OUTSTANDING PAPER: Optimal and Adaptive Multiprocessor Real-Time Scheduling: The Quasi-Partitioning Approach

Massa, Ernesto; Lima, George; Regnier, Paul; Levin, Greg; Brandt, Scott

doi:10.1109/ecrts.2014.19

Cited by 15 publications

(8 citation statements)

References 17 publications

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“…As a first attempt to explore such a perspective, we extended one of the simplest optimal scheduling algorithms for identical multicore platforms toward two-type heterogeneous scheduling. Recently, new optimal scheduling algorithms, such as Bfair [20], RUN [21], U-EDF [22], and QPS [23], were proposed for identical multicore platforms with the aim of reducing the number of preemptions and migrations. As a future work, we will extend those advanced scheduling techniques to two-type heterogeneous scheduling with the additional consideration on two types of migration showing different costs, aiming at reducing the overall preemption and migration overheads.…”

Section: Discussionmentioning

confidence: 99%

Optimal Real-Time Scheduling on Two-Type Heterogeneous Multicore Platforms

Chwa

Seo

Lee

et al. 2015

2015 IEEE Real-Time Systems Symposium

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Motivated by the cutting-edge two-type heterogeneous multicore chips, such as ARM's big.LITTLE, that offer a practical support for migration, this paper studies the global (or fully-migrative) approach to two-type heterogeneous multicore scheduling. Our goal is to design an optimal fully-migrative scheduling framework. To achieve this goal in an efficient and simple manner, we break the scheduling problem into two subproblems: workload assignment and schedule generation. We propose a per-cluster workload assignment algorithm, called Hetero-Split, that determines the fractions of workload of each task to be assigned to both clusters without losing feasibility with the complexity of O(n log n), where n is the number of tasks. Furthermore, it provides a couple of important properties (e.g., a dual property) that help to generate an optimal schedule efficiently. We also derive scheduling guidelines to design optimal schedulers for two-type heterogeneous multicore platforms, called Hetero-Fair. By tightly coupling the solutions of Hetero-Split and Hetero-Fair, we develop the first optimal two-type heterogeneous multicore scheduling algorithm, called Hetero-Wrap, that has the same complexity (O(n)) as in the identical multicore case. Finally, concerning a practical point of view, we derive the first bounds on the numbers of intra-and inter-cluster migrations under two-type heterogeneous multicore scheduling, respectively.

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Section: Discussionmentioning

confidence: 99%

Optimal Real-Time Scheduling on Two-Type Heterogeneous Multicore Platforms

Chwa

Seo

Lee

et al. 2015

2015 IEEE Real-Time Systems Symposium

View full text Add to dashboard Cite

show abstract

“…LLF fails to schedule the above-mentioned example because task T 3 can only take the processor in the intervals [9,10], [19,20], and [29,30] before it can be prioritized over T 1 and T 2 at time t = 36, when it will have zero laxity. Therefore, T 3 will be executed to completion before its deadline at time t = 40.…”

Section: Examplementioning

confidence: 93%

“…The first problem is that sometimes, we have consecutive deadlines with only one unit of time, such as [14,15), [15,16), [16,17), [19,20), and [20,21). This will result in numerous preemptions and migrations.…”

Section: Example 1: Usg Versus Fair Scheduling Algorithmsmentioning

confidence: 97%

“…In [20], a new algorithm, namely, QPS (Quasi-Partitioned Scheduling), is introduced. It is able to schedule any feasible taskset with implicit deadlines on identical processors.…”

Section: Related Workmentioning

confidence: 99%

“…time slices as mentioned previously, which are bounded by two successive deadlines, and the end of each TL-plane corresponds to the deadline of a task in the system. Hence, tasks are marshalled in the intervals [0, 5), [5,7), [7,10), [10,14), [14,15), [15,16), [16,17), [17,19), [19,20), [20,21), [21,25), [25,26), [26,28), and [28,29), which correspond to the first 14 TL-planes, after which all tasks would finish at least one period of their executions. This means that at the beginning of each TL-plane, all tasks have to be allocated local executions proportional to their utilizations and marshalled until the end of the time slice at which they must all be preempted.…”

Section: Introductionmentioning

confidence: 99%

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