Abstract
Commercial-of-the-shelf based multi-core systems present timing anomalies that cannot be ignored by the real-time systems community due to their unpredictable behaviour. These timing anomalies, often caused by applications' uncontrolled accesses to shared resources such as the components in the memory hierarchy or in the 1/0 subsystem, introduce interference that may lead to deadline misses if the problem is neglected. The Acquisition Execution Restitution (AER) execution model was previously proposed to circumvent this problem and, therefore, mitigate inter-task interference. In this model, applications decouple communication (acquisition and restitution phases) from the actual execution in a way that at most one acquisition or restitution phase is in execution at any instant of time while the execution phase of different tasks can progress in parallel on multiple cores. Thus, keeping each task's derived worst-case execution time closer to the one measured in isolation. In this paper, we study the AER execution model and compare it against a global Earliest Deadline First (EDF) approach where interferences are considered. Our results show that a priority assignment heuristic which assigns the priorities based on the tasks' periods dominates all the other proposed heuristics and that due to interference it can also schedule task sets which are not schedulable by using the global EDF approach.

Abstract
Several schedulability analyses have been proposed for a variety of parallel task systems with real-time constraints. However, these analyses are mostly restricted to global scheduling policies. The problem with global scheduling is that it adds uncertainty to the lower-level timing analysis which on multicore systems are heavily context-dependent. As parallel tasks typically exhibit intense communication and concurrency among their sequential computational units, this problem is further exacerbated. This paper considers instead the schedulability of partitioned parallel tasks. More precisely, we present a response time analysis for sporadic DAG tasks atop multiprocessors under partitioned fixed-priority scheduling. We assume the partitioning to be given. We show that a partitioned DAG task can be modeled as a set of self-suspending tasks. We then propose an algorithm to traverse a DAG and characterize such worst-case scheduling scenario. With minor modifications, any state-of-the-art technique for sporadic self-suspending tasks can thus be used to derived the worstcase response time of a partitioned DAG task. Experiments show that the proposed approach significantly tightens the worst-case response time of partitioned parallel tasks comparatively to the state-of-the-art when the most accurate technique is chosen.

Abstract
Flit-level preemptions via virtual channels have been proposed as one viable method to implement priority-preemptive arbitration policies in NoC routers, and integrate NoCs in the hard real-time domain. In recent years, researchers have explored several aspects of priority-preemptive NoCs, such as different arbitration techniques, different priority assignment methods (where applicable) and different workload mapping approaches, all with the common objective to use interconnect mediums more efficiently. Yet, the impact of different routing techniques on such a model is still an unexplored topic. Motivated by this reality, in this work we study the effects of routing flexibility on wormhole-switched priority-preemptive NoCs.

Abstract

Abstract
Several schedulability analyses have been proposed for a variety of parallel task systems with real-Time constraints. However, these analyses are mostly restricted to global scheduling policies. The problem with global scheduling is that it adds uncertainty to the lower-level timing analysis which on multicore systems are heavily context-dependent. As parallel tasks typically exhibit intense communication and concurrency among their sequential computational units, this problem is further exacerbated. This paper considers instead the schedulability of partitioned parallel tasks. More precisely, we present a response time analysis for sporadic DAG tasks atop multiprocessors under partitioned fixed-priority scheduling. We assume the partitioning to be given. We show that a partitioned DAG task can be modeled as a set of self-suspending tasks. We then propose an algorithm to traverse a DAG and characterize such worst-case scheduling scenario. With minor modifications, any state-of-The-Art technique for sporadic self-suspending tasks can thus be used to derived the worst-case response time of a partitioned DAG task. Experiments show that the proposed approach significantly tightens the worst-case response time of partitioned parallel tasks comparatively to the state-of-The-Art when the most accurate technique is chosen. © 2016 IEEE.

Abstract