Variability-tolerant workload allocation for MPSoC energy minimization under real-time constraints

Sub-50nm CMOS technologies are affected by significant variability, which causes power and performance variations among nominally similar cores in MPSoC platforms. This undesired heterogeneity threatens execution predictability and energy efficiency. We propose two techniques to allocate sets of barrier-synchronized tasks. The first technique models allocation as an ILP and achieves optimal results, but requires an offline solver. The second technique adopts a two-stage heuristic approach, and it can be adapted to work online. We tested our approach on the virtual prototype of a next-generation industrial multicore platform. Experimental results demonstrate that our approach minimizes deadline violations while increasing energy efficiency.

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