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DAAT‑MCS: A Framework to Deploy, Analyse, and Auto‑Tune Interference Mitigation Techniques in Mixed‑Criticality Systems

Authors Diogo Costa , Sandro Pinto

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LIPIcs.ECRTS.2026.18.pdf
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  • 26 pages

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Subject Classification

ACM Subject Classification
  • Computer systems organization → Real-time systems
Keywords
  • Auto-Tune
  • Cache Coloring
  • Interference
  • Contention
  • Mixed-Criticality Systems
  • Virtualization

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Abstract

The consolidation of workloads with different criticality levels onto shared multi-core platforms is widely adopted to meet stringent SWaP-C constraints, giving rise to mixed-criticality systems. This consolidation is often enabled by static partitioning hypervisors, which provide strong spatial isolation via static assignment of resources such as cores, memory regions, and devices. However, temporal isolation remains challenging because key microarchitectural resources (e.g., the last-level cache and the memory subsystem) are still shared and can induce contention-driven slowdowns and loss of predictability. Cache coloring and related mitigation techniques can reduce this interference, but their configuration is still typically performed offline via manual profiling and trial-and-error, which is time-consuming, error-prone, and highly workload- and platform-dependent. The remaining gap is therefore not the lack of mitigation mechanisms, but the lack of a systematic way to derive a deployable partition for a given workload mix under explicit timing requirements.
This paper presents DAAT-MCS, an end-to-end framework that automates cache-color assignment for static partitioning hypervisors. It consists of two components: (i) the DAAT-MCS profiler, which systematically deploys and measures a bounded set of cache partitions on real hardware to quantify interference effects in mixed-criticality consolidations; and (ii) the DAAT-MCS tuner, which uses these measurements to automatically derive the set of system-wide cache partitions that satisfy user-defined per-core performance-degradation tolerances. Together, these components turn cache-color tuning from ad-hoc trial-and-error into a repeatable, measurement-driven integration step with explicit acceptance criteria. We evaluate DAAT-MCS on an ARMv8-A Xilinx UltraScale+ ZCU104 platform across 264 workload combinations and 7 cache-partitioning configurations (1848 setups, >60 h of automated profiling). For 28 tuner settings on a subset of 154 out of the 1848 consolidations (one memory-intensive benchmark co-scheduled with 22 co-runners across 7 cache partitions), totaling 4,312 tuner runs, DAAT-MCS finds no acceptable cache partition in 84.53% of cases and returns at least one deployable configuration in the remaining 15.47%, reducing the integration search space whenever feasibility exists and avoiding manual trial-and-error. All artifacts, including code, raw traces, and reproduction infrastructure, are publicly available.

Cite As Get BibTex

Diogo Costa and Sandro Pinto. DAAT‑MCS: A Framework to Deploy, Analyse, and Auto‑Tune Interference Mitigation Techniques in Mixed‑Criticality Systems. In 38th European Conference on Real-Time Systems (ECRTS 2026). Leibniz International Proceedings in Informatics (LIPIcs), Volume 375, pp. 18:1-18:26, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026) https://doi.org/10.4230/LIPIcs.ECRTS.2026.18

Author Details

Diogo Costa
  • Centro ALGORITMI / LASI, Universidade do Minho, Braga, Portugal
Sandro Pinto
  • Centro ALGORITMI / LASI, Universidade do Minho, Braga, Portugal

Funding

  • Costa, Diogo: Supported by FCT – Fundação para a Ciência e Tecnologia within the R&D Unit Project Scope UID/00319/2025 - Centro ALGORITMI (ALGORITMI/UM) https://doi.org/10.54499/UID/00319/2025 and the Grant 2022.13378.BD.

Supplementary Materials

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