The Worst-Case Response Time (WCRT) of multi-tasking applications running on multi-cores is an important metric for real-time embedded systems. The WCRT is determined by the mapping of the tasks to the cores (which determines load balancing) and the Worst-Case Execution Time (WCET) of the tasks. However, the WCET of a task is also influenced by the conflicts in the shared cache from concurrently executing tasks on other cores in a multi-core system. In other words, the mapping of the tasks to the cores indirectly influences the WCET of the tasks, which in turn impacts the WCRT of the entire application. Thus the mapping of the tasks to the cores should simultaneously maximize workload balance and minimize shared cache interference. We propose an integer-linear programming (ILP) formulation to achieve this objective. Experimental evaluation shows that shared cache aware task mapping achieves on an average 25% and 33% WCRT reduction for real-life and synthetic applications, respectively, compared to traditional approach that is agnostic to shared cache conflicts and solely focuses on load balancing.
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