A paper “Memory Bandwidth Regulation for Multiframe Task Sets” has been accepted at RTCSA 2018. This paper aims to reduce cost of real-time systems where the worst-case execution times of tasks vary from job to job, according to known patterns. This kind of execution behavior can be captured by the multi-frame task model. However, this model is optimistic and unsafe for multi-cores with shared memory controllers, since it ignores memory contention, and existing approaches to stall analysis based on memory regulation are very pessimistic if straight-forwardly applied.
This paper remedies this by adapting existing stall analyses for memory-regulated systems to the multi-frame model. Experimental evaluations with synthetic task sets show up to 85% higher scheduling success ratio for our analysis, compared to the frame-agnostic analysis, enabling higher platform utilization without compromising safety. We also explore implementation aspects, such as how to speed up the analysis and how to trade off accuracy with tractability.
We celebrate the acceptance of our paper “Mixed-criticality Scheduling with Dynamic Memory Bandwidth Regulation” at RTCSA. This paper is the next step in my research collaboration with CISTER on mixed-criticality systems.
The paper aims to safely reduce the cost of mixed-criticality multi-core systems by addressing inefficient usage of memory bandwidth. This is achieved by combining per-core memory access regulation with the well-established Vestal model, which improves on the state-of-the-art in two respects: 1) We allow the memory access budgets of the cores to be dynamically adjusted, when the system undergoes a mode change, reflecting the different needs in each mode, for better schedulability. 2) We devise memory regulation-aware and stall-aware schedulability analysis for such systems, based on AMC-max. By comparison, the state-of-the-art offered no option of dynamic adjustment of core budgets, and only offered regulation-aware schedulability analysis based on AMC-rtb, which is inherently more pessimistic. Finally, 3) we consider different task assignment and bandwidth allocation heuristics, to assess the improvement from the dynamic memory budgets and new analysis. Our results show improvements in schedulability ratio of up to 9.1% over the state-of-the-art.
Today, we congratulate Hazem Ali for having his first paper accepted at RTCSA. The paper is entitled “Critical-Path-First Based Allocation of Real-Time Streaming Applications on 2D Mesh-Type Multi-Cores” and proposes a mapping strategy for streaming applications, represented as acyclic data-flow graphs with throughput requirements, to multi-core architectures under partitioned EDF scheduling. The key idea is to first map tasks on the critical-paths of the application to minimize their execution time and thereby increasing the chance to satisfy the throughput constraint. The camera-ready version is available here.
Hazem Ali is a PhD student at the CISTER-ISEP Research Unit in Porto, supervised by Luis Miguel Pinho and myself, and this paper is a result of my six month visit there last year and the fruitful collaboration it has resulted in afterwards.