An Analysis of Lazy and Eager Limited Preemption Approaches under DAG-Based Global Fixed Priority Scheduling

DAG-based scheduling models have been shown to effectively express the parallel execution of current many-core heterogeneous architectures. However, their applicability to real-time settings is limited by the difficulties to find tight estimations of the worst-case timing parameters of tasks that may arbitrarily be preempted/migrated at any instruction. An efficient approach to increase the system predictability is to limit task preemptions to a set of pre-defined points. This limited preemption model supports two different preemption approaches, eager and lazy, which have been analyzed only for sequential task-sets. This paper proposes a new response time analysis that computes an upper bound on the lower priority blocking that each task may incur with eager and lazy preemptions. We evaluate our analysis with both, synthetic DAG-based task-sets and a real case-study from the automotive domain. Results from the analysis demonstrate that, despite the eager approach generates a higher number of priority inversions, the blocking impact is generally smaller than in the lazy approach, leading to a better schedulability performance.This work was funded by the EU projects P-SOCRATES (FP7-ICT-2013-10) and HERCULES (H2020/ICT/2015/688860), and the Spanish Ministry of Science and Innovation under contract TIN2015-65316-P.Peer ReviewedPostprint (author's final draft

Replica determinism and flexible scheduling in hard real-time dependable systems

Fault-tolerant real-time systems are typically based on active replication where replicated entities are required to deliver their outputs in an identical order within a given time interval. Distributed scheduling of replicated tasks, however, violates this requirement if on-line scheduling, preemptive scheduling, or scheduling of dissimilar replicated task sets is employed. This problem of inconsistent task outputs has been solved previously by coordinating the decisions of the local schedulers such that replicated tasks are executed in an identical order. Global coordination results either in an extremely high communication effort to agree on each schedule decision or in an overly restrictive execution model where on-line scheduling, arbitrary preemptions, and nonidentically replicated task sets are not allowed. To overcome these restrictions, a new method, called timed messages, is introduced. Timed messages guarantee deterministic operation by presenting consistent message versions to the replicated tasks. This approach is based on simulated common knowledge and a sparse time base. Timed messages are very effective since they neither require communication between the local scheduler nor do they restrict usage of on-line flexible scheduling, preemptions and nonidentically replicated task sets

Efficient Memory-Protected Integration of Add-On Software Subsystems in Small Embedded Automotive Applications

Current innovations in the automotive industry evolve mainly in the electronics and software domain. This leads to an increasing integration of additional software subsystems into already existing electronic control units (ECUs) to cope with the raised amount and complexity of present ECUs in modern high-end vehicles. This paper discusses different approaches which are required to integrate such add-on software subsystems in an isolated memory domain, and considers particularly the special needs of small embedded systems—including the limited hardware support. Special focus is brought to the efficient detection of malicious memory accesses, as well as the benefits of a thereupon possible and adaptable failure-handling strategy. All investigations are based on a developed memory-protection framework which has been tailored to the special needs of a sample vehicle dynamics control system. Its usage allows the combination of. integrating additional subsystems without reducing the main application’s availability

Enabling preemptive multiprogramming on GPUs

GPUs are being increasingly adopted as compute accelerators in many domains, spanning environments from mobile systems to cloud computing. These systems are usually running multiple applications, from one or several users. However GPUs do not provide the support for resource sharing traditionally expected in these scenarios. Thus, such systems are unable to provide key multiprogrammed workload requirements, such as responsiveness, fairness or quality of service. In this paper, we propose a set of hardware extensions that allow GPUs to efficiently support multiprogrammed GPU workloads. We argue for preemptive multitasking and design two preemption mechanisms that can be used to implement GPU scheduling policies. We extend the architecture to allow concurrent execution of GPU kernels from different user processes and implement a scheduling policy that dynamically distributes the GPU cores among concurrently running kernels, according to their priorities. We extend the NVIDIA GK110 (Kepler) like GPU architecture with our proposals and evaluate them on a set of multiprogrammed workloads with up to eight concurrent processes. Our proposals improve execution time of high-priority processes by 15.6x, the average application turnaround time between 1.5x to 2x, and system fairness up to 3.4x.We would like to thank the anonymous reviewers, Alexan- der Veidenbaum, Carlos Villavieja, Lluis Vilanova, Lluc Al- varez, and Marc Jorda on their comments and help improving our work and this paper. This work is supported by Euro- pean Commission through TERAFLUX (FP7-249013), Mont- Blanc (FP7-288777), and RoMoL (GA-321253) projects, NVIDIA through the CUDA Center of Excellence program, Spanish Government through Programa Severo Ochoa (SEV-2011-0067) and Spanish Ministry of Science and Technology through TIN2007-60625 and TIN2012-34557 projects.Peer ReviewedPostprint (author’s final draft

