MARACAS: a real-time multicore VCPU scheduling framework

This paper describes a multicore scheduling and load-balancing framework called MARACAS, to address shared cache and memory bus contention. It builds upon prior work centered around the concept of virtual CPU (VCPU) scheduling. Threads are associated with VCPUs that have periodically replenished time budgets. VCPUs are guaranteed to receive their periodic budgets even if they are migrated between cores. A load balancing algorithm ensures VCPUs are mapped to cores to fairly distribute surplus CPU cycles, after ensuring VCPU timing guarantees. MARACAS uses surplus cycles to throttle the execution of threads running on specific cores when memory contention exceeds a certain threshold. This enables threads on other cores to make better progress without interference from co-runners. Our scheduling framework features a novel memory-aware scheduling approach that uses performance counters to derive an average memory request latency. We show that latency-based memory throttling is more effective than rate-based memory access control in reducing bus contention. MARACAS also supports cache-aware scheduling and migration using page recoloring to improve performance isolation amongst VCPUs. Experiments show how MARACAS reduces multicore resource contention, leading to improved task progress.http://www.cs.bu.edu/fac/richwest/papers/rtss_2016.pdfAccepted manuscrip

Real-time scheduling with resource sharing on heterogeneous multiprocessors

Consider the problem of scheduling a task set τ of implicit-deadline sporadic tasks to meet all deadlines on a t-type heterogeneous multiprocessor platform where tasks may access multiple shared resources. The multiprocessor platform has m k processors of type-k, where k∈{1,2,…,t}. The execution time of a task depends on the type of processor on which it executes. The set of shared resources is denoted by R. For each task τ i , there is a resource set R i ⊆R such that for each job of τ i , during one phase of its execution, the job requests to hold the resource set R i exclusively with the interpretation that (i) the job makes a single request to hold all the resources in the resource set R i and (ii) at all times, when a job of τ i holds R i , no other job holds any resource in R i . Each job of task τ i may request the resource set R i at most once during its execution. A job is allowed to migrate when it requests a resource set and when it releases the resource set but a job is not allowed to migrate at other times. Our goal is to design a scheduling algorithm for this problem and prove its performance. We propose an algorithm, LP-EE-vpr, which offers the guarantee that if an implicit-deadline sporadic task set is schedulable on a t-type heterogeneous multiprocessor platform by an optimal scheduling algorithm that allows a job to migrate only when it requests or releases a resource set, then our algorithm also meets the deadlines with the same restriction on job migration, if given processors 4×(1+MAXP×⌈|P|×MAXPmin{m1,m2,…,mt}⌉) times as fast. (Here MAXP and |P| are computed based on the resource sets that tasks request.) For the special case that each task requests at most one resource, the bound of LP-EE-vpr collapses to 4×(1+⌈|R|min{m1,m2,…,mt}⌉). To the best of our knowledge, LP-EE-vpr is the first algorithm with proven performance guarantee for real-time scheduling of sporadic tasks with resource sharing on t-type heterogeneous multiprocessors

Integrating Pragmatic Constraints and Behaviors into Real-Time Scheduling Theory

Scheduling theory has been studied and developed extensively in prior research. In some existing scheduling theory results, the focus is primarily on demonstrating interesting theoretical properties, thus these results are not always cognizant of pragmatic constraints. We seek to determine how existing scheduling theory can be improved with respect to pragmatic constraints and behaviors. The goal of this research is to study and design scheduling algorithms for scheduling real-time workload under constraints and behaviors found in real-time systems. Based on our study we derive a scheduling algorithm for partitioning a collection of real-time tasks in a manner that is cognizant of multiple resource constraints. We apply the above scheduling algorithm for partitioning mixed-criticality tasks. In real-time systems the scheduling algorithm must schedule workload such that all timing constraints are met; we verify this using schedulability tests. We describe schedulability tests for each of the scheduling algorithms that we derive. We also propose a new schedulability test for an existing scheduling algorithm that is commonly used in real-time systems research for scheduling tasks with limited-preemptivity. Finally, we propose a scheduling algorithm and schedulability test for scheduling real-time workload on processors that allow dynamic overclocking.Doctor of Philosoph

A Survey of Research into Mixed Criticality Systems

This survey covers research into mixed criticality systems that has been published since Vestal’s seminal paper in 2007, up until the end of 2016. The survey is organised along the lines of the major research areas within this topic. These include single processor analysis (including fixed priority and EDF scheduling, shared resources and static and synchronous scheduling), multiprocessor analysis, realistic models, and systems issues. The survey also explores the relationship between research into mixed criticality systems and other topics such as hard and soft time constraints, fault tolerant scheduling, hierarchical scheduling, cyber physical systems, probabilistic real-time systems, and industrial safety standards

