Optimal Task Scheduling by Removing Inter-Core Communication Overhead for Streaming Applications on MPSoC

Yi, Wang; Liu, Duo; Wang, Meng; Qin, Zhiwei; Shao, Zili

doi:10.1109/rtas.2010.19

Cited by 30 publications

(13 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In offline solutions, static schedules are generated at design time and rely on worst-case execution time estimates to compute the DVFS and DPM actions used to scale the voltage and frequency and to switch on/off cores, respectively [10], [11], [18], [19]. Synchronous dataflow (SDF) and cyclo-static dataflow (CSDF) are also known to be powerful modeling tools for static compile-time scheduling onto single and multicore processors [27], [28].…”

Section: Related Workmentioning

confidence: 99%

Online Energy-Efficient Task-Graph Scheduling for Multicore Platforms

Kanoun

Mastronarde

Atienza

et al. 2014

IEEE Trans. Comput.-Aided Des. Integr. Circuits Syst.

View full text Add to dashboard Cite

Abstract-Numerous directed acyclic graph (DAG) schedulers have been developed to improve the energy efficiency of various multicore platforms. However, these schedulers make a priori assumptions about the relationship between the task dependencies, and they are unable to adapt online to the characteristics of each application without offline profiling data. Therefore, we propose a novel energy-efficient online scheduling solution for the general DAG model to address the two aforementioned problems. Our proposed scheduler is able to adapt at run-time to the characteristics of each application by making smart foresighted decisions, which take into account the impact of current scheduling decisions on the present and future deadline miss rates and energy efficiency. Moreover, our scheduler is able to efficiently handle execution with very limited resources by avoiding scheduling tasks that are expected to miss their deadlines and do not have an impact on future deadlines. We validate our approach against state-of-the-art solutions. In our first set of experiments, our results with the H.264 video decoder demonstrate that the proposed low-complexity solution for the general DAG model reduces the energy consumption by up to 15% compared to an existing sophisticated and complex scheduler that was specifically built for the H.264 video decoder application. In our second set of experiments, our results with different configurations of synthetic DAGs demonstrate that our proposed solution is able to reduce the energy consumption by up to 55% and the deadline miss rates by up to 99% compared to a second existing scheduling solution. Finally, we show that our DAG flow manager and scheduler have low complexities on a real mobile platform and we show that our solution is resilient to workload prediction errors by using different estimator accuracies.

show abstract

Section: Related Workmentioning

confidence: 99%

Online Energy-Efficient Task-Graph Scheduling for Multicore Platforms

Kanoun

Mastronarde

Atienza

et al. 2014

IEEE Trans. Comput.-Aided Des. Integr. Circuits Syst.

View full text Add to dashboard Cite

show abstract

“…2: frames B and P with deadline d i and d i+1 respectively). The solu- [15,16] independent periodic offline [6,7,8] independent periodic online [13] dependent H.264 online Our solution dependent general online…”

Section: Related Workmentioning

confidence: 99%

A unified online directed acyclic graph flow manager for multicore schedulers

Kanoun

Atienza

Mastronarde³

et al. 2014

2014 19th Asia and South Pacific Design Automation Conference (ASP-DAC)

View full text Add to dashboard Cite

Abstract-Numerous Directed-Acyclic Graph (DAG) schedulers have been developed to improve the energy efficiency of various multi-core systems. However, the DAG monitoring modules proposed by these schedulers make a priori assumptions about the workload and relationship between the task dependencies. Thus, schedulers are limited to work on a limited subset of DAG models. To address this problem, we propose a unified online DAG monitoring solution independent from the connected scheduler and able to handle all possible DAG models. Our novel low-complexity solution processes online the DAG of the application and provides relevant information about each task that can be used by any scheduler connected to it. Using H.264/AVC video decoding as an illustrative application and multiple configurations of complex synthetic DAGs, we demonstrate that our solution connected to an external simple energy-efficient scheduler is able to achieve significant improvements in energy-efficiency and deadline miss rates compared to existing approaches.

show abstract

“…In order to take advantage of multiprocessor architectures, various techniques have been explored to increase the parallelism of application programs, which usually imposes additional interprocessor communications with considerable overheads. To improve the communication performance between processors, a number of approaches have been developed from various perspectives, e.g., [10], [14], [36], [37]. In particular, a cosynthesis approach that determines energy-efficient memory/communication configurations was proposed for high parallelism applications [14].…”

Section: Introductionmentioning

confidence: 99%

“…A communication-aware framework was developed to allocate and schedule tasks on processors with distributed memory architectures [10]. In [37], a joint rescheduling technique was exploited to overlap task executions and interprocessor communications, thereby reducing communication overheads effectively. The technique was further improved to remove communication overheads with the minimum memory usage for resource-constrained embedded systems [36].…”

Section: Introductionmentioning

confidence: 99%

Multilayer Bus Optimization for Real-Time Embedded Systems

Hsiu¹,

Hsieh²,

Lee³

et al. 2012

IEEE Trans. Comput.

View full text Add to dashboard Cite

A major challenge in the design of multicore embedded systems is how to tackle the communications among tasks with performance requirements and precedence constraints. In this paper, we consider the problem of scheduling real-time tasks over multilayer bus systems with the objective of minimizing the communication cost. We show that the problem is N P-hard and determine the best possible approximation ratio of approximation algorithms. First, we propose a polynomial-time optimal algorithm for a restricted case where one multilayer bus, and the unit execution time and communication time are considered. The result is then extended as a pseudopolynomial-time optimal algorithm to consider multiple multilayer buses with arbitrary execution and communication times, as well as different timing constraints and objective functions. We compare the performance of the proposed algorithm with that of some popular heuristics, and provide further insights into the multilayer bus system design.

show abstract

Optimal Task Scheduling by Removing Inter-Core Communication Overhead for Streaming Applications on MPSoC

Cited by 30 publications

References 9 publications

Online Energy-Efficient Task-Graph Scheduling for Multicore Platforms

Online Energy-Efficient Task-Graph Scheduling for Multicore Platforms

A unified online directed acyclic graph flow manager for multicore schedulers

Multilayer Bus Optimization for Real-Time Embedded Systems

Contact Info

Product

Resources

About