[SC2 jobs] NAG (Numerical Algorithms Group)

By | SC2 jobs

NAGlogoNAGlogoStudent Placement: Computational Software Engineer

Gain invaluable experience developing technical software in a commercial setting

About the Role

NAG is looking for a Computational Software Engineer to undertake one or more projects within their Development Division. The precise nature of the projects will depend on business needs at the time and on the successful candidate’s skills, but typical examples could be:

  • Porting and testing versions of NAG software to different software or hardware environments.
  • Writing code to implement new algorithms in the NAG Library, along with suitable test programs and documentation.
  • Re-writing code contributed by third-parties to NAG standards and incorporating it into the NAG Library.
  • Using software tools to investigate code coverage of existing test programs.
  • Developing programs which demonstrate the capabilities and advantages of NAG software, to be used by our sales and marketing staff when meeting customers, attending trade shows etc.

For more information please see https://www.nag.com/content/student-placement-computational-software-engineer

University of Michigan researcher contributes to NASA findings on carbon in the atmosphere showcased in the journal Science

By | General Interest, Happenings, News

 

High-resolution satellite data from NASA’s Orbiting Carbon Observatory-2 are revealing the subtle ways that carbon links everything on Earth – the ocean, land, atmosphere, terrestrial ecosystems and human activities. Scientists using the first 2 1/2 years of OCO-2 data have published a special collection of five papers today in the journal Science that demonstrates the breadth of this research. In addition to showing how drought and heat in tropical forests affected global carbon dioxide levels during the 2015-16 El Niño, other results from these papers focus on ocean carbon release and absorption, urban emissions and a new way to study photosynthesis. A final paper by OCO-2 Deputy Project Scientist Annmarie Eldering of NASA’s Jet Propulsion Laboratory in Pasadena, California, and colleagues gives an overview of the state of OCO-2 science.

Manish Verma, a Geospatial/Data Science Consultant at the University of Michigan’s Consulting for Statistics, Computing and Analytics Research (CSCAR) unit, contributed as a coauthor to an article on a new way to measure photosynthesis over time and space.

Using data from the OCO-2, Verma’s analysis helped expand the utility of measurements of solar induced fluorescence (SIF), which indicates active photosynthesis in plants. Verma’s work showed that SIF data collected from the OCO-2 satellite provides reliable information on the variability of photosynthesis at a much smaller scale — down to individual ecosystems.

This can, in turn, “lead to more reliable estimates of carbon sources — that is, when, where, why and how carbon is exchanged between land and atmosphere — as well as a deeper understanding of carbon-climate feedbacks,” according to the Science article.

For more, see the NASA press release (https://www.nasa.gov/feature/jpl/new-insights-from-oco-2-showcased-in-science) and the Science article (http://science.sciencemag.org/content/358/6360/eaam5747.full)

The University of Michigan is live on IBM.com

By | News, Research

IBM is showcasing the current research developed with ConFlux, our ground-breaking cluster that uses IBM’s HPC and storage technology to enable scientists to draw on huge volumes of bid data and use machine learning to create reliable models for compute-intensive research.

“ With IBM hardware boosting our HPC environment, we can offer scientists the tools to conduct research that could revolutionize entire industries. ”
Todd Raeker, Research Technology Consultant for the University of Michigan.

To learn more please visit http://www-03.ibm.com/software/businesscasestudies/us/en/corp?synkey=A323848E50678F66

 

NVIDIA Grad Fellowship applications are open for the 2018-2019 academic year

By | Educational, Funding Opportunities

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NVIDIA just launched their 17th Annual Graduate Fellowship Program for the 2018-2019 academic year, which advances the frontiers of science by awarding grants and providing technical support to graduate students who are doing outstanding GPU-based research. If you are or know of a student that uses ConFlux, please encourage them to apply as very few people have access to the types of GPUS available on Conflux, which might make their application more competitive.

This year they are especially seeking doctoral students pushing the envelope in AI, deep neural networks, autonomous vehicles, and related fields. NVIDIA’s Graduate Fellowship awards are now up to $50,000 per student. These grants will be awarded in the 2018-2019 academic year.

Since its inception in 2002, the NVIDIA Graduate Fellowship Program has awarded over 140 Ph.D. graduate students with grants that have helped accelerate their research efforts. More importantly, this funding has helped some students achieve major breakthroughs in their research – breakthroughs that may not have been possible without additional funding.

