ARC begins pilot consulting service for scientific code optimization

By | General Interest, News

ARC is starting a pilot consulting service aimed at scientific code optimization.

Through this service, you can receive assistance with locating performance bottlenecks, identifying hot spots, and parallelizing performance-critical parts of your HPC codes. Projects will be handled on a first-come, first-served basis, and assistance is limited to approximately 6 hours per project.

Please contact Alexander Gaenko <> to set up a consultation appointment.

REMINDER: MICDE Seminar: David Randall, Colorado State University, on “Climate Modeling: What To Do While We Wait for Exascale” — Feb. 5

By | Educational, Events

David Randall is a University Distinguished Professor of Atmospheric Science at Colorado State University, and director of the Center for Multiscale Modeling of Atmospheric Processes, an NSF Science and Technology Center. His research interests are in general circulation modeling, cloud-climate studies, and cloud parameterization. He previously served as Assistant Professor, Department of Meteorology, Massachusetts Institute of Technology, and Meteorologist in the Global Modeling and Simulation Branch, NASA/Goddard Space Flight Center. He is a fellow of the American Meteorological Society, the American Geophysical Union, and the American Association for the Advancement of Science. Randall holds B.S. and M.S. degrees in Aeronautical and Astronautical Engineering from Ohio State, and a Ph.D. in Atmospheric Sciences from University of California, Los Angeles.

Climate Modeling: What To Do While We Wait for Exascale

3:30 – 4:30 p.m., Thursday, Feb. 5
Room 2246, Space Research Building

Cloud processes play a central role in the dynamics of the tropical atmosphere, but for many years the shortcomings of cloud parameterizations have limited our ability to simulate and understand important weather systems. Since about 2001, “super-parameterization” has emerged as a new path forward, complementing but not replacing conventional approaches. This talk will outline the method, summarize its strengths and limitations, and show some recent results, including climate change simulations.

This event is presented by the Department of Atmospheric, Oceanic, and Space Sciences, and the Michigan Institute for Computational Discovery and Engineering.

Registration open for NCSA Blue Waters Symposium for Petascale Science and Beyond — May 10-13

By | Events

The Third Annual NCSA Blue Waters Symposium will bring together leaders in petascale computational science and engineering and will be a tremendous opportunity for sharing successes and challenges in large-scale heterogeneous computing. Along with presentations from the Blue Waters science teams, the symposium will feature keynotes from innovative thinkers in science and will provide opportunities to share and discuss specific topics of interest.

The symposium will take place at the Sunriver Resort in Sunriver Oregon. For more information, visit the Symposium Web site.

International Summer School on HPC Challenges in Computational Science — March 11 application deadline

By | Educational, Events

Graduate students and postdoctoral scholars from institutions in Canada, Europe, Japan and the United States are invited to apply for the sixth International Summer School on HPC Challenges in Computational Sciences, to be held June 21-26, 2015, in Toronto, Canada.

Applications are due March 11, 2015. The summer school is sponsored by Compute/Calcul Canada, the Extreme Science and Engineering Discovery Environment (XSEDE) with funds from the U.S. National Science Foundation, the Partnership for Advanced Computing in Europe (PRACE) and the RIKEN Advanced Institute for Computational Science (RIKEN AICS) in Japan.

Leading American, European and Japanese computational scientists and HPC technologists will offer instruction on a variety of topics, including:

  • HPC challenges by discipline (e.g, earth, life and materials sciences, physics)
  • HPC programming proficiencies
  • Performance analysis & profiling
  • Algorithmic approaches & numerical libraries
  • Data-intensive computing
  • Scientific visualization
  • Canadian, EU, Japanese and U.S. HPC-infrastructures

The expense-paid program is geared to advanced scholars from Canadian, European, Japanese and U.S. institutions who use HPC to conduct research. Interested students should apply by March 11, 2015. Meals, housing, and travel will be covered for the selected participants. Applications from graduate students and postdocs in all science and engineering fields are welcome. Preference will be given to applicants with parallel programming experience, and a research plan that will benefit from the utilization of high performance computing systems.

Further information and application visit the program Web site.

