Browsing by Author "Casini, Daniel"
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- A Holistic Memory Contention Analysis for Parallel Real-Time Tasks under Partitioned SchedulingPublication . Casini, Daniel; Biondi, Alessandro; Nelissen, Geoffrey; Buttazzo, GiorgioWhen adopting multi-core systems for safety-critical applications, certification requirements mandate bounding the delays incurred in accessing shared resources. This is the case of global memories, whose access is often regulated by memory controllers optimized for average-case performance and not designed to be predictable. As a consequence, worst-case bounds on memory access delays often result to be too pessimistic, drastically reducing the advantage of having multiple cores. This paper proposes a fine-grained analysis of the memory contention experienced by parallel tasks running on a multi-core platform. To this end, an optimization problem is formulated to bound the memory interference by leveraging a three-phase execution model and holistically considering multiple memory transactions issued during each phase. Experimental results show the advantage in adopting the proposed approach on both synthetic task sets and benchmarks.
- Memory Feasibility Analysis of Parallel Tasks Running on Scratchpad-Based ArchitecturesPublication . Casini, Daniel; Biondi, Alessandro; Nelissen, Geoffrey; Buttazzo, GiorgioThis work proposes solutions for bounding the worst-case memory space requirement for parallel tasks running on multicore platforms with scratchpad memories. It introduces a feasibility test that verifies whether memories are large enough to contain the maximum memory backlog that may be generated by the system. Both closed-form bounds and more accurate algorithmic techniques are proposed. It is shown how one can use max-plus algebra and solutions to the max-flow cut problem to efficiently solve the memory feasibility problem. Experimental results are presented to evaluate the efficiency of the proposed feasibility analysis techniques on synthetic workload and state-of-the-art benchmarks.
- Partitioned Fixed-Priority Scheduling of Parallel Tasks Without PreemptionsPublication . Casini, Daniel; Biondi, Alessandro; Nelissen, Geoffrey; Buttazzo, GiorgioThe study of parallel task models executed with predictable scheduling approaches is a fundamental problem for real-time multiprocessor systems. Nevertheless, to date, limited efforts have been spent in analyzing the combination of partitioned scheduling and non-preemptive execution, which is arguably one of the most predictable schemes that can be envisaged to handle parallel tasks. This paper fills this gap by proposing an analysis for sporadic DAG tasks under partitioned fixed-priority scheduling where the computations corresponding to the nodes of the DAG are non-preemptively executed. The analysis has been achieved by means of segmented self-suspending tasks with nonpreemptable segments, for which a new fine-grained analysis is also proposed. The latter is shown to analytically dominate state-of-the-art approaches. A partitioning algorithm for DAG tasks is finally proposed. By means of experimental results, the proposed analysis has been compared against a previouslyproposed analysis for DAG tasks with non-preemptable nodes managed by global fixed-priority scheduling. The comparison revealed important improvements in terms of schedulability performance.