Award Abstract # 1939140
Phase-II IUCRC Texas Tech University: Center for Cloud and Autonomic Computing

NSF Org: CNS
Division Of Computer and Network Systems
Recipient: TEXAS TECH UNIVERSITY SYSTEM
Initial Amendment Date: March 12, 2020
Latest Amendment Date: May 24, 2024
Award Number: 1939140
Award Instrument: Continuing Grant
Program Manager: Mohan Kumar
mokumar@nsf.gov
 (703)292-7408
CNS
 Division Of Computer and Network Systems
CSE
 Directorate for Computer and Information Science and Engineering
Start Date: March 15, 2020
End Date: February 28, 2026 (Estimated)
Total Intended Award Amount: $500,000.00
Total Awarded Amount to Date: $1,498,590.00
Funds Obligated to Date: FY 2020 = $100,001.00
FY 2021 = $377,999.00

FY 2022 = $349,217.00

FY 2023 = $481,210.00

FY 2024 = $190,163.00
History of Investigator:
  • Yong Chen (Principal Investigator)
    yong.chen@ttu.edu
  • Susan Mengel (Co-Principal Investigator)
  • Alan Sill (Co-Principal Investigator)
  • Tommy Dang (Co-Principal Investigator)
Recipient Sponsored Research Office: Texas Tech University
2500 BROADWAY
LUBBOCK
TX  US  79409
(806)742-3884
Sponsor Congressional District: 19
Primary Place of Performance: Texas Tech University
TX  US  79409-3104
Primary Place of Performance
Congressional District:
19
Unique Entity Identifier (UEI): EGLKRQ5JBCZ7
Parent UEI:
NSF Program(s): IUCRC-Indust-Univ Coop Res Ctr
Primary Program Source: 01002223DB NSF RESEARCH & RELATED ACTIVIT
01002324DB NSF RESEARCH & RELATED ACTIVIT

01002122DB NSF RESEARCH & RELATED ACTIVIT

01002122RB NSF RESEARCH & RELATED ACTIVIT

01002425DB NSF RESEARCH & RELATED ACTIVIT

01002324RB NSF RESEARCH & RELATED ACTIVIT

01002223RB NSF RESEARCH & RELATED ACTIVIT

01002425RB NSF RESEARCH & RELATED ACTIVIT

01002021DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s): 5761, 8237
Program Element Code(s): 576100
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.070

ABSTRACT

In this project, Texas Tech University will extend the previously successful industry-driven research program of the Cloud and Autonomic Computing (CAC) Industry-University Cooperative Research Center (IUCRC) as part of the NSF IUCRC program. The CAC Center currently comprises participants from two principal academic institutions, Texas Tech University (TTU) and the University of Arizona (UA), as well as two affiliate sites associated with TTU: the University of North Texas and Texas State University, and two international sites associated with UA: Universidad de Sonora, Mexico and American University of Malta. The mission of the NSF CAC Center across all participating sites is to conduct research and development activities that advance the knowledge of how to design and engineer highly distributed (cloud) and highly automated (autonomic) computing systems for practical applications with stakeholders including industry, federal agencies, and academia together. This grant will extend the IUCRC research of the CAC at TTU from Phase I to Phase II.

The TTU site of the NSF CAC focuses on advances in algorithms, methods, standards, and tools for cloud and highly automated computing systems. The Phase-II program of CAC@TTU site will continue research and development in areas including: 1) code development and Application Programming Interface (API) design for data acquisition, procedural, and workflow control; 2) high-performance data analytics and visualization in the cloud and autonomic computing settings; 3) improvements to practical applications of methods that use these and other cloud and autonomic computing techniques and methods; 4) standards implementations and design for cloud software and underlying infrastructure; and 5) applications of the above to data center control based in both industry and academic arenas. The CAC@TTU site will pursue these overall themes while remaining open to new and emerging opportunities that relate to the needs of current and future industry members or that come up through pursuit of the program of research.

NSF funding for this project plays a key role in facilitating and promoting research collaboration among stakeholders including industry, federal agencies, and academia. This project will also train a broadly inclusive and globally competitive science workforce for the nation by integrating the latest development and advanced knowledge into mentoring and educational activities. Texas Tech University is a Hispanic-Serving Institution, and the Phase-II CAC@TTU effort will leverage its experience in Phase I to carry out research and development activities to have broader impacts, including targeted efforts to integrate hands-on learning experiences for historically under-represented population groups, actively engaging undergraduate students in research programs, and organizing community activities such as workshops and conferences. These activities will also be coordinated with the overall CAC center program of broader engagement.

