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Two-Phase Low-Energy N-Modular Redundancy for Hard Real-Time Multi-Core Systems

Salehi, M ; Sharif University of Technology | 2016

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  1. Type of Document: Article
  2. DOI: 10.1109/TPDS.2015.2444402
  3. Publisher: IEEE Computer Society , 2016
  4. Abstract:
  5. This paper proposes an N-modular redundancy (NMR) technique with low energy-overhead for hard real-time multi-core systems. NMR is well-suited for multi-core platforms as they provide multiple processing units and low-overhead communication for voting. However, it can impose considerable energy overhead and hence its energy overhead must be controlled, which is the primary consideration of this paper. For this purpose the system operation can be divided into two phases: indispensable phase and on-demand phase. In the indispensable phase only half-plus-one copies for each task are executed. When no fault occurs during this phase, the results must be identical and hence the remaining copies are not required. Otherwise, the remaining copies must be executed in the on-demand phase to perform a complete majority voting. In this paper, for such a two-phase NMR, an energy-management technique is developed where two new concepts have been considered: i) Block-partitioned scheduling that enables parallel task execution during on-demand phase, thereby leaving more slack for energy saving, ii) Pseudo-dynamic slack, that results when a task has no faulty execution during the indispensable phase and hence the time which is reserved for its copies in the on-demand phase is reclaimed for energy saving. The energy-management technique has an off-line part that manages static and pseudo-dynamic slacks at design time and an online part that mainly manages dynamic slacks at run-time. Experimental results show that the proposed NMR technique provides up to 29 percent energy saving and is 6 orders of magnitude higher reliable as compared to a recent previous work. © 2015 IEEE
  6. Keywords:
  7. Multi-core systems ; Real-time and embedded systems ; Embedded systems ; Energy conservation ; Energy management ; Industrial management ; Redundancy ; Reliability ; Scheduling ; Energy minimization ; Management techniques ; Multi-core platforms ; Multi-core systems ; Multiple processing ; N-modular redundancies ; Orders of magnitude ; Real-time and embedded systems ; Real time systems
  8. Source: IEEE Transactions on Parallel and Distributed Systems ; Volume 27, Issue 5 , 2016 , Pages 1497-1510 ; 10459219 (ISSN)
  9. URL: http://ieeexplore.ieee.org/document/7122343/?reload=true