A modied branch and cut procedure for resource portfolio problem under relaxed resource dedication policy

Multi-project scheduling problems are characterized by the way resources are managed in the problem environment. The general approach in multi-project scheduling literature is to consider resource capacities as a common pool that can be shared among all projects without any restrictions or costs. The way the resources are used in a multi-project environment is called resource management policy and the aforementioned assumption is called Resource Sharing Policy in this study. The resource sharing policy is not a generalization for multi-project scheduling environments and different resource management policies maybe defined to identify characteristics of different problem environments. In this study, we present a resource management policy which prevents sharing of resources among projects but allows resource transfers when a project starts after the completion of another one. This policy is called the Relaxed Resource Dedication (RRD) Policy in this study. The general resource capacities might or might not be decision variables. We will treat here the case where the general available amounts of resources are decision variables to be determined subject to a limited budget. We call this problem as the Resource Portfolio Problem (RPP). In this study, RPP is investigated under RRD policy and a modified Branch and Cut (B&C)procedure based on CPLEX is proposed. The B&C procedure of CPLEX is modified with different branching strategies, heuristic solution approaches and valid inequalities. The computational studies presented demonstrate the effectiveness of the proposed solution approaches

Task Scheduling for Multiprocessor Systems Using Queuing Theory

This research focuses on comparing different multi-processor task scheduling algorithms. Each algorithm has been simulated using one of queuing theory models in Operations Research (OR) science to evaluate its behavior and efficiency. The comparison includes an analysis of the behavior of central processing unit (CPU) when receiving number of jobs at four random job duration patterns that are; (random, ascending, descending, and volatile low-high). Microsoft Excel 2010 was used to form the data of each case, and the result shows convergence and divergence among the studied algorithms at different patterns. Also it has been found that the Fleischer algorithm is very efficient in enhancing and minimizing the waiting duration for each job at the total job queue of the CPU. Keywords: Operations Research, Queuing Theory, Multiprocessor, Scheduling Algorithms, Simulation

Towards an OpenMP Specification for Critical Real-Time Systems

OpenMP is increasingly being considered as a convenient parallel programming model to cope with the performance requirements of critical real-time systems. Recent works demonstrate that OpenMP enables to derive guarantees on the functional and timing behavior of the system, a fundamental requirement of such systems. These works, however, focus only on the exploitation of fine grain parallelism and do not take into account the peculiarities of critical real-time systems, commonly composed of a set of concurrent functionalities. OpenMP allows exploiting the parallelism exposed within real-time tasks and among them. This paper analyzes the challenges of combining the concurrency model of real-time tasks with the parallel model of OpenMP. We demonstrate that OpenMP is suitable to develop advanced critical real-time systems by virtue of few changes on the specification, which allow the scheduling behavior desired (regarding execution priorities, preemption, migration and allocation strategies) in such systems.The research leading to these results has received funding from the Spanish Ministry of Science and Innovation, under contract TIN2015-65316-P, and from the European Union's Horizon 2020 Programme under the CLASS Project (www.classproject. eu), grant agreement No 780622.Peer ReviewedPostprint (author's final draft

YARTISS: A Tool to Visualize, Test, Compare and Evaluate Real-Time Scheduling Algorithms

International audienceIn this paper, we present a free software written in Java, YARTISS, which is a real-time multiprocessor scheduling simulator. It is aimed at comparing user-customized algorithms with ones from the literature on real-time scheduling. This simulator is designed as an easy-to-use modular tool in which new modules can be added without the need to decompress, edit nor recompile existing parts. It can simulate the execution of a large number of concurrent periodic independent task sets on multiprocessor systems and generate clear visual results of the scheduling process (both schedules and tunable metrics presentations). Other task models are already implemented in the simulator, like graph tasks with precedence constraints and it is easily extensible to other task models. Moreover, YARTISS can simulate task sets in which energy consumption is a scheduling parameter in the same manner as Worst Case Execution Time (WCET)