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ARC Director Sharon Broude Geva elected Chair of the Coalition for Academic Scientific Computation

By | HPC, News

Dr. Sharon Broude Geva, Director of Advanced Research Computing at the University of Michigan, has been elected Chair of the Coalition for Academic Scientific Computation (CASC) for 2019.

Founded in 1989, CASC advocates for the use of advanced computing technology to accelerate scientific discovery for national competitiveness, global security, and economic success. The organization’s members represent 87 institutions of higher education and national labs.

The chair position is one of four elected CASC executive officers. The officers work closely as a team with the director of CASC. The Chair is responsible for arranging and presiding over general CASC meetings and acts as an official representative of CASC.

Geva served as CASC secretary in 2015 and 2016, and vice-chair in 2017 and 2018.

The other executive officers for 2019 are Neil Bright, Georgia Institute of Technology, Vice Chair; Craig Stewart, Indiana University, Secretary; Scott Yockel, Harvard University, Treasurer; Rajendra Bose, Columbia University, past chair. Lisa Arafune is CASC Director.

 

U-M prepares for SC18 conference in Dallas

By | General Interest, Happenings, News

University of Michigan researchers and IT staff are gearing up for extensive participation in the Supercomputing ‘18 conference (SC18) in Dallas from Nov. 11-16.

SC “Perennial” Quentin Stout, U-M professor of Electrical Engineering and Computer Science and one of only 19 people who have been to every Supercomputing conference, will once again co-present a tutorial titled Parallel Computing 101.

And with the recent announcement of a new HPC cluster on campus called Great Lakes, IT staff from Advanced Research Computing – Technology Services (ARC-TS) will be making multiple presentations around the conference on the details of the new supercomputer.

U-M will be at exhibit booth 1204A, adjacent to the Michigan State University booth, highlighting our computational and data-intensive research as well as the comprehensive set of tools and services we provide to our researchers. Representatives from all ARC units will be at the booth: ARC-TS, the Michigan Institute for Data Science (MIDAS), the Michigan Institute for Computational Discovery and Engineering (MICDE), and Consulting for Statistics, Computing and Analytics Research (CSCAR).

The booth will also feature two demonstrations: one will focus on the Open Storage Research Infrastructure or OSiRIS, the multi-institutional software-defined data storage system, and the Services Layer At The Edge (SLATE) project, both of which are supported by the NSF; the other will test conference-goers’ ability to detect “fake news” stories compared to an artificial intelligence system created by researchers supported by MIDAS.

U-M Activities

Sunday, Nov. 11

8:30 a.m. – 5 p.m.
Tutorial: Parallel Computing 101: Prof. Stout and Associate Professor Christiane Jablonowski of the U-M Department of Climate and Space Sciences and Engineering will provide a comprehensive overview of parallel computing.

8:30am – noon
Introduction to Kubernetes. Presented by Bob Killen, Research Cloud Administrator, and Scott Paschke, Research Cloud Solutions Designer, both from ARC-TS. Containers have shifted the way applications are packaged and delivered. Their use in data science and machine learning is skyrocketing with the beneficial side effect of enabling reproducible research. This rise in use has necessitated the need to explore and adopt better container-centric orchestration tools. Of these tools, Kubernetes – an open-source container platform born within Google — has become the de facto standard. This half-day tutorial will introduce researchers and sys admins who may already be familiar with container concepts to the architecture and fundamental concepts of Kubernetes. Attendees will explore these concepts through a series of hands-on exercises and leave with the leg-up in continuing their container education, and gain a better understanding of how Kubernetes may be used for research applications.

Tuesday, Nov. 13

Brock Palen, Director of ARC-TS, will speak about the new Great Lakes HPC cluster:

  • DDN booth (3123), 1:30 p.m.
  • Mellanox booth (3207), 3:30 p.m.
  • Dell booth (3218), 4:30 p.m.

11 a.m. – noon
Todd Raeker, Research Technology Consultant for ARC-TS, will be at the Globus booth (4201) to talk about U-M researchers’ use of the service.

12:15pm – 1:15pm
Birds of a Feather: Meeting HPC Container Challenges as a Community. Bob Killen, Research Cloud Administrator at ARC-TS, will give a lightning talk as part of this session that will present, prioritize, and gather input on top issues and budding solutions around containerization of HPC applications.

2 p.m.
Sharon Broude Geva, Director of ARC, will be live on the SC18 News Desk discussing ARC HPC services, Women in HPC, and the Coalition for Scientific Academic Computation (CASC). The stream will be available from the Supercomputing Twitter account: https://twitter.com/Supercomputing

5:15pm – 6:45pm
Birds of a Feather: Ceph Applications in HPC Environments: Ben Meekhof, HPC Storage Administrator at ARC-TS, will give a lightning talk on Ceph and OSiRIS as part of this session. More details at https://www.msi.umn.edu/ceph-hpc-environments-sc18

7 p.m.
ARC is a sponsor of the Women in HPC Reception. See the event description for more details and to register. Sharon Broude Geva, Director of ARC, will give a presentation.

