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Ian Cosden, the director of Research Software Engineering for Computational & Data Science at Princeton University, speaks at the 2018 International RSE Leaders Meeting in London. Credit: Society of Research Software Engineering UK
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A 3D-reconstruction of mouse epithelial cells, assembled from the z-stack of a confocal microscopy image using a data-analysis tool developed by Princeton Research Software Engineer Abhishek Biswas for research carried out by doctoral candidate Lilia Leybova in the Devenport Lab.
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Staff from CSML, PICSciE and DataX help researchers launch new cancer analysis software that is capable of finding and analyzing genes that have been duplicated or deleted in multiple tumor samples from a single cancer patient. New improved version of software is more efficient and robust than previous version, and it can operate in the cloud.
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Henry Schreiner attends the IRIS-HEP Poster Session in February 2020. Schreiner is one of three IRIS-HEP team members working on developing histogramming technology for Python, a widely-used programming language. Credit: Jim Pivarski, Princeton University
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At left, Boriana Pratt, a statistical programmer at the Office of Population Research and the Data Manager for the New Jersey Families Study, works in her office using Citadel. Photo: Ma. Florevel Fusin-Wischusen/Princeton Institute for Computational Science & Engineering. At right, servers locked in a cage as part of the Secure Research Infrastructure at Princeton University. Photo: Matthew Petty, Office of Information Technology.
Enabling high-impact research by bringing education and advanced computing
to the Princeton community
Princeton Research Computing operates four large clusters and several smaller systems with more than 45,000 total cores and over 4 PFLOPS of processing power.
Supporting faculty, researchers and students with in-person and online help, software engineering, visualization and consulting on a wide range of research software tools.
An extensive educational, training, and outreach program in research computing, led by PICSciE, is available on campus and online.
Research computing at Princeton University engages academic departments and disciplines across the natural sciences, engineering, social sciences, and humanities.
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Facts and Figures
1000+
Accounts (faculty, staff, and students) from more than 50 academic departments, centers, programs, and institutional partners such as PPPL and GFDL currently use Princeton Research Computing's high-performance computing systems.
≈2,000
Students, postdocs, staff, and faculty members from over 45 departments and centers registered to attend computing and data science-centric workshops and mini-courses in the past year.
50+
Graduate students from over 20 academic departments are enrolled in PICSciE's Graduate Certificate in Computational Science and Engineering program.