An Overview of Approaches Towards the Timing Analysability of Parallel Architecture

In order to meet performance/low energy/integration requirements, parallel architectures (multithreaded cores and multi-cores) are more and more considered in the design of embedded systems running critical software. The objective is to run several applications concurrently. When applications have strict real-time constraints, two questions arise: a) how can the worst-case execution time (WCET) of each application be computed while concurrent applications might interfere? b)~how can the tasks be scheduled so that they are guarantee to meet their deadlines? The second question has received much attention for several years~cite{CFHS04,DaBu11}. Proposed schemes generally assume that the first question has been solved, and in addition that they do not impact the WCETs. In effect, the first question is far from been answered even if several approaches have been proposed in the literature. In this paper, we present an overview of these approaches from the point of view of static WCET analysis techniques

Contention in multicore hardware shared resources: Understanding of the state of the art

The real-time systems community has over the years devoted considerable attention to the impact on execution timing that arises from contention on access to hardware shared resources. The relevance of this problem has been accentuated with the arrival of multicore processors. From the state of the art on the subject, there appears to be considerable diversity in the understanding of the problem and in the “approach” to solve it. This sparseness makes it difficult for any reader to form a coherent picture of the problem and solution space. This paper draws a tentative taxonomy in which each known approach to the problem can be categorised based on its specific goals and assumptions.Postprint (published version

HWP: Hardware Support to Reconcile Cache Energy, Complexity, Performance and WCET Estimates in Multicore Real-Time Systems

High-performance processors have deployed multilevel cache (MLC) systems for decades. In the embedded real-time market, the use of MLC is also on the rise, with processors for future systems in space, railway, avionics and automotive already featuring two or more cache levels. One of the most critical elements for MLC is the write policy that not only affects several key metrics such as performance, WCET estimates, energy/power, and reliability, but also the design of complexity-prone cache coherence protocol and cache reliability solutions. In this paper we make an extensive analysis of existing write policies, namely write-through (WT) and write-back (WB). In the context of the real-time domain, we show that no write policy is superior for all metrics: WT simplifies the design of the coherence and reliability solutions at the cost of performance, WCET, and energy; while WB improves performance and energy results, but complicates cache design. To take the best of each policy, we propose Hybrid Write Policy (HWP) a low-complexity hardware mechanism that reconciles the benefits of WT in terms of simplifying the cache design (e.g. coherence solution) and the benefits of WB in improved average performance and WCET estimates as the pressure on the interconnection network increases. Guaranteed performance results show that HWP scales with core count similar to WB. Likewise, HWP reduces cache energy usage of WT, to levels similar to those of WB. These benefits are obtained while retaining the reduced coherence complexity of WT, in contrast to high coherence costs under WB

On the Determinism of Multi-core Processors

Hard real time systems are evolving in order to respond to the increasing demand in complex functionalities while taking advantage of newer hardware. Software development for safety critical systems has to comply with strict requirements that will facilitate the certification process. During this process, each part of the system is evaluated, requiring a certain level of assurance in order to provide confidence in the product. In particular there must be a level of confidence that the system behaves deterministically that may be based on functionality, resources and time. The success of system verification depends greatly on the capacity to determine its exact behavior. Nonetheless, hardware evolved in order to maximize the average computation power throughput with little to no regard to the deterministic aspect. Therefore modern architectural features of processors, like pipelines, cache memories and co-processors, make it hard to verify that all the needed properties are respected. The multi-core is furthermore difficult to analyze as the architecture employs mechanisms that compromise strong spatial and temporal partitioning when using shared resources without rigorous access control like shared caches or shared input/outputs. In this paper we identify and analyze the main sources of nondeterminism of the multi-cores with regard to the timing estimation. Precise determination of the worst case execution time is a challenging task even in single-core architectures. The problems are accentuated in the multi-core context mainly due to the resource sharing that can lead to highly complex interactions or to nondeterminism. Most of the units that generate behaviors that are hard to take into account can be deactivated, but it is not always easy to predict the impact on the performance. Nevertheless some of the features cannot be disabled (such as the out of order execution or some nondeterministic crossbar access policies) which leads to the invalidation of the respective platform for applications with high criticality level. We will address the problematic units, propose configuration or architecture guidelines and estimate their impact on the performance and determinism of the system

The Heptane Static Worst-Case Execution Time Estimation Tool

Estimation of worst-case execution times (WCETs) is required to validate the temporal behavior of hard real time systems. Heptane is an open-source software program that estimates upper bounds of execution times on MIPS and ARM v7 architectures, offered to the WCET estimation community to experiment new WCET estimation techniques. The software architecture of Heptane was designed to be as modular and extensible as possible to facilitate the integration of new approaches. This paper is devoted to a description of Heptane, and includes information on the analyses it implements, how to use it and extend it

