| NSF Org: |
CNS Division Of Computer and Network Systems |
| Recipient: |
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| Initial Amendment Date: | June 3, 2011 |
| Latest Amendment Date: | June 3, 2011 |
| Award Number: | 1059284 |
| Award Instrument: | Standard Grant |
| Program Manager: |
Vasant G. Honavar
CNS Division Of Computer and Network Systems CSE Directorate for Computer and Information Science and Engineering |
| Start Date: | July 1, 2011 |
| End Date: | June 30, 2012 (Estimated) |
| Total Intended Award Amount: | $378,016.00 |
| Total Awarded Amount to Date: | $378,016.00 |
| Funds Obligated to Date: |
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| History of Investigator: |
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| Recipient Sponsored Research Office: |
341 PINE TREE RD ITHACA NY US 14850-2820 (607)255-5014 |
| Sponsor Congressional District: |
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| Primary Place of Performance: |
341 PINE TREE RD ITHACA NY US 14850-2820 |
| Primary Place of
Performance Congressional District: |
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| Unique Entity Identifier (UEI): |
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| Parent UEI: |
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| NSF Program(s): | CCRI-CISE Cmnty Rsrch Infrstrc |
| Primary Program Source: |
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| Program Element Code(s): |
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| Award Agency Code: | 4900 |
| Fund Agency Code: | 4900 |
| Assistance Listing Number(s): | 47.070 |
ABSTRACT
II-EN: Computing research infrastructure for constraint optimization, machine learning, and dynamical models for Computational Sustainability
High performance computing infrastructure will be acquired to support the research, outreach, and educational activities of researchers engaged by the Institute for Computational Sustainability (ICS) in a number of research projects which have significant computational needs. Computational sustainability is a new interdisciplinary field that aims to apply techniques from computer science, applied mathematics and related disciplines to help the balancing of environmental, economic, and societal needs for sustainable development. Computational sustainability research brings together computational sciences and a variety of other disciplines to focus on developing computational models, methods, and tools for supporting the design of sustainable policies, practices, products, and tools. ICS has established a number of significant research projects in areas ranging from biodiversity conservation, to natural resource management, poverty mapping, and material discovery for fuel cell technology.
Computational sustainability research is already leading to foundational contributions in several areas of Computer Science. Computational Sustainability presents decision and optimization problems with a mixture of continuous and discrete variables in highly dynamic and uncertain environments, pushing the boundaries of the current state-of-the art of computer science. ICS research focuses on integrating techniques from constraint reasoning, optimization, dynamical systems, machine learning, and data mining, in order to obtain effective dynamic decision theoretic models to address sustainability problems. The computing infrastructure requested would allow ICS researchers including 21 faculty, 53 students (including 24 undergraduates), and over a 100 collaborators to scale up their work to larger problems than they would have been otherwise be able to solve.
ICS research has direct impacts on policy makers and practitioners engaged in sustainability work. For example, working in collaboration with the Laboratory of Ornithology at Cornell, ICS researchers have provided computational analysis for the U.S. Department of the Interior's 2011 State of the Birds report. In collaboration with the U.S. Forest Service, ICS research is improving the design of wildlife corridors for species such as grizzly bears, wolverines, and lynx. ICS is working with The Conservation Fund to develop conservation plans that will be used by government and conservation agencies. In collaboration with the Cornell Fuel Cell Institute, ICS members are developing automated tools to support the discovery of new materials for fuel cell technology. ICS is also building a vibrant computational sustainability research community through conferences, workshops, lectures, and online discussions. Combined with ICS education and outreach activities, these research efforts promote teaching, training, and the advancement of women and underrepresented minorities in computer science. Additional information regarding the ICS and its efforts to meet the critical societal, environmental, and economic needs for knowledge, methods, and tools that advance computational sustainability efforts can be found at the ICS website: www.cis.cornell.edu/ics
PROJECT OUTCOMES REPORT
Disclaimer
This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.
The NSF award, II-EN: Computing research infrastructure for constraint optimization, machine learning, and dynamical models for Computational Sustainability (award 1059284), provided funds for Atlas, a 57 node (684 core) compute cluster with substantial memory resources. The Atlas cluster (atlas@cac.cornell.edu) was created in order to scale up research projects undertaken by the Institute for Computational Sustainability (ICS) to large real-world applications.
ICS, founded in 2008, is funded under the NSF Expeditions in Computing program in order to forge a highly interdisciplinary effort to establish and nurture the new field of Computational Sustainability, with the grand vision that computing and information science can — and should — play a key role in increasing the efficiency and effectiveness of the way we manage and allocate our natural resources. ICS has established a number of significant research projects in areas ranging from biodiversity, species preservation, natural resource management, to poverty mapping, fuel cell technology, and more. Atlas provides important infrastructure to support these research efforts.
Atlas became operational on December 8, 2011, with extensive testing and assistance provided by the Cornell Center for Advanced Computing (CAC), which is hosting and maintaining the cluster. Researchers from the Institute for Computational Sustainability (ICS) and its collaborators have been using the computing power and memory resources of Atlas to advance their research. A number of project teams, students, and faculty members have been using this resource to produce significant research contributions and publications. Some of these projects and teams are highlighted below, with an emphasis on the specific Atlas characteristics that are enabling and accelerating the specific research.
An ICS team is using Atlas to conduct research in materials discovery. They are developing computational techniques for enhancing the search for novel materials. The Atlas cluster allows the team to examine multiple experimental settings and material combinations. This research has the potential for significant impacts on society by assisting in the fast and efficient discovery of new materials that can be utilized for fuel-cell catalysis.
Another ICS team, working for the ChargeCar project, has also been using the Atlas server to estimate charging policies in multi-battery systems of electrical vehicles, based on current road features. This project aims to optimize real-time energy management of multi-battery systems in order to increase the life span of batteries. Atlas is significantly reducing the time for each experiment, which has the potential to enhance the viability of electrical vehicles as a more sustainable transportation alternative.
ICS team has another team using Atlas to explore the performance of new techniques to construct conservation corridors, which are continuous areas of protected land that link zones of biological significance. The research results will help conservation scientists and land managers in designing better wildlife corridors that meet species conservation needs while working within real world budget constraints.
ICS members are also collaborating with researchers from AT&T and AMNH, using the Atlas cluster to develop models on land-cover classification in the Arctic under future climate change scenarios. This research, which may help the public, scientists, and policy makers understand how climate change will affect the Arctic, requires Atlas’ large memory capacity.
USGS collaborators of ICS are also using Atlas to run simulations for an ecological project that will estimate density of carnivores along linear landscape features. This work is informing how to best allocate wil...
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