Duplication‐controlled static energy‐efficient scheduling on multiprocessor computing system

Kaur, Nirmal; Bansal, Sandeep; Bansal, Rakesh Kumar

doi:10.1002/cpe.4124

Cited by 15 publications

(15 citation statements)

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“…al. [36] proposed a duplication based approach combined with dynamic power methods to reduce dynamic as well as static power consumption for dependent tasks. However, their work also does not utilize DVFS.…”

Section: Related Workmentioning

confidence: 99%

“…Each of the processors, when not in use, can be in one the idle states s where s ∈ S[m]. The set S[m] define idle states on a processor m. We consider four different idle states as have been used in [36]. The state S[m, 0] represents active-idle state on a processor m. In an active-idle state, a processor is idle i.e., it is not executing any tasks, however, all of the components of the processor are in active (power-on) state.…”

Section: A Task Processor and Network Modelmentioning

confidence: 99%

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Dynamic and Static Energy Efficient Scheduling of Task Graphs on Multiprocessors: A Heuristic

2020

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For energy efficient scheduling of task graphs on multiprocessors, dynamic voltage and frequency scaling (DVFS) and duplication are two widely used techniques. DVFS is generally used to utilize the execution slack by lowering the voltage and frequency of a task to decrease the dynamic energy consumption. Whereas duplication decreases the schedule length and communication energy consumption by replicating certain dependent tasks to avoid communication delays. However, while making decisions on DVFS and duplication for a task, the static energy consumption is mostly overlooked. With chip technologies reducing to a few nano meters, static energy consumption due to leakage current has become important. This article proposes a novel polynomial time heuristic that uses both DVFS and duplication to optimize static energy consumption along with dynamic and communication energy when scheduling task graphs on heterogeneous multiprocessors. The proposed list scheduling algorithm also balances schedule length with energy consumption using proposed normalized difference parameters while making scheduling decisions for a particular task. The results demonstrate the ability of the proposed algorithm to decrease the overall energy consumption with an improved or comparable schedule length as compared with other algorithms in various scenarios.

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Section: Related Workmentioning

confidence: 99%

Section: A Task Processor and Network Modelmentioning

confidence: 99%

Dynamic and Static Energy Efficient Scheduling of Task Graphs on Multiprocessors: A Heuristic

2020

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“…Judicious task allocation and scheduling, however, assists in achieving the above said objectives to a great extent [4], [5]. Earliest Deadline First (EDF) and Rate Monotonic (RM) are two optimal scheduling algorithms for real-time systems meant for fixed-priority and dynamic-priority tasks respectively [14].…”

Section: Kiran Arora Savina Bansal Rakesh Kumar Bansalmentioning

confidence: 99%

“…Dynamic voltage scaling (DVS) and dynamic power management (DPM) are two eminent and effective schemes at the operating system level that are typically employed for lessening energy consumption [4], [5].…”

Section: Introductionmentioning

confidence: 99%

Fault-Tolerant Energy-Aware Task Scheduling on Multiprocessor System for Fixed-Priority Real-Time Tasks

Arora*,

Bansal,

Bansal

2019

IJITEE

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Energy-aware real-time scheduling is gaining attention in recent years owing to environmental concerns and applications in numerous fields. System reliability also gets affected adversely with increasing energy dissipations posing serious challenges before the researchers. Keeping these in view, in recent times researchers have diverted to combining issues of fault-tolerance and energy efficiency. In literature, DVFS and DPM, most commonly used techniques for power management in task scheduling, are often combined with Primary/Backup technique to achieve fault tolerance against transient and permanent faults. Optimal algorithms, Earliest deadline first (EDF) and Rate-Monotonic (RM), meant for scheduling dynamic and fixed priority tasks respectively, have mainly been analyzed using a dual-processor approach for fault-tolerance and energy efficiency. In this paper, to handle higher workload of fixed-priority real-time tasks, energy-aware fault-tolerant scheduling algorithms are proposed for multiprocessor systems with balanced and unbalanced number of main and auxiliary processors. Simulations over extensive task-sets indicate that balanced approach is more energy-efficient than the unbalanced one.

