Simulating execution time and power consumption of real-time tasks on embedded platforms

Ara, Gabriele; Cucinotta, Tommaso; Mascitti, Agostino

doi:10.1145/3477314.3507030

Cited by 5 publications

(9 citation statements)

References 19 publications

(34 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The placement of the tasks in the {𝑥 𝑖,𝑝 } variables and the choice of the operating frequencies of the islands in the {𝑦 𝑠,𝑚 } ones, affect the average power consumption of the applications deployed on the platform, which the solver attempts to minimize. Precisely, following the power model discussed in [5], based on extensive experimental power consumption data gathered for a set of diverse workloads on various embedded platforms, the objective of the…”

Section: Miqcp Problem Formalizationmentioning

confidence: 99%

See 1 more Smart Citation

Multi-criteria Optimization of Real-time DAGs on Heterogeneous Platforms under P-EDF

Cucinotta

Amory

Ara

et al. 2024

ACM Trans. Embed. Comput. Syst.

Self Cite

View full text Add to dashboard Cite

This paper tackles the problem of optimal placement of complex real-time embedded applications on heterogeneous platforms. Applications are composed of directed acyclic graphs of tasks, with each DAG having a minimum inter-arrival period for its activation requests, and an end-to-end deadline within which all of the computations need to terminate since each activation. The platforms of interest are heterogeneous power-aware multi-core platforms with DVFS capabilities, including big.LITTLE Arm architectures, and platforms with GPU or FPGA hardware accelerators with Dynamic Partial Reconfiguration capabilities. Tasks can be deployed on CPUs using partitioned EDF-based scheduling. Additionally, some of the tasks may have an alternate implementation available for one of the accelerators on the target platform, which are assumed to serve requests in non-preemptive FIFO order. The system can be optimized by: minimizing power consumption, respecting precise timing constraints; maximizing the applications’ slack, respecting given power consumption constraints; or even a combination of these, in a multi-objective formulation. We propose an off-line optimization of the mentioned problem based on mixed-integer quadratic constraint programming (MIQCP). The optimization provides the DVFS configuration of all the CPUs (or accelerators) capable of frequency switching and the placement to be followed by each task in the DAGs, including the software-vs-hardware implementation choice for tasks that can be hardware-accelerated. For relatively big problems, we developed heuristic solvers capable of providing suboptimal solutions in a significantly reduced time compared to the MIQCP strategy, thus widening the applicability of the proposed framework. We validate the approach by running a set of randomly generated DAGs on Linux under SCHED_DEADLINE, deployed onto two real boards, one with Arm big.LITTLE architecture, the other with FPGA acceleration, verifying that the experimental runs meet the theoretical expectations in terms of timing and power optimization goals.

show abstract

Section: Miqcp Problem Formalizationmentioning

confidence: 99%

“…Each application has been run on both big and LITTLE cores, and for all of the available CPU frequencies. The data-set has been gathered using PARTProf, and embedded within the PARTSim open-source real-time systems simulator [5].…”

Section: Dvfs Scaling Modelmentioning

confidence: 99%

Multi-criteria Optimization of Real-time DAGs on Heterogeneous Platforms under P-EDF

Cucinotta

Amory

Ara

et al. 2024

ACM Trans. Embed. Comput. Syst.

Self Cite

View full text Add to dashboard Cite

show abstract

“…A simulation tool (SIMSO) presented in [5] is designed for the understanding of realtime scheduling algorithms and evaluate real-time system performance and overheads. SIMSO used by many studies such as [3], [14], [4] and [7].…”

Section: -6 Background and Related Workmentioning

confidence: 99%

“…This event can be the release of a new task or termination of a specific task or any other event related to the scheduling algorithm type. Figure (3) shows the difference between event driven and non-event driven scheduling in terms of response time.…”

Section: Multiprocessor Schedulingmentioning

confidence: 99%

See 1 more Smart Citation

Development of Energy- Efficient Load Balancing Scheduling Algorithm in Real-time Systems

نتيفه¹,

حجازية²

2022

Journal of Engineering Sciences and Information Technology

View full text Add to dashboard Cite

Real- time systems are considered as one of the most important topics that have attracted the attention of researchers in various scientific and technical fields due to their widespread in many fields of communication, informatics, operating systems and automatic control systems. The basic idea in real- time systems is the execution of a set of tasks that are assigned to CPUs, within a time constraint associated with each of them, and this time constraint is called a deadline. Task scheduling in real- time systems is the main factor in determining the success or failure of the system. Therefore, many studies have imposed suggestions and hypotheses for improving scheduling, according to the underlined platform, whether it is single- processor, multi- processor, or multi- core processor. Researchers have recently focused on studying and providing solutions to scheduling problems, taking into account energy consumption since energy consumption today plays an important role in determining the efficiency and reliability of the system. Energy consumption can be saved either statically by turning the processor into sleep mode or dynamically by changing the frequency of the processor cores and thus reducing power consumption. However, a slight increase in frequency leads to executing more tasks in less time and thus can lead to an increase in the efficiency of the real- time system by reducing tasks which may miss its deadline at the time of execution. In this research, a new method has been proposed to control the processor frequency in an optimal manner that makes a balanced trade- off between power consumption and execution of tasks in real- time systems.

show abstract

Reducing Peak Temperature by Redistributing Idle-Time in Modern MPSoCs

Benedikt

Yomsi

Sójka

2023

2023 IEEE 26th International Symposium on Real-Time Distributed Computing (ISORC)

View full text Add to dashboard Cite

Simulating execution time and power consumption of real-time tasks on embedded platforms

Cited by 5 publications

References 19 publications

Multi-criteria Optimization of Real-time DAGs on Heterogeneous Platforms under P-EDF

Multi-criteria Optimization of Real-time DAGs on Heterogeneous Platforms under P-EDF

Development of Energy- Efficient Load Balancing Scheduling Algorithm in Real-time Systems

Reducing Peak Temperature by Redistributing Idle-Time in Modern MPSoCs

Contact Info

Product

Resources

About