The NVIDIA Graduate Fellowship Program is open to applicants worldwide. There is a new submission portal, and the deadlines for submissions are Dec. 13, 2017 (nomination letters) and Dec. 15, 2017 (applications). Students should be sure to start their application process early, as they use the portal to request their nomination letters in advance.

Eligible graduate students will have already completed their first year of Ph.D. level studies in the areas of computer science, computer engineering, system architecture, electrical engineering, or a related area. In addition, applicants must also be engaged in active research as part of their thesis work.

For more information on eligibility and how to apply, visit http://research.nvidia.com/graduate-fellowships or email fellowship@nvidia.com.

Faculty search in Computational Science at U-M

By | Uncategorized

MICDE is pleased to bring to your attention a faculty search in Computational Science at University of Michigan. This position will be filled within the Mechanical Engineering Department, but the search will be carried out with the active engagement of MICDE. We expect that the successful candidate will be a highly visible affiliate of MICDE, and will leverage its resources.

We are interested in candidates of any rank, who can bring advances in computer science, data-driven modeling and/or mathematics to bear upon the most compelling questions in engineering science. MICDE strives to define future paradigms of computational science, in collaboration with traditional disciplines in engineering and science. This is the environment that a successful candidate will have to develop a career.

All applicants should submit, in PDF format:
(1) a detailed resume,
(2) a statement of research and teaching interests,
(3) up to three representative publications, and
(4) the names and contact information of at least three references.

Applications must be submitted electronically at http://me.engin.umich.edu/facultysearch.

The University of Michigan is a non-discriminatory/affirmative action employer and is responsive to the needs of dual career families.

For more information please visit https://me.engin.umich.edu/about/positions/faculty.

Computational Science around U-M: Ph.D. Candidate Shannon Moran (Chemical Engineering) has won an ACM SIGHPC Intel Fellowship

By | Happenings, HPC, Uncategorized

Moran_HighRes_SqShannon Moran, a Ph.D. Candidate in the department of Chemical Engineering, has won a 2017 SIGHPC Intel Fellowship. Shannon is a member of the Glotzer Group. They use computer simulation to discover the fundamental principles of how nanoscale systems of building blocks self-assemble, and to discover how to control the assembly process to engineer new materials.

ACM’s Special Interest Group on High Performance Computing is an international group with a major professional society that is devoted to the needs of students, faculty, researchers and practitioners in high performance computing. This year they awarded 12 fellowships around the country with the aim of increasing the diversity of students pursuing graduate degrees in data science and computational science, including women as well as students from racial/ethnic backgrounds that have been historically underrepresented in the computing field. The fellowship provides $15,000 annually for study anywhere in the world.

The fellowship is funded by Intel and is presented at the annual Super Computing conference that this year will take place in November 13-16 in Denver, Colorado.

U-M joins NSF-funded SLATE project to simplify scientific collaboration on a massive scale

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

From the Cosmic Frontier to CERN, New Platform Stitches Together Global Science Efforts

SLATE will enable creation of new platforms for collaborative science

Today’s most ambitious scientific quests — from the cosmic radiation measurements by the South Pole Telescope to the particle physics of CERN — are multi-institutional research collaborations requiring computing environments that connect instrumentation, data, and computational resources. Because of the scale of the data and the complexity of this science,  these resources are often distributed among university research computing centers, national high performance computing centers, or commercial cloud providers.  This can cause scientists to spend more time on the technical aspects of computation than on discoveries and knowledge creation, while computing support staff are required to invest more effort integrating domain specific software with limited applicability beyond the community served.  

With Services Layer At The Edge (SLATE), a $4 million project funded by the National Science Foundation, the University of Michigan joins a team led by the Enrico Fermi and Computation Institutes at University of Chicago to provide technology that simplifies connecting university and laboratory data center capabilities to the national cyberinfrastructure ecosystem. The University of Utah is also participating. Once installed, SLATE connects local research groups with their far-flung collaborators, allowing central research teams to automate the exchange of data, software and computing tasks among institutions without burdening local system administrators with installation and operation of highly customized scientific computing services. By stitching together these resources, SLATE will also expand the reach of domain-specific “science gateways” and multi-site research platforms.  

