79,051 research outputs found
Montage: a grid portal and software toolkit for science-grade astronomical image mosaicking
Montage is a portable software toolkit for constructing custom, science-grade
mosaics by composing multiple astronomical images. The mosaics constructed by
Montage preserve the astrometry (position) and photometry (intensity) of the
sources in the input images. The mosaic to be constructed is specified by the
user in terms of a set of parameters, including dataset and wavelength to be
used, location and size on the sky, coordinate system and projection, and
spatial sampling rate. Many astronomical datasets are massive, and are stored
in distributed archives that are, in most cases, remote with respect to the
available computational resources. Montage can be run on both single- and
multi-processor computers, including clusters and grids. Standard grid tools
are used to run Montage in the case where the data or computers used to
construct a mosaic are located remotely on the Internet. This paper describes
the architecture, algorithms, and usage of Montage as both a software toolkit
and as a grid portal. Timing results are provided to show how Montage
performance scales with number of processors on a cluster computer. In
addition, we compare the performance of two methods of running Montage in
parallel on a grid.Comment: 16 pages, 11 figure
A single-chip FPGA implementation of real-time adaptive background model
This paper demonstrates the use of a single-chip
FPGA for the extraction of highly accurate background
models in real-time. The models are based
on 24-bit RGB values and 8-bit grayscale intensity
values. Three background models are presented, all
using a camcorder, single FPGA chip, four blocks
of RAM and a display unit. The architectures have
been implemented and tested using a Panasonic NVDS60B
digital video camera connected to a Celoxica
RC300 Prototyping Platform with a Xilinx Virtex
II XC2v6000 FPGA and 4 banks of onboard RAM.
The novel FPGA architecture presented has the advantages
of minimizing latency and the movement of
large datasets, by conducting time critical processes
on BlockRAM. The systems operate at clock rates
ranging from 57MHz to 65MHz and are capable
of performing pre-processing functions like temporal
low-pass filtering on standard frame size of 640X480
pixels at up to 210 frames per second
A New Approach to Configurable Dynamic Scheduling in Clusters based on Single System Image Technologies
Clusters are now considered as an alternative to parallel machines to execute workloads made up of sequential and/or parallel applications. For efficient application execution on clusters, dynamic global process scheduling is of prime importance. Different dynamic scheduling policies that have been studied for distributed systems or parallel machines may be used in clusters. The choice of a particular policy depends on the kind of workload to be executed. In a cluster, it is thus highly desirable to implement a configurable global scheduler to be able to adapt the dynamic scheduling policy to the workload characteristics, to take benefit of all cluster resources and tocope with node shutdown and reboot. In this paper, we present the architecture of the global scheduler and the process management mechanisms of Kerrighed, a single system image operating system designed for high performance computing on clusters. Kerrighed provides a development framework allowing to easily implement dynamic scheduling policies without kernel modification. In Kerrighed, the global scheduling policy can be dynamically changed while applications execute on the cluster. Kerrighed's process management mechanisms allow to easily deploy parallelapplications in the cluster and to efficiently migrate or checkpoint processes, including processes sharing memory. Kerrighed has been implemented as a set of modules extending Linux kernel. Preliminary performance results are presented
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