XSEDE15 conference seeks student participation

High school and college students are encouraged to participate in the XSEDE15 Student Program.

XSEDE15, the fourth conference of XSEDE, the Extreme Science and Engineering Discovery Environment, will be held July 26-30, 2015, at the Marriott Renaissance Grand Hotel in downtown St. Louis, Missouri. XSEDE15 will showcase the discoveries, innovations, challenges and achievements of those who utilize and support XSEDE resources and services, as well as other digital resources and services, throughout the world.

By participating in the Student Program, high school, undergraduate, or graduate students can:

  • Meet computational and domain scientists from around the country who use high-performance systems in their research.
  • Compete in a student poster contest that shares your research involving advance cyberinfrastructure.
  • Attend introductory tutorials tailored for students new to computational science or more advanced tutorials designed to help you get the most out of XSEDE resources.
  • Present your research by submitting a paper to the XSEDE15 Technical Program.
  • Compete in a team-based student modeling and simulation challenge.

Pending final approval, the National Science Foundation may provide limited funding to support student travel, lodging, and/or registration costs for attending XSEDE15.

For details on the Student Program, see the Call for Participation:
https://conferences.xsede.org/technical-program/student-program

To apply for travel funding, see the XSEDE15 Student Travel Grant Application:
https://www.surveymonkey.com/s/XSEDE15TravelGrantApp

To submit your poster or paper, see the XSEDE15 website:
https://www.xsede.org/xsede15

Please contact Jenett Tillotson, XSEDE15 Student and EOT Program Chair at jtillots@iu.edu if you have questions.

ARC/ICOS Big Data Summer Camp — June 1-4 & 11

This year, the Interdisciplinary Committee on Organizational Studes (ICOS) and ARC are again offering a one-week “big data summer camp” for doctoral students in the social sciences interested in organizational research, with a combination of detailed examples from researchers; hands-on instruction in Python, SQL, and APIs; and group work to apply these ideas to organizational questions.

The dates of the camp are all day June 1-4 and the afternoon of June 11 for group project presentations. Enrollment is free, but students must commit to attending all day for each day of camp, and be willing to work in interdisciplinary groups.

To sign up for camp, visit the registration page.  Please note that space is limited, and we will be accepting people on a first-come, first-served basis. There are no pre-requisites, but we will expect all participants to complete some online instruction prior to camp and to bring a laptop to class with all the relevant programs and files loaded and ready.

A summary of last year’s boot camp is available on the ARC web site.

SC15 conference seeks student volunteers — June 1 application deadline

The SC15 conference in Austin, Texas, in November is taking applications for student volunteers. The deadline to apply is June 1.

Conference organizers say they are accepting an increased number of students from the U.S. and internationally. Student volunteers can attend tutorials, technical talks, panels, poster sessions, and workshops.

For information on how to apply, visit the SC15 Student Volunteer web page, or email student-vols@info.supercomputing.org

Open meeting for HPC users at U-M — May 22

Users of high performance computing resources are invited to meet Flux operators and support staff in person at an upcoming user meeting:

  • Friday, May 22, 1 – 5 p.m., NCRC Building 520, Room 1122 (Directions)

There is not a set agenda; come at anytime and stay as long as you please. You can come and talk about your use of any sort of computational resource, Flux, Nyx, XSEDE, or other.

Ask any questions you may have. The Flux staff will work with you on your specific projects, or just show you new things that can help you optimize your research.

This is also a good time to meet other researchers doing similar work.

This is open to anyone interested; it is not limited to Flux users.

Examples potential topics:

  • What Flux/ARC services are there, and how to access them?
  • How to make the most of PBS and learn its features specific to your work?
  • I want to do X, do you have software capable of it?
  • What is special about GPU/Xeon Phi/Accelerators?
  • Are there resources for people without budgets?
  • I want to apply for grant X, but it has certain limitations. What support can ARC provide?
  • I want to learn more about the compiler and debugging?
  • I want to learn more about performance tuning, can you look at my code with me?
  • Etc.

For more information, contact Brock Palen (brockp@umich.edu) at the College of Engineering; Dr. Charles Antonelli (cja@umich.edu) at LSA; Jeremy Hallum (jhallum@umich.edu) at the Medical School; or Vlad Wielbut (wlodek@umich.edu) at SPH.

HPC workshops on campus — May 11, 14, and 18

The spring schedule has been set for on-campus high performance computing workshops sponsored by ARC.

HPC100 — Introduction to the Linux Command Line for HPC
1 – 4 p.m., B737 East Hall
Monday, May 11
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., B737 East Hall
Thursday, May 14
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., B737 East Hall
Monday, May 18
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.

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

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.

ICPSR summer workshop on exploratory data mining — April 30 application deadline

The Inter-university Consortium for Political and Social Research (ICPSR) is putting on a workshop titled Exploratory Data Mining via SEARCH Strategies. Admission to the course is competitive and seating is limited. Apply through the ICPSR Summer Program Portal.

DESCRIPTION: This workshop provides an overview of current techniques in exploratory data mining for quantitative research in the social and behavioral sciences. Exploratory data mining uses computational methods on large amounts of data in order to construct predictive models of behavior, in contrast to the standard hypothesis testing of many standard statistical techniques. These data mining techniques can be used to model categorical choices, to classify groups, to discover patterns, and to model longitudinal data. Exploratory data mining techniques can be fruitful in most situations where categorical regression or many multivariate analytic techniques are used.

DATES AND TIME: June 8 – 12, 2015, 9 a.m.-5 p.m.

LOCATION: Ann Arbor, Michigan

INSTRUCTOR: John J. McArdle, University of Southern California

FEES: There are no registration fees for accepted participants. The first ten (10) admitted workshop participants will receive a travel stipend of $500.

