Category

Data

Sep 15 2023
0

HPC Emergency 2023 Maintenance: September 15

By | Data, HPC, News, Research, Systems and Services

Due to a critical issue which requires an immediate update, we will be performing updates to Slurm and underlying libraries which allow parallel jobs to communicate. We will be updating the login nodes and the rest of the cluster on the fly and you should only experience minimal impact when interacting with the clusters. 

  • Jobs that are currently running will be allowed to finish. 
  • All new jobs will only be allowed to run on nodes which have been updated. 
  • The login and Open OnDemand nodes will also be updated, which will require a brief interruption in service.

Queued jobs and maintenance reminders

Jobs will remain queued, and will automatically begin after the maintenance is completed. Any parallel using MPI will fail; those jobs may need to be recompiled, as described below. Jobs not using MPI will not be affected by this update.

Jobs will be initially slow to start, as compute nodes are drained of running jobs so they can be updated. We apologize for this inconvenience, and want to assure you that we would not be performing this maintenance during a semester unless it was absolutely necessary.

Software updates

Only one version of OpenMPI (version 4.1.6) will be available; all other versions will be removed. Modules for the versions of OpenMPI that were removed will warn you that it is not available, as well as prompt you to load openmpi/4.1.6. 

When you use the following command, it will default to openmpi/4.1.6:
module load openmpi 

Any software packages you use (provided by ARC/LSA/COE/UMMS or yourself) will need to be updated to use openmpi/4.1.6. The software package updates will be completed by ARC. The code you compile yourself will need to be updated by you.

Note that at the moment openmpi/3.1.6 will be discontinued and warned to update your use to openmpi/4.1.6.

Status updates

 

System software changes

Great Lakes, Armis2 and Lighthouse

NEW version in BOLD OLD version
Slurm 23.02.5 compiles with:
  • PMIx
    • /opt/pmix/3.2.5
    • /opt/pmix/4.2.6
  • hwloc 2.2.0-3 (OS provided)
  • ucx-1.15.0-1.59056 (OFED provided)
  • slurm-libpmi
  • slurm-contribs
 Slurm 23.02.3 compiles with:
  • PMIx
    • /opt/pmix/2.2.5
    • /opt/pmix/3.2.3
    • /opt/pmix/4.2.3
  • hwloc 2.2.0-3 (OS provided)
  • ucx-1.15.0-1.59056 (OFED provided)
  • slurm-libpmi
  • slurm-contribs
PMIx LD config /opt/pmix/3.2.5/lib PMIx LD config /opt/pmix/2.2.5/lib
PMIx versions available in /opt :
    • 3.2.5
    • 4.2.6
 PMIx versions available in /opt :
  • 2.2.5
  • 3.2.3
  • 4.1.2
OpenMPI
  • 4.1.6
 OpenMPI
  • 3.1.6
  • others

 

How can we help you?

For assistance or questions, contact ARC at arc-support@umich.edu.

Jul 18 2023
0

Summer 2023 Network Maintenance: HPC and storage unavailable August 21-22 

By | Data, HPC, News, Research, Systems and Services

During the 2023 summer maintenance, a significant networking software bug was discovered and ARC was unable to complete the ARC HPC and Storage network updates at the MACC Data Center.

ITS has been working with the vendor on a remediation, and it will be implemented on August 21-22.  This will require scheduled maintenance for the HPC clusters Great Lakes, Armis2, and Lighthouse, as well as the ARC storage systems Turbo, Locker, and Data Den. The date was selected to minimize any impact during the fall semester. 

Maintenance dates:

HPC clusters and storage systems (/home and /scratch) and ARC storage systems (Turbo, Locker, and Data Den) will be unavailable August 21 starting at 7:00am.  Expected completion date is August 22nd.

Queued jobs and maintenance reminders

Jobs will remain queued, and will automatically begin after the maintenance is completed. The command “maxwalltime” will show the amount of time remaining until maintenance begins for each cluster, so you can size your jobs appropriately. The countdown to maintenance will also appear on the ARC homepage. 

Status updates

How can we help you?

For assistance or questions, contact ARC at arc-support@umich.edu.

Jul 17 2023
0

Secure Enclave Service rate approved, shortcode needed by July 25 

By | Data, News, Systems and Services, Uncategorized

The Yottabyte Research Cloud (YBRC) migrated to the Secure Enclave Services (SES) in 2022. The new system provides improved performance for researcher workloads. Due to this transition, ARC began billing researchers who consume more than 16 gigabytes (GB) of RAM (memory) per month on July 1, 2023. 

