The computing engines of many current applications are powered by MPSoC platforms, which promise significant speedup but induce increased reliability problems as a result of ever growing integration density and chip size. While static MPSoC execution schedules deliver predictable worst-case performance, the absence of dynamic variability unfortunately constrains their usefulness in such an unreliable execution environment.  Adaptive static schedules  with predictable responses to runtime resource variations have consequently been proposed, yet the extra constraints imposed by adaptivity on task assignment have resulted in schedule length increases. We propose to eradicate the associated performance degradation of such techniques while retaining all the concomitant benefits, by exploiting an inherent degree of freedom in task assignment regarding the logical to physical core mapping. The proposed technique relies on the use of core  reordering  and  rotation  through utilizing a graph representation model, which enables a direction translation of inter-core communication paths into order requirements between cores. The algorithmic implementation results confirm that the proposed technique can drastically reduce the schedule length overhead of both  pre - and  post - reconfiguration schedules.
['Chengmo Yang', 'Alex Orailoglu']
Towards no-cost adaptive MPSoC static schedules through exploitation of logical-to-physical core mapping latitude