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Princeton University held its first computing bootcamp for graduate students and postdocs on Oct. 29 to Nov. 1, four days of short introductory-level lectures and hands-on exercises on a variety of topics, tools and techniques necessary for modern computational research careers.
On Oct. 16-17, some 60 Princeton graduate students and postdocs — along with a handful of undergraduates — explored the most widely used deep learning techniques for computer vision tasks and delved into using new parallel computing programs to dramatically speed up applications.
In the 19th century, printing technology changed the way readers experienced texts. Today, students and researchers are using digital technology to access historical literary texts in new ways and finding surprising echoes of the past in their own lives.
During a downtime period in which the Large Hadron Collider is not producing data, Princeton and CERN physicists work on the installation of the pixel luminosity telescope of the CMS experiment. Shown from left: David Stickland, Princeton; and Rob Loos and Anne Dabrowski, CERN.
© 2015-2018 CERN
With the goal of creating next-generation computing power to support high-energy physics research, the National Science Foundation (NSF) announced today that Princeton University will lead a new NSF-funded coalition of 17 research universities to be called the Institute for Research and Innovation in Software for High Energy Physics (IRIS-HEP).
Deep Learning Leader William Tang
(Photo by Elle Starkman/Office of Communications)
To capture and control the process of fusion that powers the sun and stars in facilities on Earth called tokamaks, scientists must confront disruptions that can halt the reactions and damage the doughnut-shaped devices. Now an artificial intelligence system under development at the U.S.
At podium, Alfredo Canziani, post-doc at NYU’s Center for Data Science, speaks to CoDaS-HEP attendees about machine learning. Photo by Florevel Fusin-Wischusen, Princeton Institute for Computational Science and Engineering
As thunderstorms rumbled across the region, fifty-six high energy physics graduate students and twelve presenters from across the United States, as well as from India, Pakistan, France, and Norway, gathered at the Princeton Center for Theoretical Science (PCTS) to attend the Computational and Data S
The TIGER HPC computing cluster in the High Performance Computing Research Center, Princeton’s 47,000-square-foot data center.
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Education and Training
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Enabling Princeton's Research Community
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Systems and Services
Training
Python/Numpy for High-Performance Numerical Processing
Thu, Nov 15, 2018, 10:00 am to 4:00 pm
Location:
347 Lewis Library, Vis Lab
Python Programming Techniques
Fri, Nov 16, 2018, 2:00 pm to 3:30 pm
Location:
Digital Learning Lab, 130 Lewis Library
Help Sessions
Weekly Help Sessions in Visualization & Programming
Thu, Nov 15, 2018, 2:00 pm to 3:00 pm
Location:
347 Lewis Science Library
Weekly Help Sessions
Other Events
Image Analysis using Python
Tue, Dec 4, 2018, 4:00 pm to 5:00 pm
Location:
347 Lewis Library, Vis Lab
Cluster Scheduling and Management
Tue, Jan 22, 2019, 4:00 pm to 5:00 pm
Location:
347 Lewis Library, Vis Lab
Research News
Wednesday, Aug 17, 2016
The amount of data encompassed by the global climate in its entirety, from its winds and temperature conditions to shifting formations of cloud,...
Wednesday, Aug 17, 2016
Turbulent combustion is just that. Jet engines and high-power furnaces produce a great amount of energy, along with its byproduct: emissions in...
Wednesday, Aug 17, 2016
Energy is central to civilization as we know it. It’s also environmentally untenable in its current state. This is an issue Professor Emily Carter...
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