System-level scheduling of real-time streaming applications using a semi-partitioned approach

Cannella, Emanuele; Bamakhrama, Mohamed A.; Stefanov, Todor

doi:10.7873/date2014.376

Cited by 4 publications

(21 citation statements)

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“…This memory overhead is introduced because in distributed memory systems the code of all tasks should be replicated on all the available cores. As shown in [7], semipartitioning can ameliorate the bin-packing issues of partitioned scheduling without incurring the excessive overheads of global scheduling. (3) We assume that the system's communication infrastructure is predictable, i.e., it provides guaranteed communication latency.…”

Section: Scope Of Workmentioning

confidence: 99%

“…The technique presented in [4] has been recently extended by [7], which considers that the derived periodic task set is scheduled by an SRT scheduler with bounded task tardiness (see Definition 2). This extension is summarized in the following subsection.…”

Section: Derivation Of Minimum Periods Of Tasksmentioning

confidence: 99%

“…As long as tardiness is bounded by a value Δ i for each task τ i , earliest start times of each task τ i can be derived (Lemma 1 in [7]). The earliest start times of task τ i corresponds to the parameter S i defined in Sect.…”

Section: Earliest Start Times and Buffer Size Calculationmentioning

confidence: 99%

“…In contrast with [4], existing techniques that exploit the analysis of self-timed scheduling of SDF graphs to guarantee throughput constraints (e.g., [22]) necessitate a complex design space exploration (DSE) to determine the minimum number of processors needed to schedule the applications, and the mapping of tasks to processors. Based on the analysis of [4], a promising semi-partitioned approach [7] has been proposed recently to schedule streaming applications. In semi-partitioned scheduling most tasks are assigned statically to processors, while others (usually a few) can migrate.…”

mentioning

confidence: 99%

“…In semi-partitioned scheduling most tasks are assigned statically to processors, while others (usually a few) can migrate. In [7], these migrations are allowed at job boundaries only, to reduce overheads. Semi-partitioned approaches which satisfy this property are said to have restricted migrations.…”

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confidence: 99%

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Energy efficient semi-partitioned scheduling for embedded multiprocessor streaming systems

Cannella

Stefanov

2016

Des Autom Embed Syst

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In this paper, we study the problem of energy minimization when mapping streaming applications with throughput constraints to homogeneous multiprocessor systems in which voltage and frequency scaling is supported with a discrete set of operating voltage/frequency modes. We propose a soft real-time semi-partitioned scheduling algorithm which allows an even distribution of the utilization of tasks among the available processors. In turn, this enables processors to run at a lower frequency, which yields to lower energy consumption. We show on a set of real-life applications that our semi-partitioned scheduling approach achieves significant energy savings compared to a purely partitioned scheduling approach and an existing semi-partitioned one, EDF-os, on average by 36 % (and up to 64 %) when using the lowest frequency which guarantees schedulability and is supported by the system. By using a periodic frequency switching scheme that preserves schedulability, instead of this lowest supported fixed frequency, we obtain an additional energy saving up to 18 %. Although the throughput of applications is unchanged by the proposed semi-partitioned approach, the mentioned energy savings come at the cost of increased memory requirements and latency of applications.Keywords Energy efficient multiprocessor scheduling · Energy-efficient design · Real-time multiprocessor scheduling · Model-based design · Embedded streaming systems

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Section: Scope Of Workmentioning

confidence: 99%

Section: Derivation Of Minimum Periods Of Tasksmentioning

confidence: 99%

Section: Earliest Start Times and Buffer Size Calculationmentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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Energy efficient semi-partitioned scheduling for embedded multiprocessor streaming systems

Cannella

Stefanov

2016

Des Autom Embed Syst

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Cluster formation techniques for hierarchical real time tasks allocation on multiprocessor system

Talmale

Shrawankar

2021

Concurrency and Computation

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Summary Real‐time systems are nowadays extensively used in most time‐critical embedded applications. The existing multiprocessor real‐time scheduling algorithms are based on partitioned and global scheduling approaches. The partitioned‐based algorithms suffer poor utilization bound, load balancing, not compatible for an open system environment, and the global scheduling approach faces problems like high scheduling, migration overhead. Cluster scheduling represents a hybrid scheduling approach which consists of a set of processors as clusters and tasks scheduled to each processor of clusters using a global scheduling approach. The different cluster formation heuristics are investigated for homogenous clusters. The main objective of this article is to propose task utilization‐based cluster formation and harmonic period aware task allocation for a hierarchical real‐time system on a multiprocessor platform. Tasks with high utilization, cluster size tune to a smaller value to achieve high utilization. Tasks with low utilization, the size of cluster tune to larger to reduce migration and scheduling overheads. Experimentation performed on multiprocessor real‐time simulator with a different set of tasks, multiprocessor system, different tasks utilization, and cluster size. Simulation results show that cluster base approach increases the number of tasks scheduled on a multiprocessor system, system utilization, and reduces response time, migration, and preemption overheads.

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Earliest-deadline first scheduling of multiple independent dataflow graphs

Bouakaz¹,

Gautier²,

Talpin³

2014

2014 IEEE Workshop on Signal Processing Systems (SiPS)

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Abstract-Static dataflow graphs are widely used in design of concurrent real-time streaming applications on multiprocessor systems-on-chip. The increasing complexity of these systems advocates using real-time operating systems and dynamic scheduling to manage applications and resources. Providing timing guarantees (e.g. minimum throughput, deadlines) and minimizing the required amount of resources (e.g. number of processors, buffer capacities) are crucial aspects of these systems. This paper addresses uniprocessor and partitioned multiprocessor earliest-deadline first scheduling of multiple concurrent applications, each designed as an independent dataflow graph. Our scheduling approach maps each actor to a periodic realtime task and computes the appropriate buffer sizes and timing and scheduling parameters (i.e. periods, processor allocation, etc.). The proposed parametric schedulability analysis aims at maximizing the overall processor utilization, and hence allows for reducing the required number of processors.

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System-level scheduling of real-time streaming applications using a semi-partitioned approach

Cited by 4 publications

References 0 publications

Energy efficient semi-partitioned scheduling for embedded multiprocessor streaming systems

Energy efficient semi-partitioned scheduling for embedded multiprocessor streaming systems

Cluster formation techniques for hierarchical real time tasks allocation on multiprocessor system

Earliest-deadline first scheduling of multiple independent dataflow graphs

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