Worst Case Execution Time | EPFL Graph Search

Le WCET ou Worst Case Execution Time, en français pire cas de temps d’exécution, équivaut au plus long temps d’exécution d’un programme informatique. Aujourd’hui, cette information est indispensable pour l’intégrité des systèmes embarqués voués à la sécurité comme un ABS ou un coussin gonflable de sécurité (« airbag ») dans une voiture, les systèmes de contrôle aérien et tout autre système informatique critique. Ces systèmes doivent réagir en temps réel de manière fiable, ce qui implique à la fois d’être sûr du résultat produit par le programme mais aussi de connaître absolument le temps qu’il prendra pour s’exécuter. Pour garantir cela, le plus long temps d’exécution a besoin d’être connu le plus précisément possible. Toutefois, un programme ne se comporte pas toujours de manière identique, son temps d’exécution peut varier en fonction du type de tâche à réaliser mais aussi du type de l’appareil sur lequel il s’exécute. Par conséquent, les caractéristiques du code du programme et l

Efficient Adaptive Hard Real-time Multi-processor Systems

Stefanos Skalistis

Modern computing systems are based on multi-processor systems, i.e. multiple cores on the same chip. Hard real-time systems are required to perform particular tasks within certain amount of time; failure to do so characterises an unaccepted behavior. Hard real-time systems are found in safety-critical applications, e.g. airbag control software, flight control software, etc. In safety-critical applications, failure to meet the real-time constraints can have catastrophic effects. The safe and, at the same time, efficient deployment of applications, with hard real-time constraints, on multi-processors is a challenging task. Scheduling methods and Models of Computation, that provide safe deployments, require a realistic estimation of the Worst-Case Execution Time (WCET) of tasks. The simultaneous access of shared resources by parallel tasks, causes interference delays due to hardware arbitration. Interference delays can be accounted for, with the pessimistic assumption that all possible interference can happen. The resulting schedules would be exceedingly conservative, thus the benefits of multi-processor would be significantly negated. Producing less pessimistic schedules is challenging due to the inter-dependency between WCET estimation and deployment optimisation. Accurate estimation of interference delays -and thus estimation of task WCET- depends on the way an application is deployed; deployment is an optimisation problem that depends on the estimation of task WCET. Another efficiency gap, which is of consequence in several systems (e.g. airbag control), stems from the fact that rarely tasks execute with their WCET. Safe runtime adaptation based on the Actual Execution Times, can yield additional improvements in terms of latency (more responsive systems). To achieve efficiency and retain adaptability, we propose that interference analysis should be coupled with the deployment process. The proposed interference analysis method estimates the possible amount of interference, based on an architecture and an application model. As more information is provided, such as scheduling, memory mapping, etc, the per-task interference estimation becomes more accurate. Thus, the method computes interference-sensitive WCET estimations (isWCET). Based on the isWCET method, we propose a method to break the inter-dependency between WCET estimation and deployment optimisation. Initially, the isWCETs are over-approximated, by assuming worst-case interference, and a safe deployment is derived. Subsequently, the proposed method computes accurate isWCETs by spatio-temporal exclusion, i.e. excluding interferences from non-overlapping tasks that share resources (space). Based on accurate isWCETs, the deployment solution is improved to provide better latency guarantees. We also propose a distributed runtime adaptation technique, that aims to improve run-time latency. Using isWCET estimations restricts the possible adaptations, as an adaptation might increase the interference and violate the safety guarantees. The proposed technique introduces statically scheduling dependencies between tasks that prevent additional interference. At runtime, a self-timed scheduling policy that respects these dependencies, is applied, proven to be safe, and with minimal overhead. Experimental evaluation on Kalray MPPA-256 shows that our methods improve isWCET up to 36%, guaranteed latency up to 46%, runtime performance up to 42%, with a consolidated performance gain of 50%.

EPFL2017

Near-optimal Deployment of Dataflow Applications on Many-core Platforms with Real-time Guarantees

Alena Simalatsar, Stefanos Skalistis

Safe and optimal deployment of data-streaming applications on many-core platforms requires the realistic estimation of task Worst-Case Execution Time (WCET). On the other hand, task WCET depends on the deployment solution, due to the varying number of interferences on shared resources, thus introducing a cyclic dependency. Moreover, WCET is still an over-approximation of the Actual Execution Time (AET), thus leaving room for run-time optimisation. In this paper we introduce an offline/online optimisation approach. In the offline phase, we first break the cyclic dependency and acquire safe and near-optimal solutions for tasks partitioning/placement, mapping, scheduling and buffer allocation. Then, we tighten the WCETs and update the scheduling function accordingly. In the online phase we introduce a safe distributed readjustment of the offline schedule, based on the AET. Experiments on a Kalray MPPA-256 platform show a tightening of the guaranteed latency up to 46% in the offline phase, and 41% latency reduction in the online phase. In total, we achieve more than 50% of latency reduction.

IEEE2017

Worst-case execution time analysis for many-core architectures with NoC

Alena Simalatsar, Stefanos Skalistis

The optimal deployment of data streaming applications onto multi-/many-core platform providing real-time guarantees requires to solve the application partitioning and placement, buffer allocation and task mapping and scheduling optimisation problem using the tasks Worst-Case Execution Time (WCET). In turn, tasks WCET varies due to interferences that tasks experience when accessing shared resources that depend on the solutions of the optimisation problem. In this paper we propose a detailed interference-based method that first over-approximates the WCET and then tightens it by pruning out the interferences from tasks not overlapping in time and memory. We prove that derived bounds are safe. We have found that interferences on average amount to 10% of WCET, and were able to improve latency guarantee up to 34%.

Springer Int Publishing Ag2016

Efficient Adaptive Hard Real-time Multi-processor Systems

Stefanos Skalistis

EPFL2017