Run-time spatial mapping of streaming applications to a heterogeneous multi-processor system-on-chip (MPSoC)

Hölzenspies, P.K.F.; Hurink, Johann L.; Kuper, Jan; Smit, Gerard J. M.

doi:10.1145/1403375.1403427

Cited by 52 publications

(34 citation statements)

References 8 publications

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“…), energy (e. g. Chou et al (2008); Hölzenspies et al (2008)), or average speedup (e. g. Kobbe et al (2011)). In Hölzenspies et al (2008), an iterative online application mapping methodology for heterogeneous NoC architectures is proposed. After an initial greedy task to resource assignment, the mapping is optimized and afterwards it is checked if all quality-of-service (QoS) are met.…”

Section: Related Workmentioning

confidence: 99%

A Design-Time/Run-Time Application Mapping Methodology for Predictable Execution Time in MPSoCs

Weichslgartner

Wildermann

Gangadharan

et al. 2018

ACM Trans. Embed. Comput. Syst.

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Executing multiple applications on a single MPSoC brings the major challenge of satisfying multiple quality requirements regarding real-time, energy, etc. Hybrid application mapping denotes the combination of design-time analysis with run-time application mapping. In this article, we present such a methodology, which comprises a design space exploration coupled with a formal performance analysis. This results in several resource reservation configurations, optimized for multiple objectives, with verified real-time guarantees for each individual application. The Pareto-optimal configurations are handed over to run-time management which searches for a suitable mapping according to this information. To provide any real-time guarantees, the performance analysis needs to be composable and the influence of the applications on each other has to be bounded. We achieve this either by spatial or a novel temporal isolation for tasks and by exploiting composable NoCs. With the proposed temporal isolation, tasks of different applications can be mapped to the same resource while with spatial isolation, one computing resource can be exclusively used by only one application. The experiments reveal that the success rate in finding feasible application mappings can be increased by the proposed temporal isolation by up to 30% and energy consumption can be reduced compared to spatial isolation.

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Section: Related Workmentioning

confidence: 99%

A Design-Time/Run-Time Application Mapping Methodology for Predictable Execution Time in MPSoCs

Weichslgartner

Wildermann

Gangadharan

et al. 2018

ACM Trans. Embed. Comput. Syst.

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“…For this reason, we use the Kahn Process Network (KPN) model of computation [Kahn 1974] to specify application behavior because this model of computation fits well to the streaming behavior of multimedia applications. In a KPN, an application is described as a network of concurrent processes that are interconnected via FIFO channels.…”

Section: Application Modelmentioning

confidence: 99%

“…An agent-based distributed application mapping approach for large MPSoCs is presented in Al Faruque et al [2008]. Hölzenspies et al [2008] propose a runtime spatial mapping technique to map streaming applications onto MPSoCs. Brião et al [2008] present dynamic task allocation strategies based on bin-packing algorithms for soft real-time applications.…”

Section: Related Researchmentioning

confidence: 99%

A Hybrid Task Mapping Algorithm for Heterogeneous MPSoCs

Quan

Pimentel

2015

ACM Trans. Embed. Comput. Syst.

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The application workloads in modern MPSoC-based embedded systems are becoming increasingly dynamic. Different applications concurrently execute and contend for resources in such systems, which could cause serious changes in the intensity and nature of the workload demands over time. To cope with the dynamism of application workloads at runtime and improve the efficiency of the underlying system architecture, this article presents a hybrid task mapping algorithm that combines a static mapping exploration and a dynamic mapping optimization to achieve an overall improvement of system efficiency. We evaluate our algorithm using a heterogeneous MPSoC system with three real applications. Experimental results reveal the effectiveness of our proposed algorithm by comparing derived solutions to the ones obtained from several other runtime mapping algorithms. In test cases with three simultaneously active applications, the mapping solutions derived by our approach have average performance improvements ranging from 45.9% to 105.9% and average energy savings ranging from 14.6% to 23.5%.

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“…General architectures use regular addressing, allowing routes to be constructed on demand. In our real time digital signal processing context, the situation is different: communication partners rarely change, and we wish to control channel utilization [14]. Rather than depending on addressed routing, often small (semi-)static source routing tables are used.…”

Section: Related Workmentioning

confidence: 99%

“…Rather than depending on addressed routing, often small (semi-)static source routing tables are used. Routes are computed and adapted at design-time [15], [16] or at run-time [14], [17], [18]. The latter approach is followed in our platform.…”

Section: Related Workmentioning

confidence: 99%

Adaptive resource allocation for streaming applications

Braak

Toersche

Kokkeler

et al. 2011

2011 International Conference on Embedded Computer Systems: Architectures, Modeling and Simulation

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Streaming applications often have latency and throughput requirements due to timing critical signal processing, or the time critical interaction with their environment. Mapping such applications to a multi-core architecture is commonly done at design-time to be able to analyze the complex design-space. However, such design-flows cannot deal with a dynamic platform or a dynamic set of applications. Hardware faults and resources claimed by other applications may render the assumed available resources inaccessible. To avoid the assumptions posed on the state of the platform by a fixed resource allocation, applications should be designed with location transparency in mind. Applications must be analyzed at design-time to determine the required resource budget, independent of which specific resources will be allocated. Sufficient performance can be guaranteed when such applications are mapped onto an architecture in which each resource is arbitrated using a budget scheduler.Within the Cutting edge Reconfigurable ICs for Stream Processing (CRISP) project, a many-core platform is developed that adheres to these requirements. Using the configuration features of the platform, the system is able to control at run-time what resources are being used by the applications. This paper shows that run-time resource allocation can effectively adapt to the available set of resources, providing partial distribution transparency to the user. As an example, a GNSS receiver is mapped to the platform containing faulty hardware components. A few resources remain critical, but in most cases the faulty components can be circumvented, such that adequate resources can be allocated to the application at run-time.

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Run-time spatial mapping of streaming applications to a heterogeneous multi-processor system-on-chip (MPSoC)

Cited by 52 publications

References 8 publications

A Design-Time/Run-Time Application Mapping Methodology for Predictable Execution Time in MPSoCs

A Design-Time/Run-Time Application Mapping Methodology for Predictable Execution Time in MPSoCs

A Hybrid Task Mapping Algorithm for Heterogeneous MPSoCs

Adaptive resource allocation for streaming applications

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