The real-time systems community is shrinking and needs to bridge the gap between academic research an industry practice. In my pitch at ECRTS, I shared our view on model-driven system performance engineering for cyber-physical systems and encouraged the community increase its scope and take a broader responsibility for timing-related issues in systems to achieve those goals. This means working in more of the focus areas that we have identified in our vision and validated with our industry partners, but also reconsidering some directions in areas where work is already taking place. This means less focus on hard real-time requirements and formal methods and more focus on:
• system-level KPIs instead of meeting deadlines in subsystems
• soft real-time requirements
• timing requirements beyond software
• system performance modelling, model calibration, and model learning
• data-driven performance analysis, optimization, verification, and diagnostics, e.g. using traces
I encouraged the community to have a look at our vision for model-based system performance engineering for industrial cyber-physical systems and asked to think about how they could contribute through their current and future work.
Please have a look at our vision here.
Thanks to Bram van der Sanden, Kuan-Hsun Chen, Mitra Nasri, Geoffrey Nelissen, and Twan Basten for their help preparing the pitch.
Today, Ali presented our Real-time Systems article “Uneven Memory Regulation for Scheduling IMA Applications on Multi-core Platforms” in the Journal-to-conference (J2C) session at ECRTS.
This article addresses the problem of resource sharing in mixed-criticality systems through temporal isolation by extending the state-of-the-art Single-Core Equivalence (SCE) framework in three ways: 1) we extend the theoretical toolkit for the SCE framework by considering EDF and server-based scheduling, instead of partitioned fixed-priority scheduling, 2) we support uneven memory access budgets on a per-server basis, rather than just on a per-core basis, and 3) we formulate an Integer-Linear Programming Model (ILP) guaranteed to find a feasible mapping of a given set of servers to processors, including their execution time and memory access budgets, if such a mapping exists. Our experiments with synthetic task sets confirm that considerable improvement in schedulability can result from the use of per-server memory access budgets under the SCE framework.
Overall, I greatly appreciate that key conferences in the real-time community are starting to allow journal articles to be presented. This increases the exposure of these works that are often longer and better edited. It is also helpful for researchers at the institutes where conference publications are not considered a relevant KPI. You can argue the validity of this reasoning in areas of computer science where conferences are highly competitive with 20-30% acceptance rates, but it is reality for some researchers. An interesting thing with the MODELS conference is that they collaborate with the SOSYM journal such that some accepted articles in the journal gets a full slot at the conference. This is a nice way to highlight good articles and to appreciate the work done by both authors and reviewers.
We are pleased to announce that our paper “Worst-case Stall Analysis for Multicore Architectures with Two Memory Controllers” has been accepted at ECRTS 2018. This paper represents another successful collaboration with my former colleagues from CISTER.
The paper addresses the problem that increasing bandwidth requirements have resulted in platform architectures with multiple memory controllers, for which existing analyses to compute worst-case memory stall time are not safe. This work presents a new worst-case memory stall analysis for a memory-regulated multi-core architecture with two memory controllers. This stall analysis can be integrated into the schedulability analysis of systems under fixed-priority partitioned scheduling. Five heuristics for assigning tasks and memory budgets to cores in a stall-cognisant manner are also proposed. We experimentally quantify the cost in terms of extra stall for letting all cores benefit from the memory space offered by both controllers, and also evaluate the five heuristics for different system characteristics.
Our paper “Mixed-criticality Scheduling with Dynamic Redistribution of Shared Cache” has been accepted at ECRTS 2017, marking the end of yet another succesful collaboration with my former colleagues at CISTER. The paper proposes an extension of Vestal’s model for mixed-criticality multi-core systems that 1) accounts for the per-task partitioning of the last-level cache, and 2) supports dynamic reassignment of cache portions initially reserved for lower-criticality tasks to the higher-criticality tasks when switching to high-criticality mode. A schedulability analysis based on partitioned EDF is presented that is aware of the cache resources assigned to each task and leverages the dynamic reconfiguration to improve schedulability. We also propose heuristics for partitioning the cache in low- and high-criticality mode. Experimental result indicate tangible improvements in schedulability compared to a baseline cache-aware arrangement where there is no redistribution of cache resources from low- to high-criticality tasks in the event of a mode change.
