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Polar Geospatial Center

Abstract: 

Polar Geospatial Center

The Polar Geospatial Center (PGC) provides geospatial support, mapping, and GIS/remote sensing solutions to researchers and logistics groups in the polar science community. The Center collaborates with scientists to complete their research goals in a safe, timely, and efficient manner by providing expertise and access to geospatial data and derived products. While scientists have developed elevation models over most of the earth from varied sources, the Polar Regions lack even coarse resolution digital elevation models (DEMs). This dearth of data severely limits the potential for topographic analysis in hydrology, ecology, geology, and geomorphology, and greatly reduces the accuracy of satellite imagery. Using two algorithms developed by NASA Ames and the Byrd Polar Research Center at the Ohio State University, PGC is leveraging the high volume of stereoscopic imagery being acquired in polar areas to create high resolution DEMs for distribution to the polar science community. Preliminary tests and data distribution suggest that the science community both needs and is ready to utilize such DEMs for synoptic mapping and change detection .

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Group name: 
morinp

Dell Town Hall Meeting, September 4

posted on September 3, 2013 As part of the ongoing selection process for the next HPC system at MSI, MSI has invited top high performance computing vendors to present their high performance computing portfolios and roadmaps to users in a open discussion setting. Dell Computing will be at MSI on...

Big Data, Model Combining, and Predictive Modeling of High Dimensional Data

Abstract: 

Big Data, Model Combining, and Predictive Modeling of High Dimensional Data

Big Data and the predictive modeling of high-dimensional datasets are of great interest to practitioners in many fields, such as finance, biology, and economics. These researchers are taking a methodology, model combination, that is widely and efficiently used for low-dimensional datasets and adapting it for high-dimensional situations. The project will develop a general risk bound for the group's methodology for high-dimensional predictive modeling, especially classification problems. Further, an efficient computing algorithm for the combination schemes will be developed and wrapped into a publicly available R package.

Many Big-Data sets (real data) will be analyzed by multiple high-dimensional classification methods using cross-validation. It will take about 10 million non-linear numerical optimizations for process. Besides working with real data, the researchers will perform various numerical experiments in order to have a better understanding of their methods. For different scenarios, they will compare their methods with between five and ten other popular methods and run large number of replicates to reduce the bias from the samplings. This will take about 10 million calculations.

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Group name: 
yangyh

Fast RF Calculations for High Field MRI

Abstract: 

Fast RF Calculations for High Field MRI

Radio-frequency electromagnetic analysis of high field MRI coils is an indispensable task for the development of new coil designs, for optimization of existing coils through tuning and matching when they are loaded with human models, and to ensure safety through specific absorption rate (SAR) and temperature calculations. Finite difference time domain (FDTD)-based solvers have been the method of choice so far since they can easily handle the inhomogeneities in the human model and the utilization of low-cost GPU accelerators helped in reducing the simulation times. Nonetheless, these solvers still suffer long simulation times due to the resonant nature of MRI coils. Initial experiments and a recent publication show that frequency-domain hybrid methods, such as method of moments (MOM)-finite element method (FEM), are better suited to MRI experiments in terms of solution time. In addition, because they use surface-conformal tetrahedral meshes instead of cubical voxels, they are free from staircasing errors hence yield superior accuracy compared to FDTD. The cost of the FEM-MOM approach is that it needs more memory and high-performance computing clusters to handle high-resolution human models with low simulation times. MSI resources are therefore necessary for this work.

Group name: 
vaughanj

UofM Receives Funding From NSF for Dedicated Campus Research Network

The University of Minnesota today announced the National Science Foundation (NSF) has awarded it $500,000 to build a dedicated research and computing network enabling researchers on its Twin Cities campus to more easily collaborate and innovate with research institutions around the world in their...

Visitor Numbers to LMVL at an All-Time High

The LMVL hit a milestone in October by logging its 1,000th visitor for the year 2011. Over 100 of these visitors were from businesses and government agencies that are interested in the research being performed at the University and at MSI. We have also been visited by government officials, notably...

Computing Workshops Offered

The SC09 Education Program and the National Computational Science Institute are offering a number of workshops over the summer and fall. Workshops are available in a number of fields related to high-performance computing, including parallel and cluster computing, biology, chemistry, physics,...

Analysis of Performance Determinants in NYC Taxicab Industry

Abstract: 

Analysis of Performance Determinants in NYC Taxicab Industry

The project explores NYC Taxi and Limousine Commission data on yellow cab trips in 2013. The principal question is to what extent the locus of rent creation resides with individual drivers and/or taxi fleets and leasing agents. The study employs various regression techniques with multidimensional categorical variables to separate the effects via variance and higher moments decomposition. MSI resources are required to estimate the regressions with tens of thousands of dummy variables on the set of 170 million observations.

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Group name: 
wangr

High-Throughput Data Transfer for Astrophysics Simulations

MSI, with the support of the University of Minnesota’s NTS (Network and Telecommunication Services), has recently deployed a system to take advantage of the ten-gigabit network known as the Northern Lights GigaPoP network . With this system in place, MSI was able to help Peter J. Mendygral, a post-...

Metal Cluster Structures and Reactivities: Computational Elucidation of Anion Photoelectron Spectra

Abstract: 

Metal Cluster Structures and Reactivities: Computational Elucidation of Anion Photoelectron Spectra

Research in this group focuses on the chemical bonding between transition metal atoms in ligand-free diatomics and clusters, and their reactivities with small gas phase molecules. Experiments in the laboratory employ anion photoelectron spectroscopy, flow tube ion-molecule chemistry, and mass spectrometry to study these anions and the corresponding neutral species. To help assign the photoelectron spectra, they compare the experimental results with those calculated using density functional methods, which are used to predict the equilibrium geometries, vibrational frequencies, electronic state energies, and spin multiplicities of the anionic and neutral systems. By simulating the Franck-Condon photodetachment spectra based upon the DFT results and comparing those predictions for possible electronic states and (for polyatomics) different isomers directly to the experimental spectra, the researchers are often able to deduce convincing assignments for the observed species, even if they have never been studied before either spectroscopically or computationally. The group's spectroscopic studies can also provide useful benchmarks to aid in the further development, by other researchers, of improved theoretical methods with which to treat these small but computationally challenging transition metal clusters and partially-ligated organometallics.

Current work includes studies of bare diatomics incorporating transition metals from Groups 5 and/or 6, which can exhibit very high-order multiple bonding. For example, the researchers are investigating the Group 6, third transition series homonuclear diatomic W2 (tungsten dimer), which has a formal bond order of 6, as well as the anions of bimetallic dimers incorporating metals from both Groups 5 and 6, such as NbCr-, NbMo- and NbW-, which can also exhibit sextuple bonds. They are also studying (or plan to study next year) organometallic complexes produced upon reaction of transition metal atoms with simple hydrocarbons (such as methane, ethylene or butadiene) or with CO2. These results can contribute to the understanding of the relationships between the chemical reactivities of various transition metals and the configurations and spin multiplicities of their ground and low-lying electronic states. In a broader context, these results can contribute to the development of an improved understanding of catalytic processes mediated by transition metal systems.

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Group name: 
leopoldd

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