias (e.g., electrical stimulation) transferred from one movement system to another? These saccade-pursuit interactions are clarified by a new computational neural model, which describes interactions among motion processing areas MT, MST, FPA, DLPN; saccade specification, selection, and planning areas LIP, FEF, SNr, SC; the saccadic generator in the brain stem; and the cerebellum. Model simulations explain a broad range of neuroanatomical and neurophysiological data. These results are in contrast with the simplest parallel model with no interactions between saccades and pursuit than common-target selection and recruitment of shared motoneurons. Actual tracking episodes in primates reveal multiple systematic deviations from predictions of the simplest parallel model, which are explained by the current model.National Science Foundation (SBE-0354378); Office of Naval Research (N00014-01-1-0624
Vision-Based Road Detection in Automotive Systems: A Real-Time Expectation-Driven Approach
The main aim of this work is the development of a vision-based road detection
system fast enough to cope with the difficult real-time constraints imposed by
moving vehicle applications. The hardware platform, a special-purpose massively
parallel system, has been chosen to minimize system production and operational
costs. This paper presents a novel approach to expectation-driven low-level
image segmentation, which can be mapped naturally onto mesh-connected massively
parallel SIMD architectures capable of handling hierarchical data structures.
The input image is assumed to contain a distorted version of a given template;
a multiresolution stretching process is used to reshape the original template
in accordance with the acquired image content, minimizing a potential function.
The distorted template is the process output.Comment: See http://www.jair.org/ for any accompanying file
Regularizing made-to-measure particle models of galaxies
Made-to-measure methods such as the parallel code NMAGIC are powerful tools
to build galaxy models reproducing observational data. They work by adapting
the particle weights in an N-body system until the target observables are well
matched. Here we introduce a moving prior regularization (MPR) method for such
particle models. It is based on determining from the particles a distribution
of priors in phase-space, which are updated in parallel with the weight
adaptation. This method allows one to construct smooth models from noisy data
without erasing global phase-space gradients. We first apply MPR to a spherical
system for which the distribution function can in theory be uniquely recovered
from idealized data. We show that NMAGIC with MPR indeed converges to the true
solution with very good accuracy, independent of the initial particle model.
Compared to the standard weight entropy regularization, biases in the
anisotropy structure are removed and local fluctuations in the intrinsic
distribution function are reduced. We then investigate how the uncertainties in
the inferred dynamical structure increase with less complete and noisier
kinematic data, and how the dependence on the initial particle model also
increases. Finally, we apply the MPR technique to the two
intermediate-luminosity elliptical galaxies NGC 4697 and NGC 3379, obtaining
smoother dynamical models in luminous and dark matter potentials.Comment: 16 pages, 15 figures, 2 tables. Accepted for publication in MNRA
Parallel Implementation of the PHOENIX Generalized Stellar Atmosphere Program. II: Wavelength Parallelization
We describe an important addition to the parallel implementation of our
generalized NLTE stellar atmosphere and radiative transfer computer program
PHOENIX. In a previous paper in this series we described data and task parallel
algorithms we have developed for radiative transfer, spectral line opacity, and
NLTE opacity and rate calculations. These algorithms divided the work spatially
or by spectral lines, that is distributing the radial zones, individual
spectral lines, or characteristic rays among different processors and employ,
in addition task parallelism for logically independent functions (such as
atomic and molecular line opacities). For finite, monotonic velocity fields,
the radiative transfer equation is an initial value problem in wavelength, and
hence each wavelength point depends upon the previous one. However, for
sophisticated NLTE models of both static and moving atmospheres needed to
accurately describe, e.g., novae and supernovae, the number of wavelength
points is very large (200,000--300,000) and hence parallelization over
wavelength can lead both to considerable speedup in calculation time and the
ability to make use of the aggregate memory available on massively parallel
supercomputers. Here, we describe an implementation of a pipelined design for
the wavelength parallelization of PHOENIX, where the necessary data from the
processor working on a previous wavelength point is sent to the processor
working on the succeeding wavelength point as soon as it is known. Our
implementation uses a MIMD design based on a relatively small number of
standard MPI library calls and is fully portable between serial and parallel
computers.Comment: AAS-TeX, 15 pages, full text with figures available at
ftp://calvin.physast.uga.edu/pub/preprints/Wavelength-Parallel.ps.gz ApJ, in
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