DeSyRe: on-Demand System Reliability

The DeSyRe project builds on-demand adaptive and reliable Systems-on-Chips (SoCs). As fabrication technology scales down, chips are becoming less reliable, thereby incurring increased power and performance costs for fault tolerance. To make matters worse, power density is becoming a significant limiting factor in SoC design, in general. In the face of such changes in the technological landscape, current solutions for fault tolerance are expected to introduce excessive overheads in future systems. Moreover, attempting to design and manufacture a totally defect and fault-free system, would impact heavily, even prohibitively, the design, manufacturing, and testing costs, as well as the system performance and power consumption. In this context, DeSyRe delivers a new generation of systems that are reliable by design at well-balanced power, performance, and design costs. In our attempt to reduce the overheads of fault-tolerance, only a small fraction of the chip is built to be fault-free. This fault-free part is then employed to manage the remaining fault-prone resources of the SoC. The DeSyRe framework is applied to two medical systems with high safety requirements (measured using the IEC 61508 functional safety standard) and tight power and performance constraints

ATMP: An Adaptive Tolerance-based Mixed-criticality Protocol for Multi-core Systems

© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted ncomponent of this work in other works.The challenge of mixed-criticality scheduling is to keep tasks of higher criticality running in case of resource shortages caused by faults. Traditionally, mixedcriticality scheduling has focused on methods to handle faults where tasks overrun their optimistic worst-case execution time (WCET) estimate. In this paper we present the Adaptive Tolerance based Mixed-criticality Protocol (ATMP), which generalises the concept of mixed-criticality scheduling to handle also faults of other nature, like failure of cores in a multi-core system. ATMP is an adaptation method triggered by resource shortage at runtime. The first step of ATMP is to re-partition the task to the available cores and the second step is to optimise the utility at each core using the tolerance-based real-time computing model (TRTCM). The evaluation shows that the utility optimisation of ATMP can achieve a smoother degradation of service compared to just abandoning tasks

Low-energy standby-sparing for hard real-time systems

Time-redundancy techniques are commonly used in real-time systems to achieve fault tolerance without incurring high energy overhead. However, reliability requirements of hard real-time systems that are used in safety-critical applications are so stringent that time-redundancy techniques are sometimes unable to achieve them. Standby sparing as a hardwareredundancy technique can be used to meet high reliability requirements of safety-critical applications. However, conventional standby-sparing techniques are not suitable for lowenergy hard real-time systems as they either impose considerable energy overheads or are not proper for hard timing constraints. In this paper we provide a technique to use standby sparing for hard real-time systems with limited energy budgets. The principal contribution of this work is an online energymanagement technique which is specifically developed for standby-sparing systems that are used in hard real-time applications. This technique operates at runtime and exploits dynamic slacks to reduce the energy consumption while guaranteeing hard deadlines. We compared the low-energy standby-sparing (LESS) system with a low-energy timeredundancy system (from a previous work). The results show that for relaxed time constraints, the LESS system is more reliable and provides about 26% energy saving as compared to the time-redundancy system. For tight deadlines when the timeredundancy system is not sufficiently reliable (for safety-critical application), the LESS system preserves its reliability but with about 49% more energy consumptio