I am pleased to announce that our paper “Cache-Persistence-Aware Response-Time Analysis for Fixed-Priority Preemptive Systems” got an Outstanding Paper Award at the Euromicro Conference on Real-Time Systems (ECRTS) in Toulouse. We are glad that the work was well-received and hope that the community will enjoy reading the paper.
Two papers have been accepted for presentation at the 28th Euromicro Conference on Real-Time Systems (ECRTS 2016) in Toulouse, France. The first paper is entitled “Cache-Persistence-Aware Response-Time Analysis for Fixed-Priority Preemptive Systems” as is a collaboration with Syed Aftab Rashid, Geoffrey Nelissen, and Eduardo Tovar from CISTER and Damien Hardy and Isabelle Puaut from University of Rennes. This paper presents a WCRT analysis for single-core fixed-priority preemptive systems that exploits persistent cache blocks that are known to be in the cache to reduce WCRT.
The title of the second paper is “Contention-Free Execution of Automotive Applications on a Clustered Many-Core Platform” that was written together with Borislav Nikolic and Vincent Nelis from CISTER, Matthias Becker and Thomas Nolte from MRTC, and Dakshina Dasari from Bosch. This work presents a contention-free execution framework for automotive applications on many-core platforms, which combines privatization of memory banks together with defined access phases to shared memory resources. An Integer Linear Programming (ILP) formulation is presented to find the optimal time-triggered schedule for execution as well as for accesses to shared memory. Additionally, a heuristic solution is presented that generates the schedule in a fraction of the time required by the ILP.
Today, we congratulate Yonghui Li on his first accepted journal article. The article is entitled “Architecture and Analysis of a Dynamically-Scheduled Real-Time Memory Controller” and has been accepted in the Real-Time Systems journal. The work extends his paper “Dynamic Command Scheduling for Real-Time Memory Controllers” that was presented at ECRTS 2014. The previous conference paper introduced a back-end architecture and scheduling algorithm for a dynamically scheduled SDRAM controller supporting variable transaction sizes and different degrees of bank interleaving. The properties of the back-end was extensively analyzed and worst-case execution times (WCET) of scheduled transactions was derived using two different methods with varying complexity and accuracy.
The newly accepted article extends this work by proposing a corresponding memory controller front-end, along with a complete response time analysis for memory transactions of variable sizes. A key feature of the front-end is that it features a non-work-conserving TDM arbiter, which provides static information about the order in which transactions of different sizes are scheduled, allowing the response time analysis to leverage the flexible WCET analysis of the back-end to provide tighter bounds. In addition, it is shown in which order memory clients with different request sizes should be served to minimize the total response time. The results demonstrate that dynamic command scheduling significantly outperforms our semi-static (pattern-based) approach in the average case, while it performs equally well or better in the worst-case with only a few exceptions.
The Memory Team is proud to release another open-source tool to the community. This tool is called RTMemController and contains a mathematical formalization of the dynamic command scheduler introduced in Yonghui Li’s paper Dynamic Command Scheduling for Real-Time Memory Controllers that will be presented at ECRTS. The tool is capable of determining worst-case and average-case execution times of memory transactions of different transaction sizes and with varying degrees of bank interleaving.
An important driver for releasing this tool is to promote transparency and fair comparisons between work in the field. Longer term development plans for the tool may involve adding support for a memory controller front-end with different transaction schedulers, adding support for more memory generations (currently DDR3 is supported), and making the output compatible with DRAMPower to enable chaining the tools.
The official website of RTMemController is found here. Also check out the paper that describes the scheduling algorithm and its formalization.
Today, we congratulate Yonghui Li on an accepted paper at ECRTS. The paper is entitled Dynamic Command Scheduling for Real-Time Memory Controllers and presents both an architecture and analysis for a dynamically scheduled SDRAM controller supporting different transaction sizes and memory map configurations. This is Yonghui’s first accepted paper and we are proud to see that it got very good reviews from one of the most competitive conferences in the field. Now the work begins on preparing a camera-ready version and making the scheduling algorithm publicly available for comparisons in community.