Evaluating Controlled Memory Request Injection to Counter PREM Memory Underutilization

Modern heterogeneous systems-on-chip (HeSoC) feature high-performance multi-core CPUs tightly integrated with data-parallel accelerators. Such HeSoCS heavily rely on shared resources, which hinder their adoption in the context of Real-Time systems. The predictable execution model (PREM) has proven effective at preventing uncontrolled execution time lengthening due to memory interference in HeSoC sharing main memory (DRAM). However, PREM only allows one task at a time to access memory, which inherently under-utilizes the available memory bandwidth in modern HeSoCs. In this paper, we conduct a thorough experimental study aimed at assessing the potential benefits of extending PREM so as to inject controlled amounts of memory requests coming from other tasks than the one currently granted exclusive DRAM access. Focusing on a state-of-the-art HeSoC, the NVIDIA TX2, we extensively characterize the relation between the injected bandwidth and the latency experienced by the task under test. The results confirm that for various types of workload it is possible to exploit the available bandwidth much more efficiently than standard PREM arbitration, often close to its maximum, while keeping latency inflation below 10%. We discuss possible practical implementation directions, highlighting the expected benefits and technical challenges.