632 research outputs found
A CyberGIS Integration and Computation Framework for High‐Resolution Continental‐Scale Flood Inundation Mapping
We present a Digital Elevation Model (DEM)-based hydrologic analysis methodology for continental flood inundation mapping (CFIM), implemented as a cyberGIS scientific workflow in which a 1/3rd arc-second (10m) Height Above Nearest Drainage (HAND) raster data for the conterminous U.S. (CONUS) was computed and employed for subsequent inundation mapping. A cyberGIS framework was developed to enable spatiotemporal integration and scalable computing of the entire inundation mapping process on a hybrid supercomputing architecture. The first 1/3rd arc-second CONUS HAND raster dataset was computed in 1.5 days on the CyberGIS ROGER supercomputer. The inundation mapping process developed in our exploratory study couples HAND with National Water Model (NWM) forecast data to enable near real-time inundation forecasts for CONUS. The computational performance of HAND and the inundation mapping process was profiled to gain insights into the computational characteristics in high-performance parallel computing scenarios. The establishment of the CFIM computational framework has broad and significant research implications that may lead to further development and improvement of flood inundation mapping methodologies
CC*IIE Networking Infrastructure - NSF Award #1440646 Project Description
CC*IIE Networking Infrastructure: Accelerating science, translational research, and collaboration at the University of Pittsburgh through the implementation of network upgrades
A survey of computational steering environments
Computational steering is a powerful concept that allows scientists to interactively control a computational process during its execution. In this paper, a survey of computational steering environments for the on-line steering of ongoing scientific and engineering simulations is presented. These environments can be used to create steerable applications for model exploration, algorithm experimentation, or performance optimization. For each environment the scope is identified, the architecture is summarized, and the concepts of the user interface is described. The environments are compared and conclusions and future research issues are given
Precision-Aware application execution for Energy-optimization in HPC node system
Power consumption is a critical consideration in high performance computing
systems and it is becoming the limiting factor to build and operate Petascale
and Exascale systems. When studying the power consumption of existing systems
running HPC workloads, we find that power, energy and performance are closely
related which leads to the possibility to optimize energy consumption without
sacrificing (much or at all) the performance. In this paper, we propose a HPC
system running with a GNU/Linux OS and a Real Time Resource Manager (RTRM) that
is aware and monitors the healthy of the platform. On the system, an
application for disaster management runs. The application can run with
different QoS depending on the situation. We defined two main situations.
Normal execution, when there is no risk of a disaster, even though we still
have to run the system to look ahead in the near future if the situation
changes suddenly. In the second scenario, the possibilities for a disaster are
very high. Then the allocation of more resources for improving the precision
and the human decision has to be taken into account. The paper shows that at
design time, it is possible to describe different optimal points that are going
to be used at runtime by the RTOS with the application. This environment helps
to the system that must run 24/7 in saving energy with the trade-off of losing
precision. The paper shows a model execution which can improve the precision of
results by 65% in average by increasing the number of iterations from 1e3 to
1e4. This also produces one order of magnitude longer execution time which
leads to the need to use a multi-node solution. The optimal trade-off between
precision vs. execution time is computed by the RTOS with the time overhead
less than 10% against a native execution
Airborne dust: from R and D to operational forecast. 2013-2015 Activity Report of the SDS-WAS Regional Center for Northern Africa, Middle East and Europe
The 17th World Meteorological Congress designated the consortium of AEMET and Barcelona Supercomputing Center (BSC) to host the first WMO Regional Meteorological Center specialized on Atmospheric Sand and Dust Forecast. The new center operationally generates and distributes dust forecasts under the name of Barcelona Dust Forecast Center. This decision recognizes the research activities and the products implemented by AEMET and BSC as a valuable contribution to the WMO Sand and Dust Storm – Warning Advisory and Assessment System (SDS-WAS). The services provided by the Barcelona Dust Forecast Center allow for the development of strategies to minimize the severe impacts caused by atmospheric dust on lives and property in Northern Africa, Middle East and Europe. This report summarizes the activities of the SDS-WAS Regional Center for Northern Africa, Middle East and Europe for 2013-2015 and shows the great success of the SDS-WAS project
access: v.10, no.02, Summer 1996
published or submitted for publicatio
ASTRAL PROJECTION: THEORIES OF METAPHOR, PHILOSOPHIES OF SCIENCE, AND THE ART O F SCIENTIFIC VISUALIZATION
This thesis provides an intellectual context for my work in computational
scientific visualization for large-scale public outreach in venues such as digitaldome
planetarium shows and high-definition public television documentaries. In
my associated practicum, a DVD that provides video excerpts, 1 focus especially on
work I have created with my Advanced Visualization Laboratory team at the
National Center for Supercomputing Applications (Champaign, Illinois) from
2002-2007.
1 make three main contributions to knowledge within the field of computational
scientific visualization. Firstly, I share the unique process 1 have pioneered for
collaboratively producing and exhibiting this data-driven art when aimed at popular
science education. The message of the art complements its means of production:
Renaissance Team collaborations enact a cooperative paradigm of evolutionary
sympathetic adaptation and co-creation.
Secondly, 1 open up a positive, new space within computational scientific
visualization's practice for artistic expression—especially in providing a theory of
digi-epistemology that accounts for how this is possible given the limitations
imposed by the demands of mapping numerical data and the computational models
derived from them onto visual forms. I am concerned not only with liberating
artists to enrich audience's aesthetic experiences of scientific visualization, to
contribute their own vision, but also with conceiving of audiences as co-creators of
the aesthetic significance of the work, to re-envision and re-circulate what they
encounter there. Even more commonly than in the age of traditional media, on-line
social computing and digital tools have empowered the public to capture and
repurpose visual metaphors, circulating them within new contexts and telling new
stories with them.
Thirdly, I demonstrate the creative power of visaphors (see footnote, p. 1) to
provide novel embodied experiences through my practicum as well as my thesis
discussion. Specifically, I describe how the visaphors my Renaissance Teams and I
create enrich the Environmentalist Story of Science, essentially promoting a
counter-narrative to the Enlightenment Story of Science through articulating how
humanity participates in an evolving universal consciousness through our embodied
interaction and cooperative interdependence within nested, self-producing
(autopoetic) systems, from the micro- to the macroscopic. This contemporary
account of the natural world, its inter-related systems, and their dynamics may be
understood as expressing a creative and generative energy—a kind of
consciousness-that transcends the human yet also encompasses it
Semantic Services Grid in Flood-forecasting Simulations
Flooding in the major river basins of Central Europe is a recurrent event affecting many countries. Almost every year, it takes away lives and causes damage to infrastructure, agricultural and industrial production, and severely affects socio-economic development. Recurring floods of the magnitude and frequency observed in this region is a significant impediment, which requires rapid development of more flexible and effective flood-forecasting systems. In this paper we present design and development of the flood-forecasting system based on the Semantic Grid services. We will highlight the corresponding architecture, discovery and composition of services into workflows and semantic tools supporting the users in evaluating the results of the flood simulations. We will describe in detail the challenges of the flood-forecasting application and corresponding design and development of the service-oriented model, which is based on the well known Web Service Resource Framework (WSRF). Semantic descriptions of the WSRF services will be presented as well as the architecture, which exploits semantics in the discovery and composition of services. Further, we will demonstrate how experience management solutions can help in the process of service discovery and user support. The system provides a unique bottom-up approach in the Semantic Grids by combining the advances of semantic web services and grid architectures
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