Static task partitioning for locked caches in multi-core real-time systems

  • Authors:

  • Abhik Sarkar;Frank Mueller;Harini Ramaprasad

  • Affiliations:

  • NCSU, Raleigh, NC, USA;NCSU, Raleigh, NC, USA;Southern Illinois University, Carbondale, IL, USA

  • Venue:
  • Proceedings of the 2012 international conference on Compilers, architectures and synthesis for embedded systems
  • Year:
  • 2012

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Abstract

Locking cache lines in hard real-time systems is a common means to ensure timing predictability of data references and to lower bounds on worst-case execution time, especially in a multi-tasking environment. Growing processing demand on multi-tasking real-time systems can be met by employing scalable multi-core architectures, like the recently introduced tile-based architectures. This paper studies the use of cache locking on massive multi-core architectures with private caches in the context of hard real-time systems. In shared cache architectures, a single resource is shared among {\em all} the tasks. However, in scalable cache architectures with private caches, conflicts exist only among the tasks scheduled on one core. This calls for a cache-aware allocation of tasks onto cores. Our work extends the cache-unaware First Fit Decreasing (FFD) algorithm with a Naive locked First Fit Decreasing (NFFD) policy. We further propose two cache-aware static scheduling schemes: (1) Greedy First Fit Decreasing (GFFD) and (2) Colored First Fit Decreasing (CoFFD). This work contributes an adaptation of these algorithms for conflict resolution of partially locked regions. Experiments indicate that NFFD is capable of scheduling high utilization task sets that FFD cannot schedule. Experiments also show that CoFFD consistently outperforms GFFD resulting in lower number of cores and lower system utilization. CoFFD reduces the number of core requirements from 30% to 60% compared to NFFD. With partial locking, the number of cores in some cases is reduced by almost 50% with an increase in system utilization of 10%. Overall, this work is unique in considering the challenges of future multi-core architectures for real-time systems and provides key insights into task partitioning with locked caches for architectures with private caches.