“Science, ultimately, is a collective endeavor. Most scientists don’t work in a vacuum, they work in collaboration with their peers at other institutions,” said Shawn McKee, a co-PI on the project and director of the Center for Network and Storage-Enabled Collaborative Computational Science at the University of Michigan. “They often need to share not only data, but systems that allow execution of workflows across multiple institutions. Today, it is a very labor-intensive, manual process to stitch together data centers into platforms that provide the research computing environment required by forefront scientific discoveries.”

SLATE works by implementing “cyberinfrastructure as code”, augmenting high bandwidth science networks with a programmable “underlayment” edge platform. This platform hosts advanced services needed for higher-level capabilities such as data and software delivery, workflow services and science gateway components.  

U-M  has numerous roles in the project including:

  • defining, procuring and configuring much of the SLATE hardware platform
  • working on the advanced networking aspects (along with Utah) which includes Software Defined Networking (SDN) and Network Function Virtualization (NFV),
  • developing the SLATE user interface and contributing to the core project design and implementation.

The project is similar to the OSiRIS project led by McKee, which also aims to remove bottlenecks to discovery posed by networking and data transfer infrastructure.

SLATE uses best-of-breed data center virtualization components, and where available, software defined networking, to enable automation of lifecycle management tasks by domain experts. As such, it simplifies the creation of scalable platforms that connect research teams, institutions and resources, accelerating science while reducing operational costs and development time. Since SLATE needs only commodity components, it can be used for distributed systems across all data center types and scales, thus enabling creation of ubiquitous, science-driven cyberinfrastructure.

slateAt UChicago, the SLATE team will partner with the Research Computing Center and Information Technology Services to help the ATLAS experiment at CERN, the South Pole Telescope and the XENON dark matter search collaborations create the advanced cyberinfrastructure necessary for rapidly sharing data, computer cycles and software between partner institutions.  The resulting systems will provide blueprints for national and international research platforms supporting a variety of science domains.  

For example, the SLATE team will work with researchers from the Computation Institute’s Knowledge Lab to develop a hybrid platform that elastically scales computational social science applications between commercial cloud and campus HPC resources. The platform will allow researchers to use their local computational resources with the analytical tools and sensitive data shared through Knowledge Lab’s Cloud Kotta infrastructure, reducing cost and preserving data security.

“SLATE is about creating a ubiquitous cyberinfrastructure substrate for hosting, orchestrating and managing the entire lifecycle of higher level services that power scientific applications that span multiple institutions,” said Rob Gardner, a Research Professor in the Enrico Fermi Institute and Senior Fellow in the Computation Institute. “It clears a pathway for rapidly delivering capabilities to an institution, maximizing the science impact of local research IT investments.”

Many universities and research laboratories use a “Science DMZ” architecture to balance security with the ability to rapidly move large amounts of data in and out of the local network. As sciences from physics to biology to astronomy become more data-heavy, the complexity and need for these subnetworks grows rapidly, placing additional strain on local IT teams.

That stress is further compounded when local scientists join multi-institutional collaborations, often requiring the installation of specialized, domain-specific services for the sharing of compute and data resources.

With SLATE, research groups will be able to fully participate in multi-institutional collaborations and contribute resources to their collective platforms with minimal hands-on effort from their local IT team. When joining a project, the researchers and admins can select a package of software from a cloud-based service — a kind of “app store” — that allows them to connect and work with the other partners.

“Software and data can then be updated automatically by experts from the platform operations and research teams, with little to no assistance required from local IT personnel,” said Joe Breen, Senior IT Architect for Advanced Networking Initiatives at the University of Utah’s Center for High Performance Computing. “While the SLATE platform is designed to work in any data center environment, it will utilize advanced network capabilities, such as software defined overlay networks, when the devices support it.”

By reducing the technical expertise and time demands for participating in multi-institution collaborations, the SLATE platform will be especially helpful to smaller universities that lack the resources and staff of larger institutions and computing centers. The SLATE functionality can also support the development of “science gateways” which make it easier for individual researchers to connect to HPC resources such as the Open Science Grid and XSEDE.

“A central goal of SLATE is to lower the threshold for campuses and researchers to create research platforms within the national cyberinfrastructure,” Gardner said.

