Response-Time Analysis for Non-Preemptive Periodic Moldable Gang Tasks

Gang scheduling has long been adopted by the high-performance computing community as a way to reduce the synchronization overhead between related threads. It allows for several threads to execute in lock steps without suffering from long busy-wait periods or be penalized by large context-switch overheads. When combined with non-preemptive execution, gang scheduling significantly reduces the execution time of threads that work on the same data by decreasing the number of memory transactions required to load or store the data. In this work, we focus on two main types of gang tasks: rigid and moldable. A moldable gang task has a presumed known minimum and maximum number of cores on which it can be executed at runtime, while a rigid gang task always executes on the same number of cores. This work presents the first response-time analysis for non-preemptive moldable gang tasks. Our analysis is based on the notion of schedule abstraction; a new approach for response-time analysis with the promise of high accuracy. Our experiments on periodic rigid gang tasks show that our analysis is 4.9 times more successful in identifying schedulable tasks than the existing utilization-based test for rigid gang tasks.</p

Hard Real-Time Stationary GANG-Scheduling

The scheduling of parallel real-time tasks enables the efficient utilization of modern multiprocessor platforms for systems with real-time constrains. In this situation, the gang task model, in which each parallel sub-job has to be executed simultaneously, has shown significant performance benefits due to reduced context switches and more efficient intra-task synchronization. In this paper, we provide the first schedulability analysis for sporadic constrained-deadline gang task systems and propose a novel stationary gang scheduling algorithm. We show that the schedulability problem of gang task sets can be reduced to the uniprocessor self-suspension schedulability problem. Furthermore, we provide a class of partitioning algorithms to find a stationary gang assignment and show that it bounds the worst-case interference of each task. To demonstrate the effectiveness of our proposed approach, we evaluate it for implicit-deadline systems using randomized task sets under different settings, showing that our approach outperforms the state-of-the-art

Utilization-Based Scheduling of Flexible Mixed-Criticality Real-Time Tasks

Mixed-criticality models are an emerging paradigm for the design of real-time systems because of their significantly improved resource efficiency. However, formal mixed-criticality models have traditionally been characterized by two impractical assumptions: once \textit{any} high-criticality task overruns, \textit{all} low-criticality tasks are suspended and \textit{all other} high-criticality tasks are assumed to exhibit high-criticality behaviors at the same time. In this paper, we propose a more realistic mixed-criticality model, called the flexible mixed-criticality (FMC) model, in which these two issues are addressed in a combined manner. In this new model, only the overrun task itself is assumed to exhibit high-criticality behavior, while other high-criticality tasks remain in the same mode as before. The guaranteed service levels of low-criticality tasks are gracefully degraded with the overruns of high-criticality tasks. We derive a utilization-based technique to analyze the schedulability of this new mixed-criticality model under EDF-VD scheduling. During runtime, the proposed test condition serves an important criterion for dynamic service level tuning, by means of which the maximum available execution budget for low-criticality tasks can be directly determined with minimal overhead while guaranteeing mixed-criticality schedulability. Experiments demonstrate the effectiveness of the FMC scheme compared with state-of-the-art techniques.Comment: This paper has been submitted to IEEE Transaction on Computers (TC) on Sept-09th-201

AN INTELLIGENT SCHEDULER APPROACH TO MULTIPROCESSOR SCHEDULING OF APERIODIC TASKS

This paper presents a new scheduler capable of scheduling aperiodic tasks at real time in multiprocessor system. The algorithm proposes a new way to determine dynamically tasks of high priority and low priority finding the elapsed execution time and remaining execution time, and the amount of resource availability and deadline of task, with no prior knowledge of task arrival time and also ensures that no processor remains ideal thus utilizing processors at all times