Research highlights: U-M group awarded Midwest Big Data Spoke award from NSF for Advanced Computational Neuroscience Network (ACNN)

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A group of three University of Michigan faculty members will lead the Advanced Computational Neuroscience Network project as a “spoke” in the Midwest Big Data Hub program funded by the…

Info Session: Data Science Services at U-M — Nov. 1

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Representatives of Consulting for Statistics, Computing and Analytics Research (CSCAR) and the U-M Library (UML) will give an overview of services that are now available to support data-intensive research on…

Research highlights: A new era in disaster research

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By Bob Brustman, U-M Civil and Environmental Engineering Department University of Michigan researchers have received a $2.5 million NSF grant to develop a computational model that is hoped to significantly…

Research highlights: Running climate models in the cloud

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Can cloud computing systems help make climate models easier to run? Assistant research scientist Xiuhong Chen and MICDE affiliated faculty Xianglei Huang, from Climate and Space Sciences and Engineering (CLASP),…

Latest Twetter Feeds

Robert Groves, G'town & Sudip Bhattacharjee, Census Bureau's Center for Big Data, to speak at 2016 MIDAS symposium. https://t.co/2HUOlyySi5 
MICDE Seminar: Andrea Lodi, Ecole Politechnique, Montreal — Wednesday, Oct. 24 -- https://t.co/NtUVTmYXfX 
Learn MatLab at CSCAR, starting Nov. 3: https://t.co/FrzwyQEp5w 

October 26 @ 4:10 pm - 5:00 pm

MICDE Seminar: Andrea Lodi, Ecole Polytechnique, Montreal

Bio: Dr. Andrea Lodi is a professor in the department of Mathematical and Industrial Engineering at the Polytechnique Montreal. He is the Canada Excellence Research Chair in Data Science for Real-Time Decision-Making…

October 27 @ 8:00 am - October 28 @ 5:00 pm

Big Data: Improving the Scope, Quality and Accessibility of Financial Data

The Office of Financial Research and the University of Michigan will host a joint conference, “Big Data: Improving the Scope, Quality, and Accessibility of Financial Data” in Ann Arbor, Michigan. …

November 7 @ 1:00 pm - 5:00 pm

Fitting General Linear and Mixed-Effects (Multilevel) Models in SPSS®

This three-half-days workshop is designed to provide experienced SPSS users (please read prerequisites below carefully) with hands-on exposure to more advanced modeling techniques in SPSS, using IBM SPSS for Windows….

November 8 @ 1:00 pm - 5:00 pm

Fitting General Linear and Mixed-Effects (Multilevel) Models in SPSS®

This three-half-days workshop is designed to provide experienced SPSS users (please read prerequisites below carefully) with hands-on exposure to more advanced modeling techniques in SPSS, using IBM SPSS for Windows….

ARC Highlights

Lights of India visualization

Electricity in India

Many still live in darkness

U-M Assistant Professor of Political Science Brian Min is using the Flux high performance computing cluster to analyze thousands of satellite images showing the output of electric lights in India.

His Nightlights website shows satellite images collected over 20 years from more than 600,000 villages. Min’s research reveals that some local units of government have overstated their progress in electrification, and that political considerations play into which regions get electricity, among other things.

Read the U-M press release for more details.

Conflux visualization


Combining Big Data and HPC

A new way of computing could lead to immediate advances in aerodynamics, climate science, cosmology, materials science and cardiovascular research.

The National Science Foundation will provide $2.42 million to develop a unique facility for refining complex, physics-based computer models with big data techniques at the University of Michigan. The university will provide an additional $1.04 million.

See the grant description and press release for more information.

U-M featured on CASC brochure


An image from the lab of Prof. Joaquim Martins, Aerospace Engineering, is featured on the cover of the 2016 brochure of the Coalition for Academic Scientific Computation (CASC). U-M researchers Alberto Figueroa (Surgery and Biomedical Engineering) and Venkat Raman (Aerospace Engineering) are also included in the report, which highlights notable computational research from the past year.

CASC is an 85-member non-profit group advocating for the use of the most advanced computing technology to accelerate scientific discovery for national competitiveness, global security, and economic success, as well as development of a diverse and well-prepared 21st century workforce

Animation of reducing the bottleneck effect

$5 million to widen ‘bottleneck to discovery’

An NSF grant will create a software-defined network between three Michigan universities

Buried in troves of data that scientists have gathered, but not yet analyzed, could be key insights to improving cancer treatment, understanding Alzheimer’s, predicting climate change effects and developing cheaper, clean energy technologies.

Those are just a few of the countless examples of fields where our capacity to gather scientific data now far exceeds our capacity to crunch it—especially when collaborations span the globe. Some research projects are producing the equivalent of 1,000 consumer hard drives a month, for example. Read more.

RCS Fall of 2014 event

Cyberinfrastructure (CI) Days

ARC and its predecessor ORCI held annual Cyberinfrastructure (CI) Days events to bring the computational research community together, including prominent speakers and poster competitions. For information, or to view videos and posters, see below:

CI Days evolved into the annual symposium put on by the Michigan Institute for Data Science (MIDAS) and the Michigan Institute for Computational Discovery and Engineering (MICDE).


High performance computer cluster at the University of Michigan

Current Status


  • Armis
    HIPAA-aligned HPC cluster
    ARC-TS established a HIPAA-aligned cluster in early 2016
  • 2,852
    Current ARC-TS HPC users
  • 22,818
    Number of HPC processors in ARC-TS computing resources
  • 1,087,012
    HPC jobs completed, 1Q 2016
  • 112 TB
    Amount of HPC memory