In modern heterogeneous MPSoCs, the management of shared memory resources is
crucial in delivering end-to-end QoS. Previous frameworks have either focused
on singular QoS targets or the allocation of partitionable resources among CPU
applications at relatively slow timescales. However, heterogeneous MPSoCs
typically require instant response from the memory system where most resources
cannot be partitioned. Moreover, the health of different cores in a
heterogeneous MPSoC is often measured by diverse performance objectives. In
this work, we propose a Self-Aware Resource Allocation (SARA) framework for
heterogeneous MPSoCs. Priority-based adaptation allows cores to use different
target performance and self-monitor their own intrinsic health. In response,
the system allocates non-partitionable resources based on priorities. The
proposed framework meets a diverse range of QoS demands from heterogeneous
cores.Comment: Accepted by the 55th annual Design Automation Conference 2018
(DAC'18