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@PHDTHESIS{Psychou:711539,
author = {Psychou, Georgia},
othercontributors = {Noll, Tobias G. and Blume, Holger and Gemmeke, Tobias},
title = {{S}tochastic {A}pproaches for {S}peeding-{U}p the
{A}nalysis of the {P}ropagation of {H}ardware-{I}nduced
{E}rrors and {C}haracterization of {S}ystem-{L}evel
{M}itigation {S}chemes in {D}igital {C}ommunication
{S}ystems},
school = {Rheinisch-Westfälische Technische Hochschule Aachen},
type = {Dissertation},
address = {Aachen},
reportid = {RWTH-2017-10881},
pages = {1 Online-Ressource (xiv, 123 Seiten) : Illustrationen},
year = {2017},
note = {Veröffentlicht auf dem Publikationsserver der RWTH Aachen
University 2018; Dissertation, Rheinisch-Westfälische
Technische Hochschule Aachen, 2017},
abstract = {Today's nano-scale technology nodes are bringing
reliability concerns back to the center stage of digital
system design because of issues, like process variability,
noise effects, radiation particles, as well as increasing
variability at run time. Alleviations of these effects can
become potentially very costly and the benefits of
technology scaling can be significantly reduced or even
lost. In order to build more robust digital systems,
initially, their behavior in the presence of
hardware-induced bit errors must be analyzed. In many
systems, certain types of errors can be tolerated. These
cases can be revealed through such an analysis. Overhead can
be avoided and remedy measures can be applied only when
needed. Communication systems are an interesting domain for
such explorations: First, they have high societal relevance
due to their ubiquity. Second, they can potentially tolerate
hardware-induced errors due to their built-in redundancy
present to cope with channel noise. This work focuses on
analyzing the impact of such errors on the behavior of
communication systems. Typically, error propagation studies
are performed through time-consuming fault injection
campaigns. These approaches do not scale well with growing
system sizes. Stochastic experiments allow a more
time-efficient approach. On top, breaking down the system
into subsystems and propagating error statistics through
each of these subsystems further improves the speed-up and
flexibility in the reliability evaluation of complex
systems. As an initial step in this thesis, statistical
moments are propagated through the signal flows of
Linear-Time-Invariant (LTI) blocks. Such a scheme, although
fast, can only be applied in the case that the signal lacks
autocorrelation. However, autocorrelation can be introduced
in the signal due to various reasons, like by signal
processing blocks. In that case, other approaches are
available to reduce the computational cost of the necessary
(repetitive) experiments, like the Principal Component
Analysis (PCA). Benefits of such a technique depend on
several parameters and, therefore, a more broadly usable
technique is required. To address this need, a framework is
proposed that exploits the repetitive nature of fault
injection experiments for speed-up in LTI blocks. Two cases
are distinguished: One, in which all operators of the LTI
block act in a linear time-invariant way, and one, in which
non-linear operations due to finite wordlengths are present.
To complement the subject matter, the broad range of
hardware-based mitigation techniques at the higher system
level are explored and characterized. In this way, the main
properties of each mitigation category are identified and,
therefore, suitable choices can be made according to the
application needs.},
cin = {611110},
ddc = {621.3},
cid = {$I:(DE-82)611110_20170101$},
typ = {PUB:(DE-HGF)11},
doi = {10.18154/RWTH-2017-10881},
url = {https://publications.rwth-aachen.de/record/711539},
}
Gast ::