Award Abstract # 2151829
CNS Core: Small: Budgets, Budgets Everywhere: A Necessity for Safe Real-Time on Multicore

NSF Org: CNS
Division Of Computer and Network Systems
Recipient: UNIVERSITY OF NORTH CAROLINA AT CHAPEL HILL
Initial Amendment Date: July 13, 2022
Latest Amendment Date: July 13, 2022
Award Number: 2151829
Award Instrument: Standard Grant
Program Manager: Marilyn McClure
mmcclure@nsf.gov
 (703)292-5197
CNS
 Division Of Computer and Network Systems
CSE
 Directorate for Computer and Information Science and Engineering
Start Date: July 15, 2022
End Date: June 30, 2026 (Estimated)
Total Intended Award Amount: $500,000.00
Total Awarded Amount to Date: $500,000.00
Funds Obligated to Date: FY 2022 = $500,000.00
History of Investigator:
  • James Anderson (Principal Investigator)
    anderson@cs.unc.edu
Recipient Sponsored Research Office: University of North Carolina at Chapel Hill
104 AIRPORT DR STE 2200
CHAPEL HILL
NC  US  27599-5023
(919)966-3411
Sponsor Congressional District: 04
Primary Place of Performance: University of North Carolina at Chapel Hill
Department of Computer Science
Chapel Hill
NC  US  27599-3175
Primary Place of Performance
Congressional District:
04
Unique Entity Identifier (UEI): D3LHU66KBLD5
Parent UEI: D3LHU66KBLD5
NSF Program(s): CSR-Computer Systems Research
Primary Program Source: 01002223DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s): 7923
Program Element Code(s): 735400
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.070

ABSTRACT

Multicore computers are increasingly being used to implement real-time systems. In a real-time system, programs exist that are subject to timing constraints. An automobile is a good example: When a car's brake pedal is depressed, the braking system must react by a certain deadline. Many real-time systems are safety-critical, meaning that failures may have catastrophic consequences, such as loss of life or serious financial repercussions. Automobiles are also a good example of a safety-critical system; while a typical driver may be unaware of it, modern cars contain many computers that run a myriad of programs that perform functions required for steering, braking, engine control, etc. Safety-critical real-time systems typically must undergo a certification process that ensures that important functionality is properly supported. An important part of this process is to validate that deadline requirements are met, i.e., that programs execute "on time." To do this, worst-case execution times (WCETs) of programs should be known. Unfortunately, on today's complex multicore computers, determining accurate WCETs is difficult because the worst-case execution time of a program may occur under rare circumstances and thus be difficult to reproduce. The traditional defense against not knowing WCETs with absolute certainty is to have the operating system (OS) enforce execution budgets; a program's budget is a limit on its execution time that the OS ensures won't be exceeded.

While budgets have conventionally been enforced at the program level, in challenging real-time applications of interest today, such enforcement is needed at many levels. For example, in an autonomous vehicle, the overall system is broken into subsystems, where each subsystem provides some separate function, e.g., sensing obstacles in the road, computing a plan to react to obstacles, etc. These subsystems, which may contain many programs each, should be subject to budget enforcement as well. For instance, if the obstacle-sensing subsystem takes too much time, then executing the planning subsystem is pointless. This project is directed at (i) identifying the various levels at which budgets must be enforced in complex multicore real-time applications, (ii) examining the implications for real-time safety certification that arise from making multi-level budget enforcement a first-class concern, and (iii) producing efficient implementations of such enforcement. Addressing these goals will enable safer systems to be developed. In terms of broader impacts, a special emphasis will be placed on outreach to girls and women. Such outreach will include: events involving the Graduate Women in Computer Science (GWiCS) group at UNC, which hosts an annual research symposium targeted toward undergraduate women and other underrepresented minorities; Tar Heel Hack, a hackathon for local middle and high school girls; UNC Computer Science's Girls Who Code Club, which provides local girls in grades 6-12 with a community for learning about computer science; and UNC Computer Science's annual Open House and Science Expo. Further outreach to female students will be done in the context of a computer science club for undergraduate women led by the PI called TOPICS (Talking Over Papers In Computer Science).

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

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Ahmed, Shareef and Anderson, James H. "Leibniz International Proceedings in Informatics (LIPIcs):35th Euromicro Conference on Real-Time Systems (ECRTS 2023)" Proceedings of the 35th Euromicro Conference on Real-Time Systems , 2023 https://doi.org/10.4230/LIPIcs.ECRTS.2023.16 Citation Details
, J. Bakita and J. Anderson "Hardware Compute Partitioning on NVIDIA GPUs" Proceedings of the 29th IEEE Real-Time and Embedded Technology and Applications Symposium , 2023 Citation Details
Wagle, Rohan and Tong, Zelin and Sites, Richard L and Anderson, James H "Want Predictable GPU Execution? Beware SMIs!" Proceedings of the 29th IEEE International Conference on Parallel and Distributed Systems , 2023 https://doi.org/10.1109/ICPADS60453.2023.00285 Citation Details
Tong, Zelin and Ahmed, Shareef and Anderson, James H. "Holistically Budgeting Processing Graphs" Proceedings of the 44th IEEE Real-Time Systems Symposium , 2023 https://doi.org/10.1109/RTSS59052.2023.00013 Citation Details
Ahmed, Shareef and Anderson, James H. "Soft Real-Time Gang Scheduling" Proceedings of the 44th IEEE Real-Time Systems Symposium , 2023 https://doi.org/10.1109/RTSS59052.2023.00036 Citation Details
Bakita, Joshua and Anderson, James H "Demystifying NVIDIA GPU Internals to Enable Reliable GPU Management" Proceedings of the 30th IEEE Real-Time and Embedded Technology and Appli cations Symposium , 2024 Citation Details

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