Predictable execution models have been proposed over the years to achieve contention-free execution of real-time tasks by preloading data into dedicated local memories. In this way, memory access delays can be hidden by delegating a DMA engine to perform memory transfers in parallel with processor execution. Nevertheless, state-of-the-art protocols introduce additional blocking due to priority inversion, which may severely penalize latency-sensitive applications and even worsen the system schedulability with respect to the use of classical scheduling schemes. This paper proposes a new protocol that allows hiding memory transfer delays while reducing priority inversion, thus favoring the schedulability of latency-sensitive tasks. The corresponding analysis is formulated as an optimization problem. Experimental results show the advantages of the proposed protocol against state-of-the-art solutions.
Predictable Memory-CPU Co-Scheduling with Support for Latency-Sensitive Tasks
Casini D.;Pazzaglia P.;Biondi A.;Di Natale M.;Buttazzo G.
2020-01-01
Abstract
Predictable execution models have been proposed over the years to achieve contention-free execution of real-time tasks by preloading data into dedicated local memories. In this way, memory access delays can be hidden by delegating a DMA engine to perform memory transfers in parallel with processor execution. Nevertheless, state-of-the-art protocols introduce additional blocking due to priority inversion, which may severely penalize latency-sensitive applications and even worsen the system schedulability with respect to the use of classical scheduling schemes. This paper proposes a new protocol that allows hiding memory transfer delays while reducing priority inversion, thus favoring the schedulability of latency-sensitive tasks. The corresponding analysis is formulated as an optimization problem. Experimental results show the advantages of the proposed protocol against state-of-the-art solutions.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.