Justin Wozniak, Mathematics and Computer Science Division, Argonne National Laboratory
July 31, 2014
Argonne National Lab, TCS Building 240, Room 5172, broadcast via Adobe Connect

A large-scale, collaborative computational experiment involves more than the tuning of individual code fragments- typically, codes must be assembled, integrated in one or more programming models and languages, experimental runs must be managed and data collected.  In this talk, I will present my work using the Swift programming language to assemble and run many different scientific applications on wide range of computer systems.  In high-performance computing, I will present the Swift/T system for high performance dataflow applications that run on extremely large systems such as

Tanu Malik, Research Scientist, Computation Institute
July 24, 2014
University of Chicago, Searle 240A, 5735 S. Ellis Ave. This talk will be broadcast via Adobe Connect

Data and its management are central to modern scientific enterprise. Typically, a scientist uses data from several disparate sources (file systems, RDBMS, Excel sheets, remote data sources) in the same project. Integrated data management solutions that provide uniform interfaces irrespective of the kind of data source are, however, lacking. Therefore scientists are burdened with performing several time-consuming, low-level data management tasks individually and repeatedly for each data source.