Initial partner sites for testing the SLATE platform and developing its architecture include New Mexico State University and Clemson University, where the focus will be creating distributed  cyberinfrastructure in support of large scale bioinformatics and genomics workflows. The project will also work with the Science Gateways Community Institute, an NSF funded Scientific Software Innovation Institute, on SLATE integration to make gateways more powerful and reach more researchers and resources.

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The Computation Institute (CI), a joint initiative of the University of Chicago and Argonne National Laboratory, is an intellectual nexus for scientists and scholars pursuing multi-disciplinary research and a resource center for developing and applying innovative computational approaches. Founded in 1999, it is home to over 100 faculty, fellows, and staff researching complex, system-level problems in such areas as biomedicine, energy and climate, astronomy and astrophysics, computational economics, social sciences and molecular engineering. CI is home to diverse projects including the Center for Robust Decision Making on Climate and Energy Policy, Knowledge Lab, The Urban Center for Computation and Data and the Center for Data Science and Public Policy.

For more information, contact Dan Meisler, Communications Manager, Advanced Research Computing at U-M: dmeisler@umich.edu, 734-764-7414

Info sessions on graduate studies in computational and data sciences — Sept. 21 and 25

By | Educational, Events, General Interest, News, Research

Learn about graduate programs that will prepare you for success in computationally intensive fields — pizza and pop provided

  • The Ph.D. in Scientific Computing is open to all Ph.D. students who will make extensive use of large-scale computation, computational methods, or algorithms for advanced computer architectures in their studies. It is a joint degree program, with students earning a Ph.D. from their current departments, “… and Scientific Computing” — for example, “Ph.D. in Aerospace Engineering and Scientific Computing.”
  • The Graduate Certificate in Computational Discovery and Engineering trains graduate students in computationally intensive research so they can excel in interdisciplinary HPC-focused research and product development environments. The certificate is open to all students currently pursuing Master’s or Ph.D. degrees at the University of Michigan.
  • The Graduate Certificate in Data Science is focused on developing core proficiencies in data analytics:
    1) Modeling — Understanding of core data science principles, assumptions and applications;
    2) Technology — Knowledge of basic protocols for data management, processing, computation, information extraction, and visualization;
    3) Practice — Hands-on experience with real data, modeling tools, and technology resources.

Times / Locations:

MICDE sponsored miRcore Biotechnology Summer Camp for the second year in a row

By | Happenings, HPC, Uncategorized

miRcoreBioTec2017This year’s miRcore’s Biotechnology summer camp was a big success.  The participants had hands-on experience in a wet-lab, and with the UNIX command line while accessing U-M’s High Performance Computing cluster, Flux, in a research setting. For the second year in a row MICDE and ARC-ts sponsored the campers to access Flux as they learned the steps that are needed to run code in a computer cluster. The camp also combined theoretical thermodynamic practices that gave participants an overall research experience in nucleotide biotechnology.

miRcore’s camps are designed to expose high school students to career opportunities in biomedicine and to provide research opportunities beyond the classroom setting. For more information please visit http://www.mircore.org/summer-camps/.

Siqian Shen (IOE) to receive an Early Career Award from the Department of Energy

By | News, Research

siqian-shen-featuredMICDE Associate Director Siqian Shen has been selected to receive an Early Career Award for the Department of Energy Office of Science by the DoE Office of Advanced Scientific Computing Research. The objective of her proposal titled “Extreme‐Scale Stochastic Optimization and Simulation via Learning‐Enhanced Decomposition and Parallelization” is to develop an efficient and unified framework that integrates machine learning with discrete optimization and risk‐averse modeling. The models considered represent a broad class of complex decision‐making problems, where 0‐1 or continuous decisions are made before and/or after knowing multiple and potentially correlated sources of uncertainties. This research will shed new light on the traditional decomposition algorithms for high‐performance computing.

Prof. Shen was recently promoted to Associate Professor of Industrial and Operations Engineering. To learn more about her research please visit http://micde.umich.edu/faculty-member/siqian-shen/.

The Early Career Award program from the US Department of Energy is a funding opportunity for researchers in universities and DOE national laboratories to support the development of individual research programs of outstanding scientists early in their careers. For the past 8 years this program has helped stimulate research careers in the disciplines supported by the DOE Office of Science. These include Advanced Scientific Computing Research (ASCR); Biological and Environmental Research (BER); Basic Energy Sciences (BES), Fusion Energy Sciences (FES); High Energy Physics (HEP), and Nuclear Physics (NP).