HPC 100: Introduction to Linux — Jan. 22

By | Educational, Events

A few seats are still open for the first HPC 100: Introduction to Linux course of the winter term. The course will familiarize students with the basics of accessing and interaction with high performance computers using the GNU/Linux operating system command line. Through hands on experience, students will learn the command line interface to high computing performance systems or other Linux systems for manipulating and analyzing data.

Date: Thursday, Jan. 22

Time: 1 – 4 p.m.

Location: B743 East Hall, 530 Church Street.

Instructor: Kenneth Weiss, IT Project Senior Manager, Medical School Information Services (MSIS)

Visit the course page for more information, and to register.

To see a complete listing of HPC training courses being offered this year, visit our Training and Workshops page.

ICPSR Summer Undergraduate Internship Program accepting applications — Jan. 31 deadline

By | Educational, Events

The ICPSR summer internship program provides undergraduate students with a unique and expansive research experience that introduces all aspects of social science research and includes supported exploration of a research query from start to finish, data management training, and focused methodological education in quantitative research. This prepares interns for capstone or senior thesis projects, graduate school, and/or research-based employment opportunities. The students, under the supervision of faculty mentors, develop a research question, perform a literature search and review, complete data analysis, and report findings in a poster; learn good data management processes and research practices with a research process mentor; and attend classes at the ICPSR Summer Program in Quantitative Methods.

Applications are being accepted through Jan. 31. Visit the internship website for more information.

Texas Advanced Computing Center hosts undergraduate computational summer training — Feb. 16 application deadline

By | Educational, Events

This summer in Austin, 10 undergraduates majoring in science and engineering disciplines will be immersed in training at The University of Texas at Austin to be the next generation of ‘game changers’. Participants will explore grand challenges such as climate modeling, weather forecasting, drug delivery, brain mapping, energy exploration and understanding the human genome, to name a few.

The program runs from June 1 to Aug. 1, and participants will receive a stipend for work, travel, and housing. The deadline to apply is Feb. 16.

Visit the TACC Integrative Computational Education and Research Traineeship website for more details and to apply.

Registration open for winter term HPC training

By | Educational, Events

Registration is open for a series of ARC-sponsored training courses and workshops in high performance computing in January and February. Each session — beginning, intermediate and advanced — will be offered three times.

HPC100 — Introduction to the Linux Command Line for HPC
1 – 4 p.m., B743 East Hall
Thursday, January 22
Monday, February 2
Friday, February 4
This course will familiarize students with the basics of accessing and interacting with high-performance computers using the GNU/Linux operating system’s command line. For more information, and to register, visit this page.

HPC101 — High Performance Computing Workshop
1 – 5 p.m., B743 East Hall
Tuesday, February 3
Monday, February 9
Wednesday, February 11
This course provides an overview of cluster computing in general and how to use the Flux cluster in particular. (Prerequisite: HPC 100 or equivalent.)
For more information, and to register, visit this page.

HPC201 — Advanced High Performance Computing Workshop
1 – 5 p.m., B743 East Hall
Thursday, February 5
Friday, February 13
Monday, February 16
This course will cover some more advanced topics in cluster computing on the U-M Flux Cluster. Topics to be covered include a review of common parallel programming models and basic use of Flux; dependent and array scheduling; advanced troubleshooting and analysis using checkjob, qstat, and other tools; use of common scientific applications including Python, MATLAB, and R in parallel environments; parallel debugging and profiling of C and Fortran code, including logging, gdb (line-oriented debugging), ddt (GUI-based debugging) and map (GUI-based profiling) of MPI and OpenMP programs; and an introduction to using GPUs. (Prerequisite: HPC101 or equivalent.)
For more information, and to register, visit this page.

CSCAR offering workshop on regression modeling in Python — Jan. 7 and 8

By | Educational, Events

CSCAR will offer a two-part workshop on regression modeling in Python. The main focus will be on linear models and generalized linear models (logistic, Poisson, and negative binomial regression). The statistical background will be reviewed briefly, but the main emphasis will be on fitting regression models using Python and its scientific libraries. All software discussed in the workshop is free and open source, and runs on all major platforms. There is no charge to attend the workshop.

For more information, contact

Training materials are available at:

Date: Jan. 7 and 8 (participants should plan to attend both days)

Time: 4 – 6 p.m.

Location: Rackham Commons Room, Lower Level.