A Survey on Cache Management Mechanisms for Real-Time Embedded Systems

© ACM, 2015. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in ACM Computing Surveys, {48, 2, (November 2015)} http://doi.acm.org/10.1145/2830555Multicore processors are being extensively used by real-time systems, mainly because of their demand for increased computing power. However, multicore processors have shared resources that affect the predictability of real-time systems, which is the key to correctly estimate the worst-case execution time of tasks. One of the main factors for unpredictability in a multicore processor is the cache memory hierarchy. Recently, many research works have proposed different techniques to deal with caches in multicore processors in the context of real-time systems. Nevertheless, a review and categorization of these techniques is still an open topic and would be very useful for the real-time community. In this article, we present a survey of cache management techniques for real-time embedded systems, from the first studies of the field in 1990 up to the latest research published in 2014. We categorize the main research works and provide a detailed comparison in terms of similarities and differences. We also identify key challenges and discuss future research directions.King Saud University NSER

A dynamic execution time estimation model to save energy in heterogeneous multicores running periodic tasks

this is the author’s version of a work that was accepted for publication in Future Generation Computer Systems. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Future Generation Computer Systems, vol. 56 (2016). DOI 10.1016/j.future.2015.06.011.Nowadays, real-time embedded applications have to cope with an increasing demand of functionalities, which require increasing processing capabilities. With this aim real-time systems are being implemented on top of high-performance multicore processors that run multithreaded periodic workloads by allocating threads to individual cores. In addition, to improve both performance and energy savings, the industry is introducing new multicore designs such as ARM’s big.LITTLE that include heterogeneous cores in the same package. A key issue to improve energy savings in multicore embedded real-time systems and reduce the number of deadline misses is to accurately estimate the execution time of the tasks considering the supported processor frequencies. Two main aspects make this estimation difficult. First, the running threads compete among them for shared resources. Second, almost all current microprocessors implement Dynamic Voltage and Frequency Scaling (DVFS) regulators to dynamically adjust the voltage/frequency at run-time according to the workload behavior. Existing execution time estimation models rely on off-line analysis or on the assumption that the task execution time scales linearly with the processor frequency, which can bring important deviations since the memory system uses a different power supply. In contrast, this paper proposes the Processor–Memory (Proc–Mem) model, which dynamically predicts the distinct task execution times depending on the implemented processor frequencies. A power-aware EDF (Earliest Deadline First)-based scheduler using the Proc–Mem approach has been evaluated and compared against the same scheduler using a typical Constant Memory Access Time model, namely CMAT. Results on a heterogeneous multicore processor show that the average deviation of Proc–Mem is only by 5.55% with respect to the actual measured execution time, while the average deviation of the CMAT model is 36.42%. These results turn in important energy savings, by 18% on average and up to 31% in some mixes, in comparison to CMAT for a similar number of deadline misses. © 2015 Elsevier B.V. All rights reserved.This work was supported by the Spanish Ministerio de Economia y Competitividad (MINECO) and by FEDER funds under Grant TIN2012-38341-004-01, and by the Intel Early Career Faculty Honor Program Award.Sahuquillo Borrás, J.; Hassan Mohamed, H.; Petit Martí, SV.; March Cabrelles, JL.; Duato Marín, JF. (2016). A dynamic execution time estimation model to save energy in heterogeneous multicores running periodic tasks. Future Generation Computer Systems. 56:211-219. https://doi.org/10.1016/j.future.2015.06.011S2112195

Cache-Conscious Offline Real-Time Task Scheduling for Multi-Core Processors

Most schedulability analysis techniques for multi-core architectures assume a single Worst-Case Execution Time (WCET) per task, which is valid in all execution conditions. This assumption is too pessimistic for parallel applications running on multi-core architectures with local instruction or data caches, for which the WCET of a task depends on the cache contents at the beginning of its execution, itself depending on the task that was executed before the task under study. In this paper, we propose two scheduling techniques for multi-core architectures equipped with local instruction and data caches. The two techniques schedule a parallel application modeled as a task graph, and generate a static partitioned non-preemptive schedule. We propose an optimal method, using an Integer Linear Programming (ILP) formulation, as well as a heuristic method based on list scheduling. Experimental results show that by taking into account the effect of private caches on tasks\u27 WCETs, the length of generated schedules is significantly reduced as compared to schedules generated by cache-unaware scheduling methods. The observed schedule length reduction on streaming applications is 11% on average for the optimal method and 9% on average for the heuristic method

Cache Interference-aware Task Partitioning for Non-preemptive Real-time Multi-core Systems

Shared caches in multi-core processors introduce serious difficulties in providing guarantees on the real-time properties of embedded software due to the interaction and the resulting contention in the shared caches. Prior work has studied the schedulability analysis of global scheduling for real-time multi-core systems with shared caches. This article considers another common scheduling paradigm: partitioned scheduling in the presence of shared cache interference. To achieve this, we propose CITTA, a cache interference-aware task partitioning algorithm. We first analyze the shared cache interference between two programs for set-associative instruction and data caches. Then, an integer programming formulation is constructed to calculate the upper bound on cache interference exhibited by a task, which is required by CITTA. We conduct schedulability analysis of CITTA and formally prove its correctness. A set of experiments is performed to evaluate the schedulability performance of CITTA against global EDF scheduling and other greedy partition approaches such as First-fit and Worst-fit over randomly generated tasksets and realistic workloads in embedded systems. Our empirical evaluations show that CITTA outperforms global EDF scheduling and greedy partition approaches in terms of task sets deemed schedulable