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Open Problems in Multi-Modal Scheduling theory for thermal-Resilient multicore Systems

Compositional & Parallel Real Time Systems. CoPaRTS. Open Problems in Multi-Modal Scheduling theory for thermal-Resilient multicore Systems. Department of Computer Science Wayne State University. Nathan Fisher , Masud Ahmed, and Pradeep Hettiarachchi.

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Open Problems in Multi-Modal Scheduling theory for thermal-Resilient multicore Systems

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  1. Compositional & Parallel Real Time Systems CoPaRTS Open Problems in Multi-Modal Scheduling theory for thermal-Resilient multicore Systems Department of Computer Science Wayne State University Nathan Fisher, Masud Ahmed, and PradeepHettiarachchi

  2. Designing hard-real-time systems with predictable degradation in a dynamic thermal environment. Required:Processor/Task Control Framework Thermal Resiliency [Motivation]: Heart Regulate Status Transmit Data Log Extensive Exercises • When surrounding temperature increases: • Reduce CPU thermal dissipation for the device safety. • Drop non-essential tasks on demand.

  3. Control Framework [Multi-Modal Overview] Temperature/Power and Workload Models Control System Design System Hardware Specification System Software Specification M3 M4 M1 M5 M2 (Task 2) (Task 1) Critical Priority vary over time (Task 3) High Priority (Task 5) Less Priority Less Priority (Task 4)

  4. How do we deal with changes of operating modes? Control Framework [Modes] • Real-time performance modes: M(1),…,M(q) • Each M(i) is a collection of sporadic tasks {τ(i)j}j=1…n and a periodic resource (i)=((i),(i)). • Possible to model processor with two power levels • Pact: active power • Pinc: inactive power Θ(i) Θ(i) Θ(i) Π(i) time

  5. Control Framework [Mode-Change Requests] M(j) M(i) M(k) Mode: Tasks: Resource: … … … time mcrk-1 mcrk Mode-Change Request Transition time Assumption: Mode-change request occurs at period boundaries

  6. Control Framework [Task Mode-Change Semantics] M(j) M(k) tk tk-1 + X Immediately Aborted Tasks α(ij) X Non-Aborted Tasks Unchanged Tasks τ(ij).

  7. Previous Work: Multi-modal UniprocessorSchedulability Analysis for Periodic Resources [ESTIMedia 2011, ACM-TECS 2014] Control Framework [Multi-Modal Schedulability Analysis] Busy Interval “BI5” Busy Interval “BI4” Busy Interval “BI1” Inter-Mode Schedulability Conditions Mj Mi Busy Interval “BI2” Busy Interval “BI3” Intra-Mode Schedulability Conditions

  8. Previous Work: Multi-modal UniprocessorSchedulability Analysis for Periodic Resources [ESTIMedia 2011, ACM-TECS 2014] Open Problem:Multi-modal Multiprocessor GlobalSchedulability Analysis for a Compositional Resource Model Control Framework [Schedulability Analysis] Mj Mi

  9. Multiprocessor Compositional Resource Models • Potential Models: • Multiprocessor Periodic Resource (MPR) Model: each resource characterized (i)=((i),(i), m(i)) [Shin et al, ECRTS ‘08] • Parallel Supply Function (PSF) Model [Bini et al, RTSS ‘09] Maximum Concurrency . . . . . . Pm -1 Pm Pm +1 Θ(i) (i) (i) (i) . . . P2 P1 time Π(i)

  10. Challenges/Issues • Transient backlog over multiple mode changes. • “Carry In/Out” calculations. • Time Complexity. • Relation to mixed-criticality scheduling? • “Optimal” resource parameters: • What is a good definition for thermal resiliency? • How do you calculate efficiently?

  11. Thank You! Questions? fishern@wayne.edu

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