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Fault-Tolerant Computing with Heterogeneous Hardening Modes

Authors: Florian Kriebel; Faiq Khalid; Bharath Srinivas Prabakaran; Semeen Rehman; Muhammad Shafique;

Fault-Tolerant Computing with Heterogeneous Hardening Modes

Abstract

AbstractFault-tolerance using (full-scale) redundancy-based techniques has been employed to detect and correct reliability errors (i.e., soft errors), but they pose significant area and power overhead. On the other hand, due to the masking and the error tolerance properties at different system layers and of different applications, respectively, reliable heterogeneous architectures have been emerged as an attractive design choice for power-efficient dependable computing platforms. This chapter discusses the building blocks of such computing systems, based on both embedded and superscalar processors, with different reliability (fault-tolerant) modes at the architecture layer to memories like caches, for heterogeneous in-order and out-of-order processors. We provide a comprehensive reliability, i.e., soft error, vulnerability analysis of different components in in-order and out-of-order processors, e.g., caches. We also discuss different methodologies to improve the performance and power of such a system by analyzing these vulnerabilities. Moreover, we show how such heterogeneous hardware-level hardening modes can further be complemented by software-level techniques that can be realized using a reliability-driven compiler (as introduced in Chapter “Dependable Software Generation and Execution on Embedded Systems”).

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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