Run-time resource management in fault-tolerant network on reconfigurable chips

Hosseinabady, Mohammad; Nunez-Yanez, Jose

doi:10.1109/fpl.2009.5272400

Cited by 4 publications

(3 citation statements)

References 7 publications

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“…In [12], a decentralized heuristic is presented that combines a spring layout approach with Tabu search. A combined distributed and fault-tolerant approach is presented in [13], by integrating the task mapping algorithm into the routing protocol.…”

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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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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“…6, the experiments is repeated for NoCs of different sizes (here N=M=NoC Width). To keep the resource occupation similar the number of application is also raised (7,8,9,10,11). It is obvious that the BN Algorithm with global search scales worse as can be seen from the huge amount of monitoringM essages while both produce similar avgnet.…”

Section: Scalabilitymentioning

confidence: 99%

“…Hosseinabady and Nunez-Yanez [11] propose a decentralized stochastic and fault-tolerant mapping and routing algorithm. Their methodology incrementally maps the tasks and, concurrently, routes their communication by applying a random walk.…”

Section: Related Workmentioning

confidence: 99%

Dynamic decentralized mapping of tree-structured applications on NoC architectures

Weichslgartner

Wildermann

Teich

2011

Proceedings of the Fifth ACM/IEEE International Symposium on Networks-on-Chip

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This paper presents a novel application-driven and resourceaware mapping methodology for tree-structured streaming applications onto NoCs. This includes strategies for mapping the source of streaming applications (seed point selection), as well as embedding strategies so that each process autonomously embeds its own succeeding tasks. The proposed embedding strategies only consider the local view of neighboring cells on the NoC which allows to significantly reduce computation and monitoring overhead. Our vision is that this approach facilitates self-organizing embedded systems that provide the flexibility and fault-tolerance required in future silicon technologies. The results provided in this paper show that our local and decentralized algorithms can compete with previously presented global and centralized algorithms.

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