A comparison of MPCP and MSRP when sharing resources in the Janus multiple-processor on a chip platform

P Gai, M Di Natale, G Lipari, A Ferrari… - The 9th IEEE Real …, 2003 - ieeexplore.ieee.org
P Gai, M Di Natale, G Lipari, A Ferrari, C Gabellini, P Marceca
The 9th IEEE Real-Time and Embedded Technology and Applications …, 2003ieeexplore.ieee.org
The new generation of embedded systems for automotive applications can take advantage
of low-cost multiprocessor system-on a chip architectures. The real-time software
applications running on these systems require realtime processor scheduling, and also
require the management of the communication and synchronization of tasks executing on
different processors with limited blocking time. Conventional real-time technologies, like the
Rate Monotonic scheduling algorithm together with the Multiprocessor Priority Ceiling …
The new generation of embedded systems for automotive applications can take advantage of low-cost multiprocessor system-on a chip architectures. The real-time software applications running on these systems require realtime processor scheduling, and also require the management of the communication and synchronization of tasks executing on different processors with limited blocking time. Conventional real-time technologies, like the Rate Monotonic scheduling algorithm together with the Multiprocessor Priority Ceiling Protocol (MPCP) can be used to this purpose. In earlier work, we proposed the Multiprocessor Stack Resource Policy (MSRP) for scheduling tasks and sharing resources in multiprocessor on a chip architectures. In this paper we present an experimental evaluation that compares the performance of our algorithm with a solution based on Rate Monotonic and MPCP in the con text of the Janus multiple processor architecture. The evaluation of the algorithm has been triggered by our ongoing research in the automotive domain. We report on two sets of experiments: the first addresses a range of generic task configurations to see if one of the algorithms can clearly outperform the other The results show MSRP to be better for random task periods but are probably not conclusive. Later we focus on a more application-specific (also more restrictive) architecture design representing a typical automotive application: a power-train controller In this case, MSRP clearly performs better The performance gap between the two policies can be further increased when considering that MSRP is much simpler to implement, it has a lower overhead, and it allows RAM memory optimization.
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