WCET-aware Software Based Cache Partitioning for Multi-Task Real-Time Systems

Authors Sascha Plazar, Paul Lokuciejewski, Peter Marwedel

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Sascha Plazar
Paul Lokuciejewski
Peter Marwedel

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Sascha Plazar, Paul Lokuciejewski, and Peter Marwedel. WCET-aware Software Based Cache Partitioning for Multi-Task Real-Time Systems. In 9th International Workshop on Worst-Case Execution Time Analysis (WCET'09). Open Access Series in Informatics (OASIcs), Volume 10, pp. 1-11, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2009)


Caches are a source of unpredictability since it is very difficult to predict if a memory access results in a cache hit or miss. In systems running multiple tasks steered by a preempting scheduler, it is even impossible to determine the cache behavior since interrupt-driven schedulers lead to unknown points of time for context switches. Partitioned caches are already used in multi-task environments to increase the cache hit ratio by avoiding mutual eviction of tasks from the cache. For real-time systems, the upper bound of the execution time is one of the most important metrics, called the Worst-Case Execution Time (WCET). In this paper, we use partitioning of instruction caches as a technique to achieve tighter WCET estimations since tasks can not be evicted from their partition by other tasks. We propose a novel WCET-aware cache partitioning algorithm, which determines the optimal partition size for each task with focus on decreasing the system's WCET for a given set of possible partition sizes. Employing this algorithm, we are able to decrease the WCET depending on the number of tasks in a set by up to 34%. On average, reductions between 12% and 19% can be achieved.
  • WCET analysis
  • cache partitioning


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