SPECIAL AWARDS: Those completing the course will be eligible to compete for two (2) $15,000 awards for innovative uses of SEARCH.

DEADLINE:The application deadline is April 30, 2015.

QUESTIONS?: Contact the ICPSR Summer Program at sumprog@icpsr.umich.edu or (734) 763-7400.

XSEDE new user training — April 24

The XSEDE new user training is a 90 minute webinar providing general overview and reference information for first-time users of XSEDE resources at any of XSEDE’s service providers. This session is particularly targeted at users who have just received their first allocation on XSEDE. It is not intended to teach programming, numerical methods, or computational science, but rather to provide a quick tour of what XSEDE has to offer.

Topics covered will include:

  • Overview of XSEDE resources and services
  • How to sign on to / access XSEDE systems and the Common User Environment
  • Moving data in and out of XSEDE
  • Basics of running jobs
  • XSEDE User Portal training and documentation resources
  • How to get help
  • Extended and Collaborative support
  • Software availability
  • Allocations

Significant time will be allotted for Q&A. This webcast is free, and open to all users or prospective users of XSEDE resources. Participants will receive instructions via email on how to access the webcast.

This session will begin at 1 p.m. Eastern time Friday, April 24th. XSEDE will provide certification through Moodle for course participation. Information related to certification will be provided during the training.

Visit the XSEDE User Portal to register.

Open meetings for HPC users at U-M — April 23, May 22

Users of high performance computing resources are invited to meet Flux operators and support staff in person at two upcoming user meetings:

  • Thursday, April 23, 1 – 5 p.m., Room 2610, School of Public Health Building I
  • Friday, May 22, 1 – 5 p.m., NCRC Building 520, Room 1122 (Directions)

There is not a set agenda; come at anytime and stay as long as you please. You can come and talk about your use of any sort of computational resource, Flux, Nyx, XSEDE, or other.

Ask any questions you may have. The Flux staff will work with you on your specific projects, or just show you new things that can help you optimize your research.

This is also a good time to meet other researchers doing similar work.

This is open to anyone interested; it is not limited to Flux users.

Examples potential topics:

  • What Flux/ARC services are there, and how to access them?
  • How to make the most of PBS and learn its features specific to your work?
  • I want to do X, do you have software capable of it?
  • What is special about GPU/Xeon Phi/Accelerators?
  • Are there resources for people without budgets?
  • I want to apply for grant X, but it has certain limitations. What support can ARC provide?
  • I want to learn more about the compiler and debugging?
  • I want to learn more about performance tuning, can you look at my code with me?
  • Etc.

For more information, contact Brock Palen (brockp@umich.edu) at the College of Engineering; Dr. Charles Antonelli (cja@umich.edu) at LSA; Jeremy Hallum (jhallum@umich.edu) at the Medical School; or Vlad Wielbut (wlodek@umich.edu) at SPH.

MIDAS micro Big Data Analytics workshop — April 21-24

The Michigan Institute for Data Science (MIDAS) is organizing a micro Big Data Analytics workshop to openly discuss, share and collaborate on developing the foundation for developing a new Compressive Big Data Analytics (CBDA) theory. The highlights of the workshop are seminars by Dr. Saeid Amiri (Nebraska) and Dr. Ejaz Ahmed (Brock U).

Compressive Big Data Analytics (CBDA):

This is a high-risk/high-potential-impact idea. Basically, we are working on developing the foundations of a Compressive Big Data Analytics (CBDA) framework involving iterative generation of random (sub)samples from a Big Data collection, using classical techniques to develop model-based or non-parametric inference, repeat the (re)sampling and inference steps many times, and finally employ bootstrapping techniques to quantify probabilities, estimate likelihoods, or assess accuracy of findings. We are looking for collaborators with students that can help in the algorithmic development, deriving upper bound error estimates and demonstrating the application of this technique on several large, heterogeneous and multi-source datasets.

We expect that the CBDA approach may provide a scalable solution avoiding some of the Big Data management and analytics challenges. CBDA sampling is conducted on the data-element level, not on the case level, and the sampled values are not necessarily consistent across all data elements (e.g., high-throughput random sampling from cases and variables within cases).  We are now investigating the theoretical properties (e.g., asymptotics, as sample sizes increase to infinity, but the data has sparse conditions) of model-free inference entirely based on the complete dataset without any parametric or model-limited restrictions.

Saeid Amiri

Presenter: Dr. Saeid Amiri (http://statistics.unl.edu/saeid-amiri)

Visit: April 21-23, 2015

Title: Random Subspace Scientific Inference based on High dimensional data

Seminar: Tuesday, April 21, 2015, 4:00-5:00 p.m., Palmer Commons, Great Lakes Room North

Abstract: Extraction of valuable information from  Big data (n>>p) in high dimensions  (p>>n) and the subsequent scientific inference using such derived information present considerable challenges in many medical, biological, social and data-driven sciences. In this talk, I will present statistical learning and unsupervised machine learning techniques for the low dimension data  and discuss a new sub-space alternative approach. We will illustrate an extension method  for higher-dimensions and big data based on random subspaces.   We provide a series of arguments to justify the new technique and will provide examples involving real and simulated data to compare our method with other related techniques.

Ejaz Ahmed

Presenter: Dr. Ejaz Ahmed (http://statistics.unl.edu/saeid-amiri) (http://www.brocku.ca/mathematics-science/departments-and-centres/mathematics/people/professors/syed-ejaz-ahmed), distinguished prof at Brock U/Canada.

Visit: April 23-24, 2015

Title: TBD

Seminar: Friday, April 24, 2015, TBD (morning), place TBD

Abstract: TBD