Algorithms for Hierarchical and Semi-Partitioned Parallel Scheduling

We propose a model for scheduling jobs in a parallel machine setting that takes into account the cost of migrations by assuming that the processing time of a job may depend on the specific set of machines among which the job is migrated. For the makespan minimization objective, the model generalizes classical scheduling problems such as unrelated parallel machine scheduling, as well as novel ones such as semi-partitioned and clustered scheduling. In the case of a hierarchical family of machines, we derive a compact integer linear programming formulation of the problem and leverage its fractional relaxation to obtain a polynomial-time 2-approximation algorithm. Extensions that incorporate memory capacity constraints are also discussed

Robust Partitioned Scheduling for Static-Priority Real-Time Multiprocessor Systems with Shared Resources

International audienceWe focus on the partitioned scheduling of sporadic real-time tasks with constrained deadlines. The scheduling policy on each processor is static-priority. The considered tasks are not independent and the consistency of these shared data is ensured by a multiprocessor synchronization protocol. Considering these assumptions, we propose a partitioned scheduling algorithm which tends to maximize the robustness of the tasks to the Worst Case Execution Time (WCET) overruns faults. We describe the context of the problem and we outline our solution based on simulated annealing

Real-time scheduling in multicore : time- and space-partitioned architectures

Tese de doutoramento, Informática (Engenharia Informática), Universidade de Lisboa, Faculdade de Ciências, 2014The evolution of computing systems to address size, weight and power consumption (SWaP) has led to the trend of integrating functions (otherwise provided by separate systems) as subsystems of a single system. To cope with the added complexity of developing and validating such a system, these functions are maintained and analyzed as components with clear boundaries and interfaces. In the case of real-time systems, the adopted component-based approach should maintain the timeliness properties of the function inside each individual component, regardless of the remaining components. One approach to this issue is time and space partitioning (TSP)—enforcing strict separation between components in the time and space domains. This allows heterogeneous components (different real-time requirements, criticality, developed by different teams and/or with different technologies) to safely coexist. The concepts of TSP have been adopted in the civil aviation, aerospace, and (to some extent) automotive industries. These industries are also embracing multiprocessor (or multicore) platforms, either with identical or nonidentical processors, but are not taking full advantage thereof because of a lack of support in terms of verification and certification. Furthermore, due to the use of the TSP in those domains, compatibility between TSP and multiprocessor is highly desired. This is not the present case, as the reference TSP-related specifications in the aforementioned industries show limited support to multiprocessor. In this dissertation, we defend that the active exploitation of multiple (possibly non-identical) processor cores can augment the processing capacity of the time- and space-partitioned (TSP) systems, while maintaining a compromise with size, weight and power consumption (SWaP), and open room for supporting self-adaptive behavior. To allow applying our results to a more general class of systems, we analyze TSP systems as a special case of hierarchical scheduling and adopt a compositional analysis methodology.Fundação para a Ciência e a Tecnologia (FCT, SFRH/BD/60193/2009, programa PESSOA, projeto SAPIENT); the European Space Agency Innovation (ESA) Triangle Initiative program through ESTEC Contract 21217/07/NL/CB, Project AIR-II; the European Commission Seventh Framework Programme (FP7) through project KARYON (IST-FP7-STREP-288195)

Provably good scheduling of sporadic tasks with resource sharing on a two-type heterogeneous multiprocessor platform

Consider the problem of scheduling a set of implicit-deadline sporadic tasks to meet all deadlines on a two-type heterogeneous multiprocessor platform where a task may request at most one of |R| shared resources. There are m1 processors of type-1 and m2 processors of type-2. Tasks may migrate only when requesting or releasing resources. We present a new algorithm, FF-3C-vpr, which offers a guarantee that if a task set is schedulable to meet deadlines by an optimal task assignment scheme that only allows tasks to migrate when requesting or releasing a resource, then FF-3Cvpr also meets deadlines if given processors 4+6*ceil(|R|/min(m1,m2)) times as fast. As far as we know, it is the first result for resource sharing on heterogeneous platforms with provable performance

Partitioned real-time scheduling on heterogeneous shared-memory multiprocessors

We consider several real-time scheduling problems on heterogeneous multiprocessor platforms, in which the different processors share a common memory pool. These include (i)~scheduling a collection of implicit-deadline sporadic tasks with the objective of meeting all deadlines; and (ii)~scheduling a collection of independent jobs with the objective of minimizing the makespan of the schedule. Both these problems are intractable (NP-hard). For each, we derive polynomial-time algorithms for solving them approximately, and show that these algorithms have bounded deviation from optimal behavior. We also consider the problem of determining how much common memory a platform needs in order to be able to accommodate a specified real-time workload