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Beta cluster available for learning Slurm; new scheduler to be part of upcoming cluster updates

By | Flux, General Interest, Happenings, HPC, News

New HPC resources to replace Flux and updates to Armis are coming.  They will run a new scheduling system (Slurm). You will need to learn the commands in this system and update your batch files to successfully run jobs. Read on to learn the details and how to get training and adapt your files.

In anticipation of these changes, ARC-TS has created the test cluster “Beta,” which will provide a testing environment for the transition to Slurm. Slurm will be used on Great Lakes; the Armis HIPAA-aligned cluster; and a new cluster called “Lighthouse” which will succeed the Flux Operating Environment in early 2019.

Currently, Flux and Armis use the Torque (PBS) resource manager and the Moab scheduling system; when completed, Great Lakes and Lighthouse will use the Slurm scheduler and resource manager, which will enhance the performance and reliability of the new resources. Armis will transition from Torque to Slurm in early 2019.

The Beta test cluster is available to all Flux users, who can login via ssh at ‘beta.arc-ts.umich.edu’. Beta has its own /home directory, so users will need to create or transfer any files they need, via scp/sftp or Globus.

Slurm commands will be needed to submit jobs. For a comparison of Slurm and Torque commands, see our Torque to Slurm migration page. For more information, see the Beta home page.

Support staff from ARC-TS and individual academic units will conduct several in-person and online training sessions to help users become familiar with Slurm. We have been testing Slurm for several months, and believe the performance gains, user communications, and increased reliability will significantly improve the efficiency and effectiveness of the HPC environment at U-M.

The tentative time frame for replacing or transitioning current ARC-TS resources is:

  • Flux to Great Lakes, first half of 2019
  • Armis from Torque to Slurm, January 2019
  • Flux Operating Environment to Lighthouse, first half of 2019
  • Open OnDemand on Beta, which replaces ARC Connect for web-based job submissions, Jupyter Notebooks, Matlab, and additional software packages, fall 2018

U-M selects Dell EMC, Mellanox and DDN to Supply New “Great Lakes” Computing Cluster

By | Flux, General Interest, Happenings, HPC, News

The University of Michigan has selected Dell EMC as lead vendor to supply its new $4.8 million Great Lakes computing cluster, which will serve researchers across campus. Mellanox Technologies will provide networking solutions, and DDN will supply storage hardware.

Great Lakes will be available to the campus community in the first half of 2019, and over time will replace the Flux supercomputer, which serves more than 2,500 active users at U-M for research ranging from aerospace engineering simulations and molecular dynamics modeling to genomics and cell biology to machine learning and artificial intelligence.

Great Lakes will be the first cluster in the world to use the Mellanox HDR 200 gigabit per second InfiniBand networking solution, enabling faster data transfer speeds and increased application performance.

“High-performance research computing is a critical component of the rich computing ecosystem that supports the university’s core mission,” said Ravi Pendse, U-M’s vice president for information technology and chief information officer. “With Great Lakes, researchers in emerging fields like machine learning and precision health will have access to a higher level of computational power. We’re thrilled to be working with Dell EMC, Mellanox, and DDN; the end result will be improved performance, flexibility, and reliability for U-M researchers.”

“Dell EMC is thrilled to collaborate with the University of Michigan and our technology partners to bring this innovative and powerful system to such a strong community of researchers,” said Thierry Pellegrino, vice president, Dell EMC High Performance Computing. “This Great Lakes cluster will offer an exceptional boost in performance, throughput and response to reduce the time needed for U-M researches to make the next big discovery in a range of disciplines from artificial intelligence to genomics and bioscience.”

The main components of the new cluster are:

  • Dell EMC PowerEdge C6420 compute nodes, PowerEdge R640 high memory nodes, and PowerEdge R740 GPU nodes
  • Mellanox HDR 200Gb/s InfiniBand ConnectX-6 adapters, Quantum switches and LinkX cables, and InfiniBand gateway platforms
  • DDN GRIDScaler® 14KX® and 100 TB of usable IME® (Infinite Memory Engine) memory

“HDR 200G InfiniBand provides the highest data speed and smart In-Network Computing acceleration engines, delivering HPC and AI applications with the best performance, scalability and efficiency,” said Gilad Shainer, vice president of marketing at Mellanox Technologies. “We are excited to collaborate with the University of Michigan, Dell EMC and DataDirect Networks, in building a leading HDR 200G InfiniBand-based supercomputer, serving the growing demands of U-M researchers.”

“DDN has a long history of working with Dell EMC and Mellanox to deliver optimized solutions for our customers. We are happy to be a part of the new Great Lakes cluster, supporting its mission of advanced research and computing. Partnering with forward-looking thought leaders as these is always enlightening and enriching,” said Dr. James Coomer, SVP Product Marketing and Benchmarks at DDN.

Great Lakes will provide significant improvement in computing performance over Flux. For example, each compute node will have more cores, higher maximum speed capabilities, and increased memory. The cluster will also have improved internet connectivity and file system performance, as well as NVIDIA Tensor GPU cores, which are very powerful for machine learning compared to prior generations of GPUs.

“Users of Great Lakes will have access to more cores, faster cores, faster memory, faster storage, and a more balanced network,” said Brock Palen, Director of Advanced Research Computing – Technology Services (ARC-TS).

The Flux cluster was created approximately 8 years ago, although many of the individual nodes have been added since then. Great Lakes represents an architectural overhaul that will result in better performance and efficiency. Based on extensive input from faculty and other stakeholders across campus, the new Great Lakes cluster will be designed to deliver similar services and capabilities as Flux, including the ability to accommodate faculty purchases of hardware, access to GPUs and large-memory nodes, and improved support for emerging uses such as machine learning and genomics.

ARC-TS will operate and maintain the cluster once it is built. Allocations of computing resources through ARC-TS include access to hundreds of software titles, as well as support and consulting from professional staff with decades of combined experience in research computing.

Updates on the progress of Great Lakes will be available at https://arc-ts.umich.edu/greatlakes/.

MICDE announces 2018-2019 fellowship recipients

By | Educational, General Interest, Happenings, News

The Michigan Institute for Computational Discovery and Engineering (MICDE) is pleased to announce the 2018-2019 recipients of the MICDE Fellowships for students enrolled in the PhD in Scientific Computing or the Graduate Certificate in Computational Discovery and Engineering. The fellowships, which carry a $4,000 stipend, are meant to augment other sources of funding and are available to students in both programs. See our Fellowship page for more information.

AWARDEES

Zhitong Bai, Mechanical Engineering
Kyle Bushick, Materials Science and Engineering
Geunyeong Byeon, Industrial and Operations Engineering
Sehwan Chung, Civil and Environmental Engineering
Khoi Dang, Chemistry
Sicen Du, Materials Science and Engineering
Joseph Hollowed, Physics
Jia Li, Physics
Sabrina Lynch, Biomedical Engineering
Samar Minallah, Climate and Space Sciences and Engineering
Everardo Olide, Applied Physics
Shaowu Pan, Aerospace Engineering
Alicia Petersen, Climate and Space Sciences and Engineering
Vyas Ramasubramani, Chemical Engineering
Fabricio Vasselai, Political Science
Nathan Vaughn, Applied and Interdisciplinary Mathematics
Blair Winograd, Chemistry
Samuel Young, Chemical Engineering
Kexin Zhang, Chemistry
Bu Zhao, School of Environment and Sustainability