Update on Overleaf.

fault_injection_async25.tex

@@ -93,10 +93,11 @@ While commercial EDA tools offer convenient access to the current state of the i
 It is generally agreed that this EDA focus on mainstream synchronous design is one key reason for the hesitant adoption of asynchronous design styles.
 This lack of EDA support has somewhat been mitigated by the publication of the open source ACT toolchain by the Yale AVLSI group \cite{manoharOpenSourceDesign}. However, the local compute currently offered by ACT often does not suffice for tasks that are more laborious. 
 
-Especially for those tasks that lend themselves nicely to a high degree of parallelization, cluster computing offers high potential for speed improvements. For this reason, we have augmented ACT with a tool which does just that - while offering a simple \acs{api} to vastly extend its functionality. Our goal was to create a framework to build on, and we here present a real world use-case to demonstrate this capability.
+Especially for those tasks that lend themselves nicely to a high degree of parallelization, cluster computing offers high potential for speed improvements. 
+For this reason, we have augmented ACT with the tool \texttt{action} which does just that - while offering a simple \acs{api} to vastly extend its functionality. Our goal was to create a framework to build on, and we here present a real world use-case to demonstrate this capability.
 
 Specifically, we consider the problem of fault-tolerance assessment through fault injection.
-With applications extending into harsh environments like space on the one hand, and feature sizes in the nanometer regime on the other hand, high-energy particles are getting more likely to cause erroneous behavior of transistors. Consequently fault tolerance is an increasingly desired property of digital circuits, be they synchronous or asynchronous. To this end, studying the behavior of selected target circuits under artificially injected faults is a vital means. Beyond a mere quantitative estimation of the error probability of a given design in a given environment, there are also more qualitative, conceptual questions that fault injection can answer. For instance, one may try to understand whether a mechanism like the temporal masking provided by flip flops in synchronous designs also exists in asynchronous designs, established by the communication protocol, e.g., and if so, on which parameters it depends.
+With applications extending into harsh environments like space on the one hand, and feature sizes in the nanometer regime on the other hand, high-energy particles are getting more likely to cause erroneous behavior of transistors. Consequently fault tolerance is an increasingly desired property of digital circuits, be they synchronous or asynchronous. To this end, studying the behavior of selected target circuits under artificially injected faults is a vital means. Beyond a mere quantitative estimation of the error probability of a given design in a given environment, there are also more qualitative, conceptual questions that fault injection can answer. For instance, one may try to understand whether a mechanism like the temporal masking provided by flip flops in synchronous designs also exists in asynchronous designs, established by the communication protocol, and if so, on which parameters it depends.
 
 In any case, to produce meaningful results such fault-injection experiments need to cover an ample parameter space, spanned by time and location of fault injection, fault parameters, target circuit properties and condition, just to name a few. In the literature, multiple attempts have been made to create tools for leveraging this ambitious task, and they have produced valuable results (see \cite{behalExplainingFaultSensitivity2021} for just one example). Yet, we feel that the chance to integrate such a fault-injection tool into a design environment, as well as the availability of cluster computing offers the opportunity for further improvement.
 
@@ -107,7 +108,7 @@ In any case, to produce meaningful results such fault-injection experiments need
 
 %But what is often much more important than knowing \emph{if} a design can fail under certain (extreme) circumstances, is \emph{how} exactly these failure modes play out. Certain use-cases might call for or even enforce safety in form of known failure modes on critical systems. While multiple attempts have been made to create tooling for exploration of fault-space in the past \cite{behalExplainingFaultSensitivity2021}, as of yet these tools have several shortcomings, which we feel need to be addressed.
 
-With this in mind, we will, after visiting the related work in Section~\ref{sec:relatedwork}present our novel framework along with its integration into ACT in Section~\ref{sec:tooling}. We will also be concerned with its use for fault injection experiments, before delving more into details of modeling and experiment configuration in Section~\ref{sec:system_model}. Sections~\ref{sec:experiment_setup} and \ref{sec:results} will then be devoted to the setup and the results of the experiment, respectively. We conclude the paper in Section~\ref{sec:conclusion}.
+With this in mind, we will, after visiting the related work in Section~\ref{sec:relatedwork}, present our novel framework along with its integration into ACT in Section~\ref{sec:tooling}. We will then show its use for fault injection experiments, before delving more into details of modeling and experiment configuration in Section~\ref{sec:system_model}. Sections~\ref{sec:experiment_setup} and \ref{sec:results} will then be devoted to the setup and the results of the experiment, respectively. We conclude the paper in Section~\ref{sec:conclusion}.
 
 \section{Related Work}
 \label{sec:relatedwork}