Predictable Shared Cache Management for Multi-Core Real-Time Virtualization

Abstract

Real-time virtualization has gained much attention for the consolidation of multiple real-time systems onto a single hardware platform while ensuring timing predictability. However, a shared last-level cache (LLC) on modern multi-core platforms can easily hamper the timing predictability of real-time virtualization due to the resulting temporal interference among consolidated workloads. Since such interference caused by the LLC is highly variable and may have not even existed in legacy systems to be consolidated, it poses a significant challenge for real-time virtualization. In this article, we propose a predictable shared cache management framework for multi-core real-time virtualization. Our framework introduces two hypervisor-level techniques, vLLC and vColoring, that enable the cache allocation of individual tasks running in a virtual machine (VM), which is not achievable by the current state of the art. Our framework also provides a cache management scheme that determines cache allocation to tasks, designs VMs in a cache-aware manner, and minimizes the aggregated utilization of VMs to be consolidated. As a proof of concept, we implemented vLLC and vColoring in the KVM hypervisor running on x86 and ARM multi-core platforms. Experimental results with three different guest OSs (i.e., Linux/RK, vanilla Linux, and MS Windows Embedded) show that our techniques can effectively control the cache allocation of tasks in VMs. Our cache management scheme yields a significant utilization benefit compared to other approaches while satisfying timing constraints.