Reconfigurable accelerators, like CGRAs and dataflow architectures, have come to prominence for addressing data-processing problems. However, they are largely limited to workloads with regular parallelism, precluding their applicability to prevalent task-parallel workloads. Reconfigurable architectures and task parallelism seem to be at odds, as the former requires repetitive and simple program structure, and the latter breaks program structure to create small, individually scheduled program units.
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Dadu et al. (2022) studied this question.
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