The first 16 GB of RAM (memory) is covered by the U-M Research Computing Package (UMRCP). If you have not already requested or been granted the UMRCP, learn more and request it on the UMRCP service page on the ARC website.

Approved rate 

The approved rate for a Secure Enclave Services machine is $7.00 per GB of RAM (memory) per machine, per month. Visit the Rates page on the ARC website for information about billing for all ARC services. 

Action requested: Submit a shortcode 

A shortcode is needed to accommodate billing for any resources consumed that are not covered by the UMRCP. Please submit a shortcode no later than July 25, 2023. Access to your machine will be removed or reduced if a shortcode is not on file by July 25. Contact us at arc-support@umich.edu to submit your shortcode, or make any changes to the configuration or use of your machines. 

Some schools and colleges (including the U-M Medical School) are subsidizing the use of Secure Enclave Services beyond the 16 GB of RAM (memory). Talk to your unit’s IT staff or email ARC to learn more. 

Contact ARC (arc-support@umich.edu) if you would like to meet with the ARC storage manager to ask questions or get clarification.

Feb 22 2023
0

Globus maintenance happening at 9 a.m. on March 11

By | Armis2, Data, General Interest, Great Lakes, HPC, News, Research, Uncategorized

Due to planned maintenance by the vendor, Globus services will be unavailable for up to two hours beginning at 9 a.m. U.S. Eastern Time (10 a.m. Central Time) on Saturday, March 11, 2023.

Customers will not be able to authenticate or initiate any transfers during that time. Any transfers that have started before the outage will be stalled until the outage is over. Transfers will resume once maintenance is complete.

More details are available on the Globus blog.

For assistance or questions, please contact ARC at arc-support@umich.edu.

Feb 16 2022
0

Understanding the strongest electromagnetic fields in the universe

By | Data, Great Lakes, HPC, Research, Uncategorized

Alec Thomas is part of the team from the U-M College of Engineering Gérard Mourou Center for Ultrafast Optical Science that is building the most powerful laser in the U.S.

Dubbed “ZEUS,” the laser will be 3-petawatts of power. That’s a ‘3’ with 15 zeros. All the power generated in the entire world is 10-terawatts, or 1000 times less than the ZEUS laser. 

The team’s goal is to use the laser to explore how matter behaves in the most extreme electric and magnetic fields in the universe, and also to generate new sources of radiation beams, which may lead to developments in medicine, materials science, and national security. 

A simulation of a plasma wake.

This simulation shows a plasma wake behind a laser pulse. The plasma behaves like water waves generated behind a boat. In this image, the “waves” are extremely hot plasma matter, and the “boat” is a short burst of powerful laser light. (Image courtesy of Daniel Seipt.)

“In the strong electric fields of a petawatt laser, matter becomes ripped apart into a `plasma,’ which is what the sun is made of. This work involves very complex and nonlinear physical interactions between matter particles and light. We create six-dimensional models of particles to simulate how they might behave in a plasma in the presence of these laser fields to learn how to harness it for new technologies. This requires a lot of compute power,” Thomas said. 

That compute power comes from the Great Lakes HPC cluster, the university’s fastest high-performance computing cluster. The team created equations to solve a field of motion for each six-dimensional particle. The equations run on Great Lakes and help Thomas and his team to learn how the particle might behave within a cell. Once the field of motion is understood, solutions can be developed. 

“On the computing side, this is a very complex physical interaction. Great Lakes is designed to handle this type of work,” said Brock Palen, director of Advanced Research Computing, a division of Information and Technology Services. 

Thomas has signed up for allocations on the Great Lakes HPC cluster and Data Den storage. “I just signed up for the no-cost allocations offered by the U-M Research Computing Package. I am planning to use those allocations to explore ideas and concepts in preparation for submitting grant proposals.”

Learn more and sign up for the no-cost U-M Research Computing Package (UMRCP).

Prof. Thomas’ work is funded by a grant from the National Science Foundation.

