In the fall of 2014, MSI added a Ceph object storage system as an option for second-tier storage for MSI users. Many MSI researchers are in disciplines that use huge amounts of data, such as informatics, genomics, and astrophysics. Often, much of this data does not need to be stored on a machine...
On Wednesday, February 7, 2018, MSI staff will perform scheduled maintenance and upgrades to various MSI systems. Primary Storage, Mesabi, and Itasca will be unavailable throughout much of the day. In preparation for February's Maintenance Day, a system reservation will be placed on all nodes...
On Wednesday, May 2, 2018, MSI staff will perform scheduled maintenance and upgrades to various MSI systems. Primary Storage, Mesabi, and Itasca will be unavailable throughout much of the day. A global system reservation will start at 6am on May 2. Jobs that cannot be completed before 6am on May 2...
<h3 class="red">Reduced-Complexity Air Quality Model Development and Application</h3><p>Outdoor air pollution kills approximately three million people per year. Air quality models are commonly used to understand and manage air quality. Chemical transport models (CTMs) are the most accurate of these models but are too computationally intensive for many applications. Reduced complexity models can be used to augment CTM simulations. These researchers have developed a reduced complexity air pollution modeling framework (InMAP, the Intervention Model for Air Pollution) and have created implementations of the model for the continental US for the years 2005 and 2030. They are using MSI resources to create additional implementations of the model: one that is specific to China, one that is specific to India, and a worldwide version.</p><p>Research Spotlights about this work appeared on the MSI website in <a href="https://www.msi.umn.edu/content/air-pollution-and-socioeconomic-status">September 2014</a> and <a href="https://www.msi.umn.edu/content/effects-alternative-fuels-air-quality">February 2015</a>.</p><p>Return to this PI’s <a href="https://www.msi.umn.edu/pi/f6c8babcd096c43fea5d360e3fb29676/14397">main page</a>.</p>
MSI PIs George Weiblen and M. David Marks , both professors in the Department of Plant Biology , have published research that identifies a gene that distinguishes hemp from marijuana. This research could have implications for future industrial uses of hemp. Currently, legal restrictions affect both...
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<h4>Resource Allocation in Humanitarian Operations</h4><p><span style="color: rgb(51, 51, 51); font-size: 14px; background-color: rgb(255, 255, 255); line-height: 1.5;">This project studies inventory management in the context of supplementary food and disease progression in a finite time horizon. In addition to presenting structural properties, the researcher explores the efficacy of pragmatic heuristics in this context. MSI resources are used to computationally evaluate the performance of different heuristics.</span></p><p><span style="color: rgb(51, 51, 51); font-size: 14px; background-color: rgb(255, 255, 255); line-height: 1.5;">Return to this PI's <a href="https://www.msi.umn.edu/pi/95904a877516d6d6c418ec4bcf91dd13/10792">main page</a>.</span></p><p> </p>
posted on December 4, 2014 Two opportunities in high-performance computing research are now accepting applications for their programs in 2015. The Computational Physics Student Summer Workshop will be hosted by Los Alamos National Laboratory’s Computational Physics Division, June 8 - August 14,...
<p><strong>Data Mining for Healthcare Applications</strong></p> <p>This research group uses MSI resources for several ongoing projects related to healthcare. In the first project, they use match run data to develop a predictive model for determining accept/decline decisions by candidates on organ transplant wait list. These models are used to estimate the impact of allocation policy changes on the effectiveness of transplant programs. The second project uses time stamp and health records data to develop a predictive model for hospital stays. This model will be used to develop a capacity management methodology for hospitals. The third project uses longitudinal data from integrated health systems to study impact of different service delivery paradigms on cost and quality of care.</p> <p> </p>
<h3 class="red">Calibration of Simulation Models for Colorectal Cancer Screening</h3><p>The goal of this project is to develop a Markov model to simulate natural history of colorectal cancer in the US population over time based on different population demographics, screening and treatment dissemination, post-colorectal cancer diagnosis, and other improvements in cancer-specific survival. In order to do this, the model parameters must be calibrated to fit the observed survival. Calibration procedures are performed with either search algorithms or optimization procedures, which typically require intense computing processes and a large temporary memory allocation. MSI resources significantly improve productivity and allow reduced computing time.</p><p>Return to this PI's <a href="https://www.msi.umn.edu/pi/0735ff4192f733f9b4852727fe994ea0/10660">main page</a>.</p>