Modern embedded systems are evolving toward complex, heterogeneous architectures to accommodate increasingly demanding applications. Driven by SWAP-C constraints, this shift has led to consolidating multiple systems onto single hardware platforms. Static Partitioning Hypervisors offer a promising solution to partition hardware resources and provide spatial isolation between critical workloads. However, shared resources like the Last-Level Cache and system bus can introduce temporal interference between virtual machines (VMs), negatively impacting performance and predictability. Over the past decade, academia and industry have developed interference mitigation techniques, such as cache partitioning and memory bandwidth reservation. However, configuring these techniques is complex and time-consuming. Cache partitioning requires balancing cache sections across VMs, while memory bandwidth reservation needs tuning bandwidth budgets and periods. Testing all configurations is impractical and often leads to suboptimal results. Moreover, understanding how these techniques interact is limited, as their combined use can produce compounded or conflicting effects on performance. Static analysis tools estimating worst-case execution times offer guidance for configuring mitigation techniques but often fail to capture the complexity of modern multi-core systems. They typically focus on limited shared resources while neglecting others, such as IOMMUs and interrupt controllers. To address these challenges, we present SP-IMPact, an open-source framework for analyzing and guiding interference mitigation configurations. SP-IMPact supports (i) cache coloring and (ii) memory bandwidth reservation, while evaluating their interactions and cumulative impact. By providing insights on real hardware, SP-IMPact helps optimize configurations for mixed-criticality systems, ensuring performance and predictability.

翻译：现代嵌入式系统正朝着复杂、异构的架构演进，以适应日益严苛的应用需求。在尺寸、重量、功耗与成本（SWAP-C）约束的驱动下，这一趋势促使多个系统被整合到单一硬件平台上。静态分区虚拟机监控器为划分硬件资源并在关键工作负载间提供空间隔离提供了一种前景广阔的解决方案。然而，末级缓存和系统总线等共享资源可能引发虚拟机之间的时序干扰，从而对性能和可预测性产生负面影响。过去十年间，学术界与工业界已开发出多种干扰缓解技术，例如缓存分区和内存带宽预留。然而，配置这些技术既复杂又耗时。缓存分区需要在各虚拟机间平衡缓存区段，而内存带宽预留则需调整带宽预算与周期。测试所有配置方案既不切实际，也常导致次优结果。此外，对这些技术如何相互作用的理解仍有限，因为它们的组合使用可能对性能产生叠加或冲突效应。用于估算最坏情况执行时间的静态分析工具虽能为配置缓解技术提供指导，但往往难以捕捉现代多核系统的复杂性。这些工具通常仅关注有限的共享资源，而忽略了其他组件，如IOMMU和中断控制器。为应对这些挑战，我们提出了SP-IMPact——一个用于分析和指导干扰缓解配置的开源框架。SP-IMPact支持（i）缓存着色与（ii）内存带宽预留，同时评估二者的相互作用与累积影响。通过在真实硬件上提供深入洞察，SP-IMPact有助于优化混合关键性系统的配置，从而确保性能与可预测性。