A major shift from compute-centric to data-centric computing systems can be perceived, as novel big data workloads like cognitive computing and machine learning strongly enforce embarrassingly parallel and highly efficient processor architectures. With Moore's law having surrendered, innovative architectural concepts as well as technologies are urgently required, to enable a path for tackling exascale and beyond -- even though current computing systems face the inevitable instruction-level parallelism, power, memory, and bandwidth walls.
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Siegl et al. (2016) studied this question.
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