2,566 research outputs found
IMP Science Gateway: from the Portal to the Hub of Virtual Experimental Labs in Materials Science
"Science gateway" (SG) ideology means a user-friendly intuitive interface
between scientists (or scientific communities) and different software
components + various distributed computing infrastructures (DCIs) (like grids,
clouds, clusters), where researchers can focus on their scientific goals and
less on peculiarities of software/DCI. "IMP Science Gateway Portal"
(http://scigate.imp.kiev.ua) for complex workflow management and integration of
distributed computing resources (like clusters, service grids, desktop grids,
clouds) is presented. It is created on the basis of WS-PGRADE and gUSE
technologies, where WS-PGRADE is designed for science workflow operation and
gUSE - for smooth integration of available resources for parallel and
distributed computing in various heterogeneous distributed computing
infrastructures (DCI). The typical scientific workflows with possible scenarios
of its preparation and usage are presented. Several typical use cases for these
science applications (scientific workflows) are considered for molecular
dynamics (MD) simulations of complex behavior of various nanostructures
(nanoindentation of graphene layers, defect system relaxation in metal
nanocrystals, thermal stability of boron nitride nanotubes, etc.). The user
experience is analyzed in the context of its practical applications for MD
simulations in materials science, physics and nanotechnologies with available
heterogeneous DCIs. In conclusion, the "science gateway" approach - workflow
manager (like WS-PGRADE) + DCI resources manager (like gUSE)- gives opportunity
to use the SG portal (like "IMP Science Gateway Portal") in a very promising
way, namely, as a hub of various virtual experimental labs (different software
components + various requirements to resources) in the context of its practical
MD applications in materials science, physics, chemistry, biology, and
nanotechnologies.Comment: 6 pages, 5 figures, 3 tables; 6th International Workshop on Science
Gateways, IWSG-2014 (Dublin, Ireland, 3-5 June, 2014). arXiv admin note:
substantial text overlap with arXiv:1404.545
BOSS-LDG: A Novel Computational Framework that Brings Together Blue Waters, Open Science Grid, Shifter and the LIGO Data Grid to Accelerate Gravitational Wave Discovery
We present a novel computational framework that connects Blue Waters, the
NSF-supported, leadership-class supercomputer operated by NCSA, to the Laser
Interferometer Gravitational-Wave Observatory (LIGO) Data Grid via Open Science
Grid technology. To enable this computational infrastructure, we configured,
for the first time, a LIGO Data Grid Tier-1 Center that can submit
heterogeneous LIGO workflows using Open Science Grid facilities. In order to
enable a seamless connection between the LIGO Data Grid and Blue Waters via
Open Science Grid, we utilize Shifter to containerize LIGO's workflow software.
This work represents the first time Open Science Grid, Shifter, and Blue Waters
are unified to tackle a scientific problem and, in particular, it is the first
time a framework of this nature is used in the context of large scale
gravitational wave data analysis. This new framework has been used in the last
several weeks of LIGO's second discovery campaign to run the most
computationally demanding gravitational wave search workflows on Blue Waters,
and accelerate discovery in the emergent field of gravitational wave
astrophysics. We discuss the implications of this novel framework for a wider
ecosystem of Higher Performance Computing users.Comment: 10 pages, 10 figures. Accepted as a Full Research Paper to the 13th
IEEE International Conference on eScienc
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ToScA North America (6 – 8 June 2017, The University of Texas, Austin, TX) Program
ToScA North America will address key areas of science,
including Multi-modal Imaging, Geosciences, Forensics, Increasing Contrast,
Educational Outreach, Data, Materials Science and Medical and Biological
Science.University of Texas High-Resolution X-ray CT Facility (UTCT);
Jackson School of Geosciences, The University of Texas at Austin;
Natural History Museum (London);
Royal Microscopical Society (Oxford, UK)Geological Science
The INCF Digital Atlasing Program: Report on Digital Atlasing Standards in the Rodent Brain
The goal of the INCF Digital Atlasing Program is to provide the vision and direction necessary to make the rapidly growing collection of multidimensional data of the rodent brain (images, gene expression, etc.) widely accessible and usable to the international research community. This Digital Brain Atlasing Standards Task Force was formed in May 2008 to investigate the state of rodent brain digital atlasing, and formulate standards, guidelines, and policy recommendations.

Our first objective has been the preparation of a detailed document that includes the vision and specific description of an infrastructure, systems and methods capable of serving the scientific goals of the community, as well as practical issues for achieving
the goals. This report builds on the 1st INCF Workshop on Mouse and Rat Brain Digital Atlasing Systems (Boline et al., 2007, _Nature Preceedings_, doi:10.1038/npre.2007.1046.1) and includes a more detailed analysis of both the current state and desired state of digital atlasing along with specific recommendations for achieving these goals
py4DSTEM: a software package for multimodal analysis of four-dimensional scanning transmission electron microscopy datasets
Scanning transmission electron microscopy (STEM) allows for imaging,
diffraction, and spectroscopy of materials on length scales ranging from
microns to atoms. By using a high-speed, direct electron detector, it is now
possible to record a full 2D image of the diffracted electron beam at each
probe position, typically a 2D grid of probe positions. These 4D-STEM datasets
are rich in information, including signatures of the local structure,
orientation, deformation, electromagnetic fields and other sample-dependent
properties. However, extracting this information requires complex analysis
pipelines, from data wrangling to calibration to analysis to visualization, all
while maintaining robustness against imaging distortions and artifacts. In this
paper, we present py4DSTEM, an analysis toolkit for measuring material
properties from 4D-STEM datasets, written in the Python language and released
with an open source license. We describe the algorithmic steps for dataset
calibration and various 4D-STEM property measurements in detail, and present
results from several experimental datasets. We have also implemented a simple
and universal file format appropriate for electron microscopy data in py4DSTEM,
which uses the open source HDF5 standard. We hope this tool will benefit the
research community, helps to move the developing standards for data and
computational methods in electron microscopy, and invite the community to
contribute to this ongoing, fully open-source project
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