Wednesday, Nov. 14

1 – 2 p.m.
Todd Raeker, Research Technology Consultant for ARC-TS, will be at the Globus booth (4201) to talk about U-M researchers’ use of the service.

1:30 p.m.
Brock Palen, Director of ARC-TS, will speak the SLURM booth (1242) about the new Great Lakes HPC cluster:

5:15 – 6:45 p.m.
Birds of a Feather: Cloud Infrastructure Solutions to Run HPC Workloads: Bob Killen, Research Cloud Administrator at ARC-TS, will present at this session aimed at architects, administrators, software engineers, and scientists interested in designing and deploying cloud infrastructure solutions such as OpenStack, Docker, Charliecloud, Singularity, Kubernetes, and Mesos.

Follow ARC on Twitter at https://twitter.com/ARC_UM for updates.

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/.

ARC-TS seeks pilot users for two new research storage services

By | General Interest, Happenings, HPC, News

Advanced Research Computing – Technology Services (ARC-TS) is seeking pilot users for two new research storage services.

The first, Locker, is group project storage focused on large data sets, and is available at a cost less than half that of current primary storage services. Locker still provides encryption, replication, snapshots, and workstation access. Example use cases for Locker are research projects in climate studies, genomics, imaging, and other data-intensive sciences.

The second service, Data Den, provides archive class storage for research data that is not actively used. As our lowest cost research storage offering, Data Den provides “cold storage” for massive amounts of data with 20 petabytes of encrypted and replicated capacity. Data Den allows researchers to preserve data between rounds of funding and management plans, and to free up space in more expensive primary storage by moving valuable, but not currently used, data.

Those interested in participating in the pilots should contact ARC-TS at hpc-support@umich.edu.

U-M part of new software institute on high-energy physics

By | General Interest, Happenings, News, Research

The University of Michigan is part of an NSF-supported 17-university coalition dedicated to creating next-generation computing power to support high-energy physics research.

Led by Princeton University, the Institute for Research and Innovation in Software for High Energy Physics (IRIS-HEP) will focus on developing software and expertise to enable a new era of discovery at the Large Hadron Collider (LHC) at CERN in Geneva, Switzerland.

Shawn McKee, Research Scientist in the U-M Department of Physics, is a co-PI of the institute. His His work will focus on integrating and extending the Open Storage Grid networking activities with similar efforts at the LHC.

For more information, see Princeton’s press release, and the NSF’s announcement.

New course for fall 2018: On-Ramp to Data Science for Chemical Engineers

By | Educational, General Interest, Happenings, News

Description: Engineers are encountering and generating a ever-growing body of data and recognizing the utility of applying data science (DataSci) approaches to extract knowledge from that data. A common barrier to learning DataSci is the stack of prerequisite courses that cannot fit into the typical engineering student schedule. This class will remove this barrier by, in one semester, covering essential foundational concepts that are not part of many engineering disciplines’ core curricula. These include: good programming practices, data structures, linear algebra, numerical methods, algorithms, probability, and statistics. The class’s focus will be on how these topics relate to data science and to provide context for further self-study.

Eligibility: College of Engineering students, pending instructor approval.

More information: http://myumi.ch/LzqPq

Instructor: Heather Mayes, Assistant Professor, Chemical Engineering, hbmayes@umich.edu.

University of Michigan awarded Women in High Performance Computing chapter

By | General Interest, News

The University of Michigan has been recognized as one of the first Chapters in the new Women in High Performance Computing (WHPC) Pilot Program.

“The WHPC Chapter Pilot will enable us to reach an ever-increasing community of women, provide these women with the networks that we recognize are essential for them excelling in their career, and retaining them in the workforce.” says Dr. Sharon Broude Geva, WHPC’s Director of Chapters and Director of Advanced Research Computing (ARC) at the University of Michigan (U-M). “At the same time, we envisage that the new Chapters will be able to tailor their activities to the needs of their local community, as we know that there is no ‘one size fits all’ solution to diversity.”

“At WHPC we are delighted to be accepting the University of Michigan as a Chapter under the pilot program, and working with them to build a sustainable solution to diversifying the international HPC landscape” said Dr. Toni Collis, Chair and co-founder of WHPC, and Chief Business Development Officer at Appentra Solutions.

The process of selecting organizations to participate in the program accounted for potential conflicts of interest; Geva did not vote on U-M’s application.

