Leah Guzowski, Decision and Information Sciences Division, Argonne National Laboratory
March 20, 2014
University of Chicago, Searle 240A, 5735 S. Ellis Ave. This talk will be broadcast via Adobe Connect

Estimates of long-term operational energy and peak energy demand are essential for the sustainable development of new and existing urban areas. Improving energy efficiency and reducing demand in the built environment are also vital to urban development. Building the models required to simulate energy demand and consumption in existing facilities is time consuming and expensive. In addition, a great deal of uncertainty is inherent in these models because building energy use is primarily dictated by stochastic weather and building operations.

John Grime, CMTS & Katrin Heitmann, Argonne
March 19, 2014
Searle 240A, University of Chicago & Adobe Connect

John Grime, Postdoctoral Scholar, Center for Multiscale Theory and Simulation

Michela Taufer, University of Delaware
March 14, 2014
University of Chicago, Searle 240A
Today, petascale distributed memory systems perform large-scale simulations and generate massive amounts of data in a distributed fashion at unprecedented rates. This massive amount of data presents new challenges for the scientists analyzing the data scientific meaning. In case of clustering of this data, traditional analysis methods may require the comparison of single records with each other in an iterative process, and therefore involve moving data across nodes of the system.