|Jun 12, 2013-Jun 12, 2013||SDSC Hosts First Annual Industry Partners Research Review|
SDSC hosts its first annual research review for current and prospective industrial partners and affiliates. Participants will learn about SDSC’s diverse research activities; including its wide expertise in advanced computing and storage, managing the deluge of ‘Big Data’ now being generated by commercial laboratories, academia, and government institutions; and how the Center is leading the way in emerging areas such as data mining and predictive analytics.
|Jun 23, 2013-Jun 28, 2013||2013 International Summer School on HPC Challenges in Computational Sciences|
New York University
Graduate students and postdoctoral scholars in the United States, Europe, and Japan are invited to apply for the fourth International Summer School on HPC Challenges in Computational Sciences, to be held June 23-28, 2013, at New York University in New York City. The summer school is sponsored by the U.S. National Science Foundation's Extreme Science and Engineering Discovery Environment (XSEDE) project, the European Union Seventh Framework Program's Partnership for Advanced Computing in Europe (PRACE), and RIKEN Advanced Institute for Computational Science (RIKEN AICS).
|Jul 8, 2013-Jul 10, 2013||VSCSE Data Intensive Summer School|
SDSC Synthesis Center
The Data Intensive Summer School focuses on the skills needed to manage, process and gain insight from large amounts of data. It is targeted at researchers from the physical, biological, economic and social sciences that are beginning to drown in data. We will cover the nuts and bolts of data intensive computing, common tools and software, predictive analytics algorithms, data management and non-relational database models.
|Jul 22, 2013-Jul 25, 2013||XSEDE13 Conference|
The XSEDE13 conference will place a spotlight on the broad impact of Science Gateways to facilitate discoveries across a broad range of disciplines. Our technical, science and TEOS tracks will provide a broad range of studies and advances for our community, but this year we'll also offer a round of "lightning talks" to engage attendees in the discussion. The conference will devote a half day to the biosciences, with invited speakers, panelists, and paper presentations offering the latest discoveries in this high-profile arena. And a job fair will allow attendees -- especially students -- to discover new careers.
|Aug 5, 2013-Aug 9, 2013||SDSC 2013 Summer Institute: Discover Big Data|
Discover Big Data is the theme of SDSC’s Summer Institute in 2013, reflecting the pressing need for high performance solutions for exploring and analyzing the large volumes of data that science and business applications are now able to generate with ease. The 5-day summer institute will cover topics in HPC and big data including, data management, data analytics and visualization, and parallel programming models, via discussion of specific use cases and hands-on exercises.
|Aug 12, 2013-Aug 16, 2013||ECSITE'13: EarthCube Summer Institute 2013|
ECSITE’13 will provide an introduction to data science concepts and topics, while also covering topics in computational science. The Institute is particularly encourages applications from early career faculty and researchers, specially those interested in carrying forward the concepts learned at ECSITE into their own research activities and to their classroom teaching, as well as graduate students and postdocs.
|Sep 12, 2013-Sep 13, 2013||PACE Data Mining Bootcamp 1|
SDSC Synthesis Center
The PACE Boot Camp 1 is designed to provide individuals in business enterprises and scientific communities with improved tactics critical to design, build, verify, and test predictive data models. Data mining, the art and science of learning from data, covers a number of different procedures.
|Feb 5, 2012-Feb 8, 2012||PACE Data Mining Bootcamp 2|
SDSC Syntesis Center
This hands-on course emphasizes advanced learning techniques including Artificial Neural Networks (ANNs), Support Vector Machines (SVM), Text Mining, Collaborative Filtering, Bayesian Networks and Temporal Data Mining.