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authormjkwiatkowski <mati.rewa@gmail.com>2026-06-22 08:54:23 +0200
committermjkwiatkowski <mati.rewa@gmail.com>2026-06-22 08:54:23 +0200
commitf062b0967b126c80af7968aebd7db3b0e5779f7a (patch)
treee79f5c6d1e280aceba0e59492390369a76cef500 /main.tex
parent862effeee0e9ccdc4f94354a0f20df9a99c8823e (diff)
feat: added an additional slide for experimental setup
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1 files changed, 23 insertions, 3 deletions
diff --git a/main.tex b/main.tex
index b5e76fe..051d295 100644
--- a/main.tex
+++ b/main.tex
@@ -103,14 +103,34 @@
\end{center}
\vspace{-0.2cm}
\tiny
- \textbf{Figure 1.4:} The predictive datacenter digital twin architecture. The time-series data flows initially to the \texttt{Kibana} dashboard, \texttt{PostgreSQL} database and \texttt{Redis} cache, as suggested in~\cite{DBLP:conf/sc/TaheriBPRHDEWPM24}.
- \end{minipage}
+ \textbf{Figure 1.4:} The predictive datacenter digital twin architecture. \end{minipage}
% We decided to use discrete-event simulation, as opposed to computational fluid dynamics because of the high overheads of development time needed for CFD.
% CFD simply takes too long to run, making it unfeasible for real-time analytics and simulation.
% Citing ExaDigit: [CFD] they are also more computationally expensive, generally making real-time operation unfeasible.
% Consider adding this minipage directly to the ``draw.io'' diagram
\end{frame}
+\begin{frame}\frametitle{\textbf{RQ3}: Experimental Setup}
+ \begin{minipage}[b]{0.45\linewidth}
+ \begin{center}
+ \includegraphics[width=1.2\linewidth]{images/predictive_analyticsv2.pdf}
+ \end{center}
+ \vspace{-0.3cm}
+ \tiny
+ \textbf{Figure 1.5:} Evaluating DCDTs is difficult. To answer \textbf{RQ3} we provide a novel way to evaluate datacenter digital twins through discrete-event simulation.
+ \end{minipage}
+ \hfill
+ \begin{minipage}[b]{0.45\linewidth}
+ \begin{center}
+ \includegraphics[width=0.7\linewidth]{images/scrs.jpg}
+ \end{center}
+ \vspace{-0.2cm}
+ \tiny
+ \textbf{Figure 1.6:} The software stack used to implement \emph{Sunfish}.
+ The time-series data flows initially to the \texttt{Grafana} dashboard, \texttt{PostgreSQL} database and \texttt{Redis} cache, as suggested in~\cite{DBLP:conf/sc/TaheriBPRHDEWPM24}.
+ \end{minipage}
+\end{frame}
+
\begin{frame}\frametitle{\textbf{RQ3}: Experimental Results I}
\begin{tcolorbox}[title=Main Finding I]
On average, \emph{Sunfish} achieves 12.17\% less failures per task than baseline (OpenDC).
@@ -162,7 +182,7 @@
\end{frame}
-\setcounter{framenumber}{3}
+\setcounter{framenumber}{4}
\setbeamertemplate{footline}[page number]{
% Unfortunately this must remain here.