About Women in High Performance Computing (WHPC) and the Chapters and Affiliates Pilot Program

Women in High Performance Computing (WHPC) was created with the vision to encourage women to participate in the HPC community by providing fellowship, education, and support to women and the organizations that employ them. Through collaboration and networking, WHPC strives to bring together women in HPC and technical computing while encouraging women to engage in outreach activities and improve the visibility of inspirational role models.

WHPC has launched a pilot program for groups to become Affiliates or Chapters. The program will share the knowledge and expertise of WHPC as well as help to tailor activities and develop diversity and inclusion goals suitable to the needs of local HPC communities. During the pilot, WHPC will work with the Chapters and Affiliates to support and promote the work of women in their organizations, develop crucial role models, and assist employers in the recruitment and retention of a diverse and inclusive HPC workforce.

WHPC is stewarded by EPCC at the University of Edinburgh. For more information visit http://www.womeninhpc.org.  

For more information on the U-M chapter, contact Dr. Geva at sgeva@umich.edu.

MIDAS researchers’ papers accepted at ACM KDD data science conference in London

By | General Interest, Happenings, News, Research

Several U-M faculty affiliated with MIDAS will participate in the KDD2018 Conference in London in August. The meeting is held by the Associate for Computing Machinery’s Special Interest Group in Knowledge Discovery and Data Mining (KDD).

U-M researchers had the following papers accepted:

Learning Adversarial Networks for Semi-Supervised Text Classification via Policy Gradient
Yan Li (U-M); Jieping Ye (U-M)

TINET: Learning Invariant Networks via Knowledge Transfer
Chen Luo (Rice University); Zhengzhang Chen (NEC Laboratories America); Lu-An Tang (NEC Laboratories America); Anshumali Shrivastava (Rice University); Zhichun Li (NEC Laboratories America); Haifeng Chen (NEC Laboratories America); Jieping Ye (U-M)

Modeling Task Relationships in Multi-task Learning with Multi-gate Mixture-of-Experts
Jiaqi Ma(U-M); Zhe Zhao (Google); Xinyang Yi (Google); Jilin Chen (Google); Lichan Hong (Google); Ed Chi (Google)

Learning Credible Models
Jiaxuan Wang (U-M); Jeeheh Oh (U-M); Haozhu Wang (U-M); Jenna Wiens (U-M)

Deep Multi-Output Forecasting: Learning to Accurately Predict Blood Glucose Trajectories
Ian Fox (U-M); Lynn Ang (U-M); Mamta Jaiswal (U-M); Rodica Pop-Busui (U-M); Jenna Wiens (U-M)

ActiveRemediation: The Search for Lead Pipes in Flint, Michigan
Jacob Abernethy (Georgia Institute of Technology); Alex Chojnacki (U-M); Arya Farahi (U-M); Eric Schwartz (U-M); Jared Webb (Brigham Young University)

Career Transitions and Trajectories: A Case Study in Computing
Tara Safavi (U-M); Maryam Davoodi (Purdue University); Danai Koutra (U-M)

In addition, U-M Professor Jieping Ye will present at the event’s Artificial Intelligence in Transportation tutorial, and U-M Assistant Professor Qiaozhu Mei will speak as part of Deep Learning Day.

Deep learning in pharmacogenomics: from gene regulation to patient stratification

By | News, Research

MIDAS-affiliated researchers recently published a review of current and future applications of deep learning in pharmacogenomics.

Title: Deep learning in pharmacogenomics: from gene regulation to patient stratification
Published in: Pharmacogenomics, April 2018
DOI: 10.2217/pgs-2018-0008
Authors: Alexandr A. Kalinin, Gerald A. Higgins, Narathip Reamaroon, S. M. Reza Soroushmehr, Ari Allyn-Feuer, Ivo D. Dinov, Kayvan Najarian, Brian D. Athey, Alexandr A Kalinin, Gerald A Higgins, Sayedmohammadreza Soroushmehr, Ivo D Dinov, Brian D Athey
Abstract: This Perspective provides examples of current and future applications of deep learning in pharmacogenomics, including: identification of novel regulatory variants located in noncoding domains of the genome and their function as applied to pharmacoepigenomics; patient stratification from medical records; and the mechanistic prediction of drug response, targets and their interactions. Deep learning encapsulates a family of machine learning algorithms that has transformed many important subfields of artificial intelligence over the last decade, and has demonstrated breakthrough performance improvements on a wide range of tasks in biomedicine. We anticipate that in the future, deep learning will be widely used to predict personalized drug response and optimize medication selection and dosing, using knowledge extracted from large and complex molecular, epidemiological, clinical and demographic datasets.