Abstract
This letter proposes a system architecture for a scalable software-assisted memory (SAM) hierarchy for emerging manycore embedded systems. Our SAM hierarchy overcomes the coherence overhead and inflexibility of purely hardware-managed memory hierarchies in adapting to variable workloads. Our preliminary results show opportunities for energy saving and performance improvement through: 1) a hybrid software-programmable memory (SPM)/cache local memory adaptable to the application’s memory characteristics; 2) SPM-based management of shared data; and 3) virtualizing and sharing the on-chip memory space between concurrently running applications. Primary experimental results show opportunities to reduce the execution time and the memory hierarchy energy consumption by up to 23% and 7%, respectively, depending on the workload.
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