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Award Detail

Doing Business As Name:University of Oregon Eugene
  • Boyana Norris
  • (541) 346-4413
  • Peter L Ralph
Award Date:05/11/2021
Estimated Total Award Amount: $ 1,214,001
Funds Obligated to Date: $ 1,214,001
  • FY 2021=$1,214,001
Start Date:09/01/2021
End Date:08/31/2025
Transaction Type:Grant
Awarding Agency Code:4900
Funding Agency Code:4900
CFDA Number:47.070
Primary Program Source:040100 NSF RESEARCH & RELATED ACTIVIT
Award Title or Description:Collaborative Research: Framework Implementation: CSSI: CANDY: Cyberinfrastructure for Accelerating Innovation in Network Dynamics
Federal Award ID Number:2104115
DUNS ID:079289626
Parent DUNS ID:049793995
Program:Software Institutes
Program Officer:
  • Tevfik Kosar
  • (703) 292-7992

Awardee Location

Awardee Cong. District:04

Primary Place of Performance

Organization Name:University of Oregon Eugene
Cong. District:04

Abstract at Time of Award

Efficient analysis of dynamic networks is highly important in diverse multidisciplinary real-life applications, such as data mining and analytics, social and biological networks, epidemiology, cyber-physical infrastructures, transportation networks, surface mining, and cybersecurity. Although numerous software exists for analyzing static networks, a comprehensive cyberinfrastructure that supports innovative research challenges in large-scale, complex, dynamic networks is lacking. This multi-university proposal addresses this gap by developing a novel platform, called CANDY (Cyberinfrastructure for Accelerating Innovation in Network Dynamics), based on efficient, scalable parallel algorithm design for dynamic networks and high-performance software development with performance optimization. For broader impact and outreach activities, the investigators will (1) collaborate with multidisciplinary research groups to evaluate the effectiveness of the developed platform, algorithms and software tools; (2) host workshops, webinars, and tutorials to educate research community about the cyberinfrastructure; (3) disseminate project outcomes via a dedicated website, keynote and invited talks, demos, and high-quality publications in peer-reviewed journals and conferences; and (4) train next generation data scientists in the development of CANDY platform, by engaging women and underrepresented minority students, including high school students and rural communities in Missouri, Hispanic and African-American communities in Texas, and First Nation (Native American) community in Oregon. This project will develop the first parallel, scalable, extendable, and user-friendly software platform for updating important properties of dynamic networks. It will also provide the requisite functionalities and tools to modify existing algorithms or create new ones, catering to basic, intermediate and advanced users with different levels of expertise. The CANDY cyberinfrastructure platform will be implemented on different architectures, such as distributed memory, shared memory, and graphics processor units providing user-friendly interfaces. Significant research and development innovations include: (1) a novel hierarchical taxonomy of network analysis algorithms that allows for layered specification of parallel algorithms based on multiple parameters; (2) templates for creating new scalable algorithms for dynamic network analysis; (3) algorithms to partition the streaming set of nodes and edges into network snapshots at changing points; and (4) invariant-based quantifiable performance metrics for analyzing large-scale dynamic networks. As a case study, the developed software will be evaluated on two disparate domains -- fast processing of genomic data on dynamic trees, and cost-effective operation of complex mining engineering applications. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

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