Category

Happenings

MIDAS announces winners of 2018 poster competition

By | Educational, General Interest, Happenings, Research

The Michigan Institute for Data Science (MIDAS) is pleased to announce the winners of its 2018 poster competition, which is held in conjunction with the MIDAS annual symposium.

The symposium was held on Oct. 9-10, 2018, and the student poster competition had more than 60 entries. The winners, judged by a panel of faculty members, received cash prizes.

Best Overall

Arthur Endsley, “Comparing and timing business cycles and land development trends in U.S. metropolitan housing markets”

Most likely health impact

  • Yehu Chen, Yingsi Jian, Qiucheng Wu, Yichen Yang, “Compressive Big Data Analytics – CBDA: Applications to Biomedical and Health Studies”
  • Jinghui Liu, “An Information Retrieval System with an Iterative Pattern for TREC Precision Medicine”

Most likely transformative science impact

  • Prashant Rajaram, “Bingeability and Ad Tolerance: New Metrics for the Streaming Media Age”
  • Mike Ion, “Learning About the Norms of Teaching Practice: How Can Machine Learning Help Analyze Teachers’ Reactions to Scenarios?”

Most interesting methodological advancement

  • Nina Zhou and Qiucheng Wu, “DataSifter: Statistical Obfuscation of Electronic Health Records and Other Sensitive Datasets”
  • Aniket Deshmukh, “Simple Regret Minimization for Contextual Bandits”

Most likely societal impact

  • Ece Sanci, “Optimization of Food Pantry Locations to Address Food Scarcity in Toledo, OH”
  • Rohail Syed, “Human Perception of Surprise: A User Study”

Most innovative use of data

  • Lan Luo, “Renewable Estimation and Incremental Inference in Generalized Linear Models with Streaming Datasets”
  • Danaja  Maldeniya, “Psychological Response of Communities affected by Natural Disasters in Social Media”

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.

MDST group wins KDD best paper award

By | General Interest, Happenings, MDSTPosts, Research

A paper by members and faculty leaders of the Michigan Data Science Team (co-authors: Jacob Abernethy, Alex Chojnacki, Arya Farahi, Eric Schwartz, and Jared Webb) won the Best Student Paper award in the Applied Data Science track at the KDD 2018 conference in August in London.

The paper, ActiveRemediation: The Search for Lead Pipes in Flint, Michigan, details the group’s ongoing work in Flint to detect pipes made of lead and other hazardous material.

For more on the team’s work, see this recent U-M press release.

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.

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.

CASC image competition open for submissions

By | General Interest, Happenings, News

The image competition for the Coalition for Academic Scientific Computation (CASC) 2019 annual brochure is now open. Winning images will be featured in the brochure, which is distributed to industry, government and academia. An image from U-M Aerospace Engineering Professor Joaquim Martins was on the cover of the 2016 edition, and several U-M investigators have had their work featured in the brochure in other years.

Images will be judged on the following criteria:

  • Illustrative of research underway at the center submitting the proposed images
  • Focus on research that offers a broad representation of what CASC members have undertaken
  • Timeliness of visualization relative to events currently in the news
  • Exhibits intellectual merit
  • Provides scientific, cultural, economic impact
  • Compelling, visually interesting, lively, colorful images in a  high-resolution format

Please send potential submissions to Dan Meisler, ARC Communications Manager, at dmeisler@umich.edu. The deadline is June 11, 2018.

ARC-TS joins Cloud Native Computing Foundation

By | General Interest, Happenings, News

Advanced Research Computing – Technology Services (ARC-TS) at the University of Michigan has become the first U.S. academic institution to join the Cloud Native Computing Foundation (CNCF), a foundation that advances the development and use of cloud native applications and services. Founded in 2015, CNCF is part of the Linux Foundation.

CNCF announced ARC-TS’s membership at the KubeCon and CloudNativeCon event in Copenhagen. A video of the opening remarks by CNCF Executive Director Dan Kohn can be viewed on the event website.

“Our membership in the CNCF signals our commitment to bringing cloud computing and containers technology to researchers across campus,” said Brock Palen, Director of ARC-TS. “Kubernetes and other CNCF platforms are becoming crucial tools for advanced machine learning, pipelining, and other research methods. We also look forward to bring an academic perspective to the foundation.”

ARC-TS’s membership and participation in the group signals its adoption and commitment to cloud-native technologies and practices. Users of containers and other CNCF services will have access to experts in the field.

Membership gives the U-M research community input into in the continuing development of cloud-native applications, and within CNCF-managed and ancillary projects. U-M is the second academic institution to join the foundation, and the only one in the U.S.