Apr 30 2018
0

Yottabyte Research Cloud certified for CUI data

By | Data, General Interest, Happenings, News

Advanced Research Computing – Technology Services (ARC-TS) is pleased to announce that the Yottabyte Research Cloud (YBRC) computing platform is now certified to accept data designated as Controlled Unclassified Information (CUI). This includes certification for YBRC and its associated services, enabling secure data analysis on Windows and Linux virtual desktops as well as secure hosting of databases and data ingestion.

For more information on CUI, see the U-M Research Ethics and Compliance CUI webpage and Sensitive Data Guide: Controlled Unclassified Information (CUI). CUI regulations apply to federal non-classified information requiring security controls; an example of CUI data often used in research is data from the Centers for Medicare and Medicaid Services.

The new capability ensures the security of CUI data through the creation of firewalled network enclaves, allowing CUI data to be analyzed safely and securely in YBRC’s flexible, robust and scalable environment.  Within each network enclave, researchers have access to Windows and Linux virtual desktops that can contain any software required for their analysis pipeline.

This capability also extends to our database and ingestion services:

  • Structured databases:  MySQL/MariaDB, and PostgreSQL.
  • Unstructured databases: Cassandra, InfluxDB, Grafana, and ElasticSearch.
  • Data ingestion: Redis, Kafka, RabbitMQ.
  • Data processing: Apache Flink, Apache Storm, Node.js and Apache NiFi.
  • Other data services are available upon request.

The CUI certification extends YBRC’s existing capabilities for handling sensitive data; the service can also take HIPAA data, Export Controlled REsearch (ITAR, EAR), Personally Identifiable Information, and more. Please see Sensitive Data Guide: Yottabyte Research Cloud for more information.

YBRC is supported by U-M’s Data Science Initiative launched in 2015 and was created through a partnership between Yottabyte and ARC-TS. These tools are offered to all researchers at the University of Michigan free of charge, provided that certain usage limits are not exceeded. Large-scale users who outgrow the no-cost allotment may purchase additional YBRC resources. All interested parties should contact arcts-support@umich.edu.

Apr 20 2018
0

MIDAS Data Science for Music Challenge Initiative announces funded projects

By | Data, General Interest, Happenings, News, Research

From digital analysis of Bach sonatas to mining data from crowdsourced compositions, researchers at the University of Michigan are using modern big data techniques to transform how we understand, create and interact with music.

Four U-M research teams will receive support for projects that apply data science tools like machine learning and data mining to the study of music theory, performance, social media-based music making, and the connection between words and music. The funding is provided under the Data Science for Music Challenge Initiative through the Michigan Institute for Data Science (MIDAS).

“MIDAS is excited to catalyze innovative, interdisciplinary research at the intersection of data science and music,” said Alfred Hero, co-director of MIDAS and the John H. Holland Distinguished University Professor of Electrical Engineering and Computer Science. “The four proposals selected will apply and demonstrate some of the most powerful state-of-the-art machine learning and data mining methods to empirical music theory, automated musical accompaniment of text and data-driven analysis of music performance.”

Jason Corey, associate dean for graduate studies and research at the School of Music, Theatre & Dance, added: “These new collaborations between our music faculty and engineers, mathematicians and computer scientists will help broaden and deepen our understanding of the complexities of music composition and performance.”

The four projects represent the beginning of MIDAS’ support for the emerging Data Science for Music research. The long-term goal is to build a critical mass of interdisciplinary researchers for sustained development of this research area, which demonstrates the power of data science to transform traditional research disciplines.

Each project will receive $75,000 over a year. The projects are:

Understanding and Mining Patterns of Audience Engagement and Creative Collaboration in Large-Scale Crowdsourced Music Performances

Investigators: Danai Koutra and Walter Lasecki, both assistant professors of computer science and engineering

Summary: The project will develop a platform for crowdsourced music making and performance, and use data mining techniques to discover patterns in audience engagement and participation. The results can be applied to other interactive settings as well, including developing new educational tools.

Understanding How the Brain Processes Music Through the Bach Trio Sonatas
Investigators: Daniel Forger, professor of mathematics and computational medicine and bioinformatics; James Kibbie, professor and chair of organ and university organist

Summary: The project will develop and analyze a library of digitized performances of Bach’s Trio Sonatas, applying novel algorithms to study the music structure from a data science perspective. The team’s analysis will compare different performances to determine features that make performances artistic, as well as the common mistakes performers make. Findings will be integrated into courses both on organ performance and on data science.

