Energy-Efficient Scheduling of Real-Time Tasks in Reconfigurable Homogeneous Multicore Platforms

Gammoudi, Aymen; Benzina, Adel; Khalgui, Mohamed; Chillet, Daniel

doi:10.1109/tsmc.2018.2865965

Cited by 15 publications

(15 citation statements)

References 30 publications

(72 reference statements)

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“…Task success ratio (TSR) and reliability Cost ( cost ) are the principal metrics based on which the evaluation has been performed. The cost is defined in (14). TSR can be defined as the percentage of the total number of tasks accepted by the system over the entire schedule length out of the total number of appeared tasks.…”

Section: Methodsmentioning

confidence: 99%

“…Variation in Platforms: Scheduling a set of real-time tasks in a multicore processor is an NP-hard problem and thus, various heuristic solutions have been employed to overcome this complication [14], [15]. In order to introduce fault-tolerant mechanisms within the scheduling strategy, hardware and time redundancy remain the most popular techniques in timeconstrained systems [16], [17].…”

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

RASA: Reliability-Aware Scheduling Approach for FPGA-Based Resilient Embedded Systems in Extreme Environments

Saha

Zhai

Ehsan

et al. 2022

IEEE Trans. Syst. Man Cybern, Syst.

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Field-programmable gate arrays (FPGAs) offer the flexibility of general-purpose processors along with the performance efficiency of dedicated hardware that essentially renders it as a platform of choice for modern-day robotic systems for achieving real-time performance. Such robotic systems when deployed in harsh environments often get plagued by faults due to extreme conditions. Consequently, the real-time applications running on FPGA become susceptible to errors which call for a reliability-aware task scheduling approach, the focus of this article. We attempt to address this challenge using a hybrid offline-online approach. Given a set of periodic real-time tasks that require to be executed, the offline component generates a feasible preemptive schedule with specific preemption points. At runtime, these preemption events are utilized for fault detection. Upon detecting any faulty execution at such distinct points, the reliability-aware scheduling approach, RASA, orchestrates the recovery mechanism to remediate the scenario without jeopardizing the predefined schedule. Effectiveness of the proposed strategy has been verified through simulation-based experiments and we observed that the RASA is able to achieve 72% of task acceptance rate even under 70% of system workloads with high fault occurrence rates.

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Section: Methodsmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

RASA: Reliability-Aware Scheduling Approach for FPGA-Based Resilient Embedded Systems in Extreme Environments

Saha

Zhai

Ehsan

et al. 2022

IEEE Trans. Syst. Man Cybern, Syst.

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show abstract

“…Tariq et al [38] developed a meta-heuristic for energy-efficient and contention-aware dependent tasks with precedence constraints on VFI-NoC-HMPSoC. Gammoudi et al [39] scheduled periodic tasks on homogeneous NoC-VFI-MPSoC architectures deploying well known EDF task ordering policy. Though these investigations reduced the energy consumption by utilizing appropriate task mapping and scheduling, they did not consider re-timing at the task level to further minimize the total energy consumption.…”

Section: Literature Reviewmentioning

confidence: 99%

Energy-Aware Scheduling of Streaming Applications on Edge-Devices in IoT-Based Healthcare

Tariq

Ali

Liu

et al. 2021

IEEE Trans. on Green Commun. Netw.

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The reliance on Network-on-Chip (NoC) based Multiprocessor Systems-on-Chips (MPSoCs) is proliferating in modern embedded systems to satisfy the higher performance requirement of multimedia streaming applications. Task level coarse grained software pipeling also called re-timing when combined with Dynamic Voltage and Frequency Scaling (DVFS) has shown to be an effective approach in significantly reducing energy consumption of the multiprocessor systems at the expense of additional delay. In this paper we develop a novel energy-aware scheduler considering tasks with conditional constraints on Voltage Frequency Island (VFI) based heterogeneous NoC-MPSoCs deploying re-timing integrated with DVFS for real-time streaming applications. We propose a novel task level re-timing approach called R-CTG and integrate it with non linear programming based scheduling and voltage scaling approach referred to as ALI-EBAD. The R-CTG approach aims to minimize the latency caused by re-timing without compromising on energy-efficiency. Compared to R-DAG, the state-of-the-art approach designed for traditional Directed Acyclic Graph (DAG) based task graphs, R-CTG significantly reduces the re-timing latency because it only re-times tasks that free up the wasted slack. To validate our claims we performed experiments on using 12 real benchmarks, the results demonstrate that ALI-EBAD out performs CA-TMES-Search and CA-TMES-Quick task schedulers in terms of energyefficiency.

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“…The VILCF reduces the energy consumption by fully utilizing an island that is already active before activating other islands. Gammoudi et al (2018) scheduled periodic tasks on homogeneous NoC-VFI-MPSoC architectures deploying well-known EDF task ordering policy. Tariq et al (2019) developed a meta-heuristic for energy-efficient and contention-aware dependent tasks with precedence constraints.…”

Section: Literature Review and Contributionsmentioning

confidence: 99%

Energy-efficient scheduling of streaming applications in VFI-NoC-HMPSoC based edge devices

Tariq

Ali

Liu

et al. 2020

J Ambient Intell Human Comput

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Energy-aware high-performance computing is becoming a challenging facet for streaming applications at edge devices in Internet-of-Things (IoT) due to the high computational complexity involved. Therefore, the number of processors has increased significantly on the multiprocessor system subsequently, Voltage Frequency Island (VFI) recently adopted for an effective energy management mechanism in the large scale multiprocessor chip designs. In this paper, energy-aware scheduling of real-time streaming applications on edge-devices is investigated. First, an innovative re-timing based technique is developed to transform the dependent workload into an independent task model to avail resources and the wasted slack in the processors with a possible minimal prologue. Moreover, unlike the existing population-based optimization algorithms, a novel population-based algorithm, ARSH-FATI is proposed that can dynamically switch between explorative and exploitative search modes at run-time for performance trade-off. Finally, a communication contention-aware Earliest Edge Consistent Deadline First (EECDF) scheduling algorithm is presented. Our static scheduler ARHS-FATI collectively performs task mapping and ordering. Consequently, its performance is superior to the existing state-of-the-art approach proposed for homogeneous VFI based MPSoCs.

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Energy-Efficient Scheduling of Real-Time Tasks in Reconfigurable Homogeneous Multicore Platforms

Cited by 15 publications

References 30 publications

RASA: Reliability-Aware Scheduling Approach for FPGA-Based Resilient Embedded Systems in Extreme Environments

RASA: Reliability-Aware Scheduling Approach for FPGA-Based Resilient Embedded Systems in Extreme Environments

Energy-Aware Scheduling of Streaming Applications on Edge-Devices in IoT-Based Healthcare

Energy-efficient scheduling of streaming applications in VFI-NoC-HMPSoC based edge devices

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