The Phase-II CAC@TTU site will distribute portions of its output through GitHub repositories (https://github.com/nsfcac) and websites including https://nsfcac.org/, http://cac.ttu.edu/, and https://discl.cs.ttu.edu/ for public releases of software, data, and results. The project members will provide industry motivation, expertise, and materials to facilitate research and development progress. The websites and repositories will be maintained for three years past the project completion date, and principal investigators will strive to maintain the associated output software products that remain in use as long as possible.

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.

PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH

Note:  When clicking on a Digital Object Identifier (DOI) number, you will be taken to an external site maintained by the publisher. Some full text articles may not yet be available without a charge during the embargo (administrative interval).

Some links on this page may take you to non-federal websites. Their policies may differ from this site.

(Showing: 1 - 10 of 22)
Zhou, Jiang and Chen, Yong and Zheng, Mai and Wang, Weiping "Data Distribution for Heterogeneous Storage Systems" IEEE Transactions on Computers , v.72 , 2023 https://doi.org/10.1109/TC.2022.3223302 Citation Details
Zhou, Jiang and Chen, Yong and Xie, Wei and Dai, Dong and He, Shuibing and Wang, Weiping "PRS: A Pattern-Directed Replication Scheme for Heterogeneous Object-Based Storage" IEEE Transactions on Computers , v.69 , 2020 https://doi.org/10.1109/TC.2019.2954089 Citation Details
Wang, Xi and Williams, Brody and Leidel, John D. and Ehret, Alan and Kinsy, Michel and Chen, Yong "Remote Atomic Extension (RAE) for Scalable High Performance Computing" Proceedings of The 57th Design Automation Conference (DAC'20) , 2020 https://doi.org/10.1109/DAC18072.2020.9218589 Citation Details
Wang, Xi and Tumeo, Antonino and Leidel, John D. and Li, Jie and Chen, Yong "HAM: Hotspot-Aware Manager for Improving Communications With 3D-Stacked Memory" IEEE Transactions on Computers , v.70 , 2021 https://doi.org/10.1109/TC.2021.3066982 Citation Details
Wang, Xi and Leidel, John D. and Williams, Brody and Ehret, Alan and Mark, Miguel and Kinsy, Michel A. and Chen, Yong "xBGAS: A Global Address Space Extension on RISC-V for High Performance Computing" 2021 IEEE International Parallel and Distributed Processing Symposium (IPDPS) , 2021 https://doi.org/10.1109/IPDPS49936.2021.00054 Citation Details
Side, Mert and Williams, Brody and Leidel, John and Woodruff, Jonathan and Moore, Simon W. and Chen, Yong "Towards xBGAS on CHERI: Supporting a Secure Global Memory" , 2023 https://doi.org/10.1109/IPDPSW59300.2023.00100 Citation Details
Nguyen, Ngan V.T. and Hass, Jon and Dang, Tommy "TimeRadar: Visualizing the Dynamics of Multivariate Communities via Timeline Views" 2021 IEEE 45th Annual Computers, Software, and Applications Conference, COMPSAC 2021 , 2021 https://doi.org/10.1109/COMPSAC51774.2021.00057 Citation Details
Nguyen, Ngan V. and Nguyen, Bao D. and Dang, Tommy and Hass, Jon "ScagnosticsViewer: tracking time series patterns via scagnostics meatures" , 2020 https://doi.org/10.1145/3430036.3430072 Citation Details
Nguyen, Ngan and Hass, Jon and Chen, Yong and Li, Jie and Sill, Alan and Dang, Tommy "RadarViewer : Visualizing the dynamics of multivariate data" PEARC '20: Practice and Experience in Advanced Research Computing , 2020 https://doi.org/https://doi.org/10.1145/3311790.3404538 Citation Details
Li, Jie and Wang, Rui and Ali, Ghazanfar and Dang, Tommy and Sill, Alan and Chen, Yong "Workload Failure Prediction for Data Centers" , 2023 https://doi.org/10.1109/CLOUD60044.2023.00064 Citation Details
Li, Jie and Michelogiannakis, George and Maloney, Samuel and Cook, Brandon and Suarez, Estela and Shalf, John and Chen, Yong "Job Scheduling in High Performance Computing Systems with Disaggregated Memory Resources" , 2024 https://doi.org/10.1109/CLUSTER59578.2024.00033 Citation Details
(Showing: 1 - 10 of 22)

Please report errors in award information by writing to: awardsearch@nsf.gov.

Print this page

Back to Top of page