Evaluating cache related preemption delay (CRPD) in preemptive scheduling context of Real-Time Embedded System (RTES) stays an open issue despite of its practical importance. Indeed, various parameters should be taken into account such as memory layout, cache utilization, processor utilization, priority assignment and scheduling algorithm. In state-of-the-art work, dependencies amongst those parameters are not investigated with precision because of the lack of scheduling analysis tool taking them into account. In this article, we present a tool to investigate and evaluate scheduling analysis of RTES with cache memory and various scheduling parameters. The work consists in modeling guidelines and implementation of a cache-aware scheduling simulator. Implementation is made in Cheddar, an open-source scheduling analyzer, which is freely available to researchers and practitioners. Experiments are conducted in order to illustrate applicability and performance of our tool. Furthermore, we discuss about implementation issues, problems raised and lessons learned from those experiments.
This paper presents a synthesis tool of real-time system scheduling parameters: ADFG computes task periods and bu er sizes of systems as signal processing applications, resulting in a trade-o between throughput maximization and bu er size minimization. ADFG synthesizes systems modeled by ultimately cyclo-static data ow (UCSDF) graphs, an extension of the standard CSDF model. Two new synthesis algorithms are also introduced and evaluated.
Novel memory architectures have been introduced in multi/many-core processors to address the performance bottle neck due to shared memory accesses. Taking the advantages brought by these architectures in scheduling analysis is still an open challenge. In this article, we present a scheduling analysis technique that exploits a shared multi-bank memory architecture to efficiently schedule parallel real-time applications modeled as synchronous data flow (SDF) graphs by minimizing the memory access contentions. Our approach aims at producing a static timetriggered schedule with the objective of minimizing the makespan and buffer size requirements while respecting consistency and data dependency constraints. An Integer Linear Programming formulation of the scheduling problem is presented, as well as a heuristic with significantly lower time complexity. Experimental results are given using synthetic SDF graphs generated by the SDF3 tool and applications available in the StreamIt benchmark.
The use of hardware caches became essential in modern embedded systems to address the speed gap between processor and memory. In such systems, cacherelated preemption delay (CRPD) may represent a significant proportion of task execution time. Addressing this delay in scheduling simulation of these systems stays an open and under-examined problem. Assumptions are often made to simplify the computation model used in simulation and capture the worst-case effect. Nevertheless, they can introduce situations in which scheduling simulation is considered not only pessimistic but also non-sustainable. In this article, we discuss the problem and propose a less pessimistic CRPD computation model that allows sustainable scheduling simulation regarding the capacity parameter. With the proposed model, a system that is schedulable with simulated worstcase execution times remains so when these parameters are reduced. These results improve the applicability of scheduling simulation in the early verification stage for systems with caches. Experiments conducted with our CRPD computation model show a 5% to 12% improvement of schedulability task set coverage and a 30% to 50% reduction of preemption cost with regard to existing CRPD computation models. An integration in a scheduling simulator and a performance evaluation are also realized for the proposed model.
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