The Sound of Text
Investigators: Rada Mihalcea, professor of electrical engineering and computer science; Anıl Çamcı, assistant professor of performing arts technology

Summary: The project will develop a data science framework that will connect language and music, developing tools that can produce musical interpretations of texts based on content and emotion. The resulting tool will be able to translate any text—poetry, prose, or even research papers—into music.

A Computational Study of Patterned Melodic Structures Across Musical Cultures
Investigators: Somangshu Mukherji, assistant professor of music theory; Xuanlong Nguyen, associate professor of statistics

Summary: This project will combine music theory and computational analysis to compare the melodies of music across six cultures—including Indian and Irish songs, as well as Bach and Mozart—to identify commonalities in how music is structured cross-culturally.

The Data Science for Music program is the fifth challenge initiative funded by MIDAS to promote innovation in data science and cross-disciplinary collaboration, while building on existing expertise of U-M researchers. The other four are focused on transportation, health sciences, social sciences and learning analytics.

Hero said the confluence of music and data science was a natural extension.

“The University of Michigan’s combined strengths in data science methodology and music makes us an ideal crucible for discovery and innovation at this intersection,” he said.

Contact: Dan Meisler, Communications Manager, Advanced Research Computing
734-764-7414, dmeisler@umich.edu

Mar 21 2018
0

Interdisciplinary Committee on Organizational Studies (ICOS) Big Data Summer Camp, May 14-18

By | Data, Educational, General Interest, Happenings, News
Social and organizational life are increasingly conducted online through electronic media, from emails to Twitter feed to dating sites to GPS phone tracking. The traces these activities leave behind have acquired the (misleading) title of “big data.” Within a few years, a standard part of graduate training in the social sciences will include a hefty dose of “using of big data,” and we will all be utilizing terms like API and Python.
This year ICOS, MIDAS, and ARC are again offering a one-week “big data summer camp” for doctoral students 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.  Enrollment is free, but students must commit to attending all day for each day of camp, and be willing to work in interdisciplinary groups.

The dates of the camp are all day May 14th-18th.

https://ttc.iss.lsa.umich.edu/ttc/sessions/interdisciplinary-committee-on-organizational-studies-icos-big-data-summer-camp-3/ 

Nov 01 2017
0

CSCAR provides walk-in support for new Flux users

By | Data, Educational, Flux, General Interest, HPC, News

CSCAR now provides walk-in support during business hours for students, faculty, and staff seeking assistance in getting started with the Flux computing environment.  CSCAR consultants can walk a researcher through the steps of applying for a Flux account, installing and configuring a terminal client, connecting to Flux, basic SSH and Unix command line, and obtaining or accessing allocations.  

In addition to walk-in support, CSCAR has several staff consultants with expertise in advanced and high performance computing who can work with clients on a variety of topics such as installing, optimizing, and profiling code.  

Support via email is also provided via hpc-support@umich.edu.  

CSCAR is located in room 3550 of the Rackham Building (915 E. Washington St.). Walk-in hours are from 9 a.m. – 5 p.m., Monday through Friday, except for noon – 1 p.m. on Tuesdays.

See the CSCAR web site (cscar.research.umich.edu) for more information.

Nov 01 2017
0

Info session: Consulting and computing resources for data science — Nov. 8

By | Data, Educational, Events, General Interest, Happenings, HPC

Advanced Research Computing at U-M (ARC) will host an information session for graduate students in all disciplines who are interested in new computing and data science resources and services available to U-M researchers.

Brief presentations from members of ARC Technology Services (ARC-TS) on computing infrastructure, and from Consulting for Statistics, Computing, and Analytics Research (CSCAR) on statistics, data science, and computing training and consulting will be followed by a Q&A session, and opportunities to interact individually with ARC and CSCAR staff.

ARC and CSCAR are interested in connecting with graduate students whose research would benefit from customized or innovative computational or analytic approaches, and can provide guidance for students aiming to do this. ARC and CSCAR are also interested in developing training and documentation materials for a diverse range of application areas, and would welcome input from student researchers on opportunities to tailor our training offerings to new areas.

Speakers:

  • Kerby Shedden, Director, CSCAR
  • Brock Palen, Director, ARC-TS

Date/Time/Location:

Wednesday, Nov. 8, 2017, 2 – 4 p.m., West Conference Room, 4th Floor, Rackham Building (915 E. Washington St.)

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