Designing soft errors resilient systems is a complex engineering task, which nowadays follows a cross-layer approach. It requires a careful planning for different fault-tolerance mechanisms at different system's layers: starting from the technology up to the software domain. While these design decisions have a positive effect on the reliability of the system, they usually have a detrimental effect on its size, power consumption, performance and cost. Design space exploration for cross-layer reliability is therefore a multi-objective search problem in which reliability must be traded-off with other design dimensions. This paper proposes a cross-layer multi-objective design space exploration algorithm developed to help designers when building soft error resilient electronic systems. The algorithm exploits a system-level Bayesian reliability estimation model to analyze the effect of different cross-layer combinations of protection mechanisms on the reliability of the full system. A new heuristic based on the extremal optimization theory is used to efficiently explore the design space. An extended set of simulations shows the capability of this framework when applied both to benchmark applications and realistic systems, providing optimized systems that outperform those obtained by applying state-of-the-art cross-layer reliability techniques.

ReDO: Cross-Layer Multi-Objective Design-Exploration Framework for Efficient Soft Error Resilient Systems / Savino, Alessandro; Vallero, Alessandro; Di Carlo, Stefano. - In: IEEE TRANSACTIONS ON COMPUTERS. - ISSN 0018-9340. - STAMPA. - 67:10(2018), pp. 1462-1477. [10.1109/TC.2018.2818735]

ReDO: Cross-Layer Multi-Objective Design-Exploration Framework for Efficient Soft Error Resilient Systems

Savino, Alessandro;Vallero, Alessandro;Di Carlo, Stefano
2018

Abstract

Designing soft errors resilient systems is a complex engineering task, which nowadays follows a cross-layer approach. It requires a careful planning for different fault-tolerance mechanisms at different system's layers: starting from the technology up to the software domain. While these design decisions have a positive effect on the reliability of the system, they usually have a detrimental effect on its size, power consumption, performance and cost. Design space exploration for cross-layer reliability is therefore a multi-objective search problem in which reliability must be traded-off with other design dimensions. This paper proposes a cross-layer multi-objective design space exploration algorithm developed to help designers when building soft error resilient electronic systems. The algorithm exploits a system-level Bayesian reliability estimation model to analyze the effect of different cross-layer combinations of protection mechanisms on the reliability of the full system. A new heuristic based on the extremal optimization theory is used to efficiently explore the design space. An extended set of simulations shows the capability of this framework when applied both to benchmark applications and realistic systems, providing optimized systems that outperform those obtained by applying state-of-the-art cross-layer reliability techniques.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2704265
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