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“…For bi-objective optimization, a number of studies have considered task duplications for makespan improvements while reducing the energy by scaling down the feasible frequencies. 16,17 In general, recent approaches can be classified into two modes, ie, coscheduling and rescheduling. In the coscheduling mode, [18][19][20][21][22] both time and energy factors are simultaneously considered at each decision episode, usually by a trade-off function, to seek a high quality schedule in a single pass.…”

Section: Of 17mentioning

confidence: 99%

Energy‐efficient task scheduling on heterogeneous computing systems by linear programming

Zhang

Wang

Tang

et al. 2018

Concurrency and Computation

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The continually increasing energy consumption represents a critical issue in modern heterogeneous computing systems. With the aid of dynamic voltage frequency scaling (DVFS), task scheduling is considered an effective software-based technique for reducing the total energy consumption and minimizing the overall schedule length (makespan). A natural solution is to reclaim the slack time in a given time-efficient schedule, which is also referred to as a "two-pass" method or a "rescheduling" method. A number of studies have focused on slack reclamation to achieve energy reductions through heuristics; although, these methods offer suboptimal solutions. In this article, the rescheduling optimization problem is formulated as a linear program for minimizing an energy objective function subject to precedence and deadline constraints implied in the given schedule. Two types of decision variables, ie, frequency duty factors and task intervals, are defined to set up the linear model. Consequently, an optimal solution to the problem can be provided in a straightforward manner by a linear programming solver, which suggests that such a rescheduling problem belongs to the P (polynomial time) class. The experimental results show the effectiveness of the proposed approach and demonstrate that the performance is superior to that of other competitive algorithms in terms of both energy saving and runtime efficiency. KEYWORDS dynamic voltage frequency scaling (DVFS), energy efficiency, heterogeneous computing system, linear programming, slack reclamation, task scheduling 1 INTRODUCTION A heterogeneous computing system (HCS) is a computing platform with diverse sets of heterogeneous computing resources connected by a high-speed network for processing parallel applications. 1 In recent decades, HCSs have been widely used in both scientific and commercial fields, such as supercomputing, cloud computing, and big data. For example, the world's fastest supercomputer "Sunway TaihuLight" has 40,960 computer nodes, each with 4 management processing elements (MPEs) and 256 computing processing elements (CPEs). Although it provides the most powerful computing capability, "Sunway TaihuLight" also consumes a tremendous amount of electrical energy, estimated at approximately 15,371 kW. 2,3At an approximate price of $0.1/kWh, its energy cost is approximately $13.46 million per year, which is far beyond the acceptable cost for many HCS operators. Furthermore, the energy cost of powering a typical data center doubles every five years. 4 In certain cases, the power cost may exceed the hardware purchase costs. 5 Besides, high energy consumption creates a number of environmental problems. 6,7 For example, in 2014, global data centers consumed up to 3% of the world's electricity production while causing 200 million metric tons of carbon emissions, thus accounting for approximately 2% of the world's greenhouse gas emissions. 8 On the other hand, a large portion of servers inside these data centers have relatively low average utilization efficiency. Observa...

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Duplication‐controlled static energy‐efficient scheduling on multiprocessor computing system

Cited by 15 publications

References 30 publications

Dynamic and Static Energy Efficient Scheduling of Task Graphs on Multiprocessors: A Heuristic

Dynamic and Static Energy Efficient Scheduling of Task Graphs on Multiprocessors: A Heuristic

Fault-Tolerant Energy-Aware Task Scheduling on Multiprocessor System for Fixed-Priority Real-Time Tasks

Energy‐efficient task scheduling on heterogeneous computing systems by linear programming

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