Reservation-Based Federated Scheduling for Parallel Real-Time Tasks

This paper considers the scheduling of parallel real-time tasks with arbitrary-deadlines. Each job of a parallel task is described as a directed acyclic graph (DAG). In contrast to prior work in this area, where decomposition-based scheduling algorithms are proposed based on the DAG-structure and inter-task interference is analyzed as self-suspending behavior, this paper generalizes the federated scheduling approach. We propose a reservation-based algorithm, called reservation-based federated scheduling, that dominates federated scheduling. We provide general constraints for the design of such systems and prove that reservation-based federated scheduling has a constant speedup factor with respect to any optimal DAG task scheduler. Furthermore, the presented algorithm can be used in conjunction with any scheduler and scheduling analysis suitable for ordinary arbitrary-deadline sporadic task sets, i.e., without parallelism

Randomized Caches Can Be Pretty Useful to Hard Real-Time Systems

Cache randomization per se, and its viability for probabilistic timing analysis (PTA) of critical real-time systems, are receiving increasingly close attention from the scientific community and the industrial practitioners. In fact, the very notion of introducing randomness and probabilities in time-critical systems has caused strenuous debates owing to the apparent clash that this idea has with the strictly deterministic view traditionally held for those systems. A paper recently appeared in LITES (Reineke, J. (2014). Randomized Caches Considered Harmful in Hard Real-Time Systems. LITES, 1(1), 03:1-03:13.) provides a critical analysis of the weaknesses and risks entailed in using randomized caches in hard real-time systems. In order to provide the interested reader with a fuller, balanced appreciation of the subject matter, a critical analysis of the benefits brought about by that innovation should be provided also. This short paper addresses that need by revisiting the array of issues addressed in the cited work, in the light of the latest advances to the relevant state of the art. Accordingly, we show that the potential benefits of randomized caches do offset their limitations, causing them to be - when used in conjunction with PTA - a serious competitor to conventional designs

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This PhD dissertation has resulted in six publications in which one of the papers received Best Paper Award at ICESS 2021. All the papers were published in reputed venues for real-time systems research, i.e., RTSS 2020, RTNS 2021, ICESS 2021, RTCSA 2022, RTSS 2022, Elsevier’s Journal of System Architecture. Two more papers are expected to be published soon.Multicore platforms share the hardware resources such as caches, interconnects, and main memory among all the cores. Due to such sharing, tasks running on different cores compete to access these shared resources which can potentially result in shared resource contention. This shared resource contention can increase the execution times of tasks in a non-deterministic manner. Consequently, the shared resource contention is problematic for hard real-time systems, i.e., systems that run tasks with stringent timing requirements. To address this issue, this PhD dissertation builds novel solutions to model and analyze the shared resource contention that can be suffered by tasks executing on a multicore system. The shared resource contention aware schedulability analysis is then derived by integrating the maximum shared resource contention that can be suffered by the tasks.This work was supported by the CISTER Research Unit (UIDP/UIDB/04234/2020), financed by National Funds through FCT/MCTES (Portuguese Foundation for Science and Technology); by project ADACORSA (ECSEL/0010/2019 - JU grant nr. 876019) financed through National Funds from FCT and European funds through the EU ECSEL JU. The JU receives support from the European Union’s Horizon 2020 research and innovation programme and Austria, Sweden, Spain, Italy, France, Portugal, Ireland, Finland, Slovenia, Poland, Netherlands, Turkey - Disclaimer: This document reflects only the author’s view and the Commission is not responsible for any use that may be made of the information it contains. This work is also a result of the work developed under project Aero.Next Portugal (nº C645727867-00000066) and FLY-PT (grant nº 46079, POCI-01-0247-FEDER-046079), also funded by FCT under PhD grant 2020.09532.BD.info:eu-repo/semantics/publishedVersio

Semi-Partitioned Scheduling of Dynamic Real-Time Workload: A Practical Approach Based on Analysis-Driven Load Balancing

