Flexible Cache Partitioning for Multi-Mode Real-Time Systems

Kwon, Oh-Chul; Schwaricke, Gero; Kloda, Tomasz; Hoornaert, Denis; Gracioli, Giovani; Caccamo, Marco

doi:10.23919/date51398.2021.9474240

Cited by 5 publications

(3 citation statements)

References 23 publications

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“…Nonetheless, cache partitioning mechanisms are not a perfect solution and can harm the average and guaranteed performance of safetyrelated applications [6] and the flexibility to schedule tasks with diverse and variable performance requirements [13]. However, solutions providing less abrupt mitigation policies [5] require additional means to verify the controllability of such interference [2]. For instance, we may want to check that the number of evictions in the shared cache is below certain thresholds or even zero.…”

Section: B Multicore Contention Due To Shared Cachesmentioning

confidence: 99%

“…Some of these partitioning mechanisms have been surveyed in [12]. However, as highlighted in several works [5], [6], [21] such partitioning schemes can introduce non-negligible performance degradation and limit the flexibility of the underlying computing platform.…”

Section: Related Workmentioning

confidence: 99%

“…However, robust partitioning mechanisms come at the expense of reducing the efficiency and flexibility of cache resources. In this context, alternative approaches facilitating higher-performance cache allocation policies [5], [6] are desirable but challenging to deploy in safety-critical systems since they complicate the certification process [7].…”

Section: Introductionmentioning

confidence: 99%

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Hashing ATD Tags for Low-overhead Safe Contention Monitoring

Andreu,

Lopez,

Hernandez

2024

IEEE Comput. Arch. Lett.

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Increasing the performance of safety-critical systems via introducing multicore processors is becoming the norm. However, when multiple cores access a shared cache, inter-core evictions become a relevant source of interference that must be appropriately controlled. To solve this issue, one can statically partition caches and remove the interference. Unfortunately, this comes at the expense of less flexibility and, in some cases, worse performance. In this context, enabling more flexible cache allocation policies requires additional monitoring support.This paper proposes HashTAG, a novel approach to accurately upperbound inter-core eviction interference. HashTAG enables a low-overhead implementation of an Auxiliary Tag Directory to determine inter-core evictions. Our results show that no inter-task interference underprediction is possible with HashTAG while providing a 44% reduction in ATD area with only 1.14% median overprediction.

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Section: B Multicore Contention Due To Shared Cachesmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Hashing ATD Tags for Low-overhead Safe Contention Monitoring

Andreu,

Lopez,

Hernandez

2024

IEEE Comput. Arch. Lett.

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Minimizing cache usage with fixed-priority and earliest deadline first scheduling

Sun,

Kloda,

Garcia

et al. 2024

Real-Time Syst

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Cache partitioning is a technique to reduce interference among tasks running on the processors with shared caches. To make this technique effective, cache segments should be allocated to tasks that will benefit the most from having their data and instructions stored in the cache. The requests for cached data and instructions can be retrieved faster from the cache memory instead of fetching them from the main memory, thereby reducing overall execution time. The existing partitioning schemes for real-time systems divide the available cache among the tasks to guarantee their schedulability as the sole and primary optimization criterion. However, it is also preferable, particularly in systems with power constraints or mixed criticalities where low- and high-criticality workloads are executing alongside, to reduce the total cache usage for real-time tasks. Cache minimization as part of design space exploration can also help in achieving optimal system performance and resource utilization in embedded systems. In this paper, we develop optimization algorithms for cache partitioning that, besides ensuring schedulability, also minimize cache usage. We consider both preemptive and non-preemptive scheduling policies on single-processor systems with fixed- and dynamic-priority scheduling algorithms (Rate Monotonic (RM) and Earliest Deadline First (EDF), respectively). For preemptive scheduling, we formulate the problem as an integer quadratically constrained program and propose an efficient heuristic achieving near-optimal solutions. For non-preemptive scheduling, we combine linear and binary search techniques with different fixed-priority schedulability tests and Quick Processor-demand Analysis (QPA) for EDF. Our experiments based on synthetic task sets with parameters from real-world embedded applications show that the proposed heuristic: (i) achieves an average optimality gap of 0.79% within 0.1× run time of a mathematical programming solver and (ii) reduces average cache usage by 39.15% compared to existing cache partitioning approaches. Besides, we find that for large task sets with high utilization, non-preemptive scheduling can use less cache than preemptive to guarantee schedulability.

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