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.
Anna Minaeva had an article entitled “Time-Triggered Co-Scheduling of Computation and Communication with Jitter Requirements” accepted in IEEE Transactions on Computers. The article considers the problem of efficiently co-scheduling task execution and communication in multi-core automotive platforms. Most existing works typically deal with zero-jitter scheduling, which results in lower resource utilization, but has lower memory requirements. In contrast, this article focuses on jitter-constrained scheduling that puts constraints on the tasks jitter, increasing schedulability over zero-jitter scheduling.
The contributions of this article are: 1) Integer Linear Programming and Satisfiability Modulo Theory model exploiting problem-specific information to reduce the formulations complexity to schedule small applications. 2) A heuristic approach, employing three levels of scheduling scaling to real-world use-cases with 10000 tasks and messages. 3) An experimental evaluation of the proposed approaches on a case-study and on synthetic data sets showing the efficiency of both zero-jitter and jitter-constrained scheduling. It shows that up to 28% higher resource utilization can be achieved by having up to 10 times longer computation time with relaxed jitter requirements.
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.
After successfully defending his dissertation “A Reconfigurable Mixed-Time-Criticality SDRAM Controller“, Sven Goossens earned himself a PhD degree and the right to call himself a doctor. The work proposes a pattern-based SDRAM controller targeting mixed-time-criticality systems, i.e. systems where some memory clients need firm worst-case guarantees on bandwidth and latency, while other clients only care about average-case performance. A new memory controller architecture is designed to address this mix of requirements and it is implemented both as a cycle-accurate SystemC simulation model and as synthesizable RTL code for generating FPGA instances. A unique feature of this memory controller is its conservative open-page policy that leaves rows open in the memory banks as long as possible to exploit locality and boost average-case performance, but closes them just in time to avoid reducing the worst-case performance.
The work also parameterizes the concept of memory patterns by allowing the number of banks and the number of bursts per bank to be chosen when the patterns are generated. This allows patterns with different degrees of bank-level parallelism to be created for six different generations of DRAM for any request size, enabling the user to make a trade-off between worst-case bandwidth, worst-case response time, and power consumption. To generate efficient memory patterns, the work proposes an integer linear programming formulation that provides optimal patterns, as well as a near-optimal heuristic that runs in a fraction of the time. In addition to generating predictable memory patterns that provide bounded bandwidth and execution times, composable read and write patterns can be generated with negligible performance loss. These patterns have equal length and can be used to provide complete temporal isolation between memory clients when combined with a non-work-conserving Time-Division Multiplexing (TDM) arbiter in the front-end. The memory patterns are generated offline at design time, but are programmed at run-time when the memory controller is initialized. Lastly, the proposed controller supports run-time reconfiguration of its TDM arbiter, allowing it to be safely reprogrammed when applications dynamically start and stop at run-time without sacrificing the worst-case guarantees of applications that keep running.
I would like to thank Sven for the five years of hard work. It has been a pleasure to work with such a versatile and independent young researcher who seems to be succesful at whatever he attempts, be it design, analysis, writing papers, or hardware/software implementation in more or lesss any language. He has also been an excellent member of the Memory Team and the larger CompSoC Team, never passing on an opportunity to use his skills to support other members of the team. At the end of January, Sven starts his new career with Intrinsic-ID in Eindhoven. We wish him the best of luck with his new job and hope to stay in touch.
Congratulations to Anna Minaeva for having her article “Scalable and Efficient Configuration of Time-Division Multiplexed Resources” accepted in Journal of Systems and Software. The article is an extension of our conference paper “An Efficient Configuration Methodology for Time-Division Multiplexed Single Resources” that was presented at the Real-Time and Embedded Technology and Applications Symposium (RTAS) earlier this year. The original conference paper addresses the problem of configuring a Time-Division Multiplexing (TDM) arbiter that provides access to a single shared resource, such as a memory, in a way the satisfies the bandwidth and latency requirements of all memory clients. This is achieved using an optimized Integer Linear Programming (ILP) formulation.
The newly accepted article extends the problem scope to consider more complex system with a larger number of memory clients and a longer TDM frame. For large problems, the previous ILP formulation takes unpractically long to solve, which is addressed by using it as a building block in a Branch and Price framework to improve its scalability. This approach decomposes the problem into smaller sub-problems and uses more sophisticated exploration methods to navigate the search-space, enabling the number of clients to be increased by up to a factor of 8 compared to the original ILP formulation.