Recent work showed that semi-partitioned scheduling can achieve near-optimal schedulability performance, is simpler to implement compared to global scheduling, and less heavier in terms of runtime overhead, thus resulting in an excellent choice for implementing real-world systems. However, semi-partitioned scheduling typically leverages an off-line design to allocate tasks across the available processors, which requires a-priori knowledge of the workload. Conversely, several simple global schedulers, as global earliest-deadline first (G-EDF), can transparently support dynamic workload without requiring a task-allocation phase. Nonetheless, such schedulers exhibit poor worst-case performance. This work proposes a semi-partitioned approach to efficiently schedule dynamic real-time workload on a multiprocessor system. A linear-time approximation for the C=D splitting scheme under partitioned EDF scheduling is first presented to reduce the complexity of online scheduling decisions. Then, a load-balancing algorithm is proposed for admitting new real-time workload in the system with limited workload re-allocation. A large-scale experimental study shows that the linear-time approximation has a very limited utilization loss compared to the exact technique and the proposed approach achieves very high schedulability performance, with a consistent improvement on G-EDF and pure partitioned EDF scheduling

Nested, but Separate: Isolating Unrelated Critical Sections in Real-Time Nested Locking

Prior work has produced multiprocessor real-time locking protocols that ensure asymptotically optimal bounds on priority inversion, that support fine-grained nesting of critical sections, or that are independence-preserving under clustered scheduling. However, while several protocols manage to come with two out of these three desirable features, no protocol to date accomplishes all three. Motivated by this gap in capabilities, this paper introduces the Group Independence-Preserving Protocol (GIPP), the first protocol to support fine-grained nested locking, guarantee a notion of independence preservation for fine-grained nested locking, and ensure asymptotically optimal priority-inversion bounds. As a stepping stone, this paper further presents the Clustered k-Exclusion Independence-Preserving Protocol (CKIP), the first asymptotically optimal independence-preserving k-exclusion lock for clustered scheduling. The GIPP and the CKIP rely on allocation inheritance (a.k.a. migratory priority inheritance) as a key mechanism to accomplish independence preservation

Design and Implementation of a Time Predictable Processor: Evaluation With a Space Case Study

Embedded real-time systems like those found in automotive, rail and aerospace, steadily require higher levels of guaranteed computing performance (and hence time predictability) motivated by the increasing number of functionalities provided by software. However, high-performance processor design is driven by the average-performance needs of mainstream market. To make things worse, changing those designs is hard since the embedded real-time market is comparatively a small market. A path to address this mismatch is designing low-complexity hardware features that favor time predictability and can be enabled/disabled not to affect average performance when performance guarantees are not required. In this line, we present the lessons learned designing and implementing LEOPARD, a four-core processor facilitating measurement-based timing analysis (widely used in most domains). LEOPARD has been designed adding low-overhead hardware mechanisms to a LEON3 processor baseline that allow capturing the impact of jittery resources (i.e. with variable latency) in the measurements performed at analysis time. In particular, at core level we handle the jitter of caches, TLBs and variable-latency floating point units; and at the chip level, we deal with contention so that time-composable timing guarantees can be obtained. The result of our applied study with a Space application shows how per-resource jitter is controlled facilitating the computation of high-quality WCET estimates

Leveraging Hardware QoS to Control Contention in the Xilinx Zynq UltraScale+ MPSoC

The interference co-running tasks generate on each other’s timing behavior continues to be one of the main challenges to be addressed before Multi-Processor System-on-Chip (MPSoCs) are fully embraced in critical systems like those deployed in avionics and automotive domains. Modern MPSoCs like the Xilinx Zynq UltraScale+ incorporate hardware Quality of Service (QoS) mechanisms that can help controlling contention among tasks. Given the distributed nature of modern MPSoCs, the route a request follows from its source (usually a compute element like a CPU) to its target (usually a memory) crosses several QoS points, each one potentially implementing a different QoS mechanism. Mastering QoS mechanisms individually, as well as their combined operation, is pivotal to obtain the expected benefits from the QoS support. In this work, we perform, to our knowledge, the first qualitative and quantitative analysis of the distributed QoS mechanisms in the Xilinx UltraScale+ MPSoC. We empirically derive QoS information not covered by the technical documentation, and show limitations and benefits of the available QoS support. To that end, we use a case study building on neural network kernels commonly used in autonomous systems in different real-time domains.This work has been partially supported by the Spanish Ministry of Science and Innovation under grant PID2019-107255GB; the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 878752 (MASTECS) and the European Research Council (ERC) grant agreement No. 772773 (SuPerCom).Peer ReviewedPostprint (published version