82,122 research outputs found
A Pattern Language for High-Performance Computing Resilience
High-performance computing systems (HPC) provide powerful capabilities for
modeling, simulation, and data analytics for a broad class of computational
problems. They enable extreme performance of the order of quadrillion
floating-point arithmetic calculations per second by aggregating the power of
millions of compute, memory, networking and storage components. With the
rapidly growing scale and complexity of HPC systems for achieving even greater
performance, ensuring their reliable operation in the face of system
degradations and failures is a critical challenge. System fault events often
lead the scientific applications to produce incorrect results, or may even
cause their untimely termination. The sheer number of components in modern
extreme-scale HPC systems and the complex interactions and dependencies among
the hardware and software components, the applications, and the physical
environment makes the design of practical solutions that support fault
resilience a complex undertaking. To manage this complexity, we developed a
methodology for designing HPC resilience solutions using design patterns. We
codified the well-known techniques for handling faults, errors and failures
that have been devised, applied and improved upon over the past three decades
in the form of design patterns. In this paper, we present a pattern language to
enable a structured approach to the development of HPC resilience solutions.
The pattern language reveals the relations among the resilience patterns and
provides the means to explore alternative techniques for handling a specific
fault model that may have different efficiency and complexity characteristics.
Using the pattern language enables the design and implementation of
comprehensive resilience solutions as a set of interconnected resilience
patterns that can be instantiated across layers of the system stack.Comment: Proceedings of the 22nd European Conference on Pattern Languages of
Program
Automated Stellar Spectral Classification and Parameterization for the Masses
Stellar spectroscopic classification has been successfully automated by a
number of groups. Automated classification and parameterization work best when
applied to a homogeneous data set, and thus these techniques primarily have
been developed for and applied to large surveys. While most ongoing large
spectroscopic surveys target extragalactic objects, many stellar spectra have
been and will be obtained. We briefly summarize past work on automated
classification and parameterization, with emphasis on the work done in our
group. Accurate automated classification in the spectral type domain and
parameterization in the temperature domain have been relatively easy. Automated
parameterization in the metallicity domain, formally outside the MK system, has
also been effective. Due to the subtle effects on the spectrum, automated
classification in the luminosity domain has been somewhat more difficult, but
still successful. In order to extend the use of automated techniques beyond a
few surveys, we present our current efforts at building a web-based automated
stellar spectroscopic classification and parameterization machine. Our proposed
machinery would provide users with MK classifications as well as the
astrophysical parameters of effective temperature, surface gravity, mean
abundance, abundance anomalies, and microturbulence.Comment: 5 pages; to appear in The Garrison Festschrift conference proceeding
Reverse Detection of Short-Term Earthquake Precursors
We introduce a new approach to short-term earthquake prediction based on the
concept of selforganization of seismically active fault networks. That approach
is named "Reverse Detection of Precursors" (RDP), since it considers precursors
in reverse order of their appearance. This makes it possible to detect
precursors undetectable by direct analysis. Possible mechanisms underlying RDP
are outlined. RDP is described with a concrete example: we consider as
short-term precursors the newly introduced chains of earthquakes reflecting the
rise of an earthquake correlation range; and detect (retrospectively) such
chains a few months before two prominent Californian earthquakes - Landers,
1992, M = 7.6, and Hector Mine, 1999, M = 7.3, with one false alarm. Similar
results (described elsewhere) are obtained by RDP for 21 more strong
earthquakes in California (M >= 6.4), Japan (M >= 7.0) and the Eastern
Mediterranean (M >= 6.5). Validation of the RDP approach requires, as always,
prediction in advance for which this study sets up a base. We have the first
case of advance prediction; it was reported before Tokachi-oki earthquake (near
Hokkaido island, Japan), Sept. 25, 2003, M = 8.1. RDP has potentially important
applications to other precursors and to prediction of other critical phenomena
besides earthquakes. In particular, it might vindicate some short-term
precursors, previously rejected as giving too many false alarms.Comment: 17 pages, 5 figure
Toward Self-Organising Service Communities
This paper discusses a framework in which catalog service communities are built, linked for interaction, and constantly monitored and adapted over time. A catalog service community (represented as a peer node in a peer-to-peer network) in our system can be viewed as domain specific data integration mediators representing the domain knowledge and the registry information. The query routing among communities is performed to identify a set of data sources that are relevant to answering a given query. The system monitors the interactions between the communities to discover patterns that may lead to restructuring of the network (e.g., irrelevant peers removed, new relationships created, etc.)
Faint dwarf galaxies in the Next Generation Virgo cluster Survey
The Next Generation Virgo Cluster Survey (NGVS) is a CFHT Large Program that
is using the wide field of view capabilities of the MegaCam camera to map the
entire Virgo Cluster from its core to virial radius. The observing strategy has
been optimized to detect very low surface brightness structures in the cluster,
including intracluster stellar streams and faint dwarf spheroidal galaxies. We
present here the current status of this ongoing survey, with an emphasis on the
detection and analysis of the very low-mass galaxies in the cluster that have
been revealed by the NGVS.Comment: 6 pages, 2 figures, Conference Proceedings: "A Universe of Dwarf
Galaxies", 14-18 June 2010, Lyon, Franc
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