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authormjkwiatkowski <mati.rewa@gmail.com>2026-06-23 13:29:28 +0200
committermjkwiatkowski <mati.rewa@gmail.com>2026-06-23 13:29:28 +0200
commitaff0ce83458daebf0bdf783ca5144225a72b328a (patch)
tree36e6e14bcd0b8cffce3db09dafe65f4f23130592
parentf062b0967b126c80af7968aebd7db3b0e5779f7a (diff)
feat: changed experiment I to be something completely different
-rw-r--r--build/main.aux1
-rw-r--r--build/main.fdb_latexmk22
-rw-r--r--build/main.fls23
-rw-r--r--build/main.log120
-rw-r--r--build/main.pdfbin5821815 -> 5600657 bytes
-rw-r--r--build/main.synctex.gzbin56767 -> 58246 bytes
-rw-r--r--citations/Replication_vs_Reproduction.pdfbin0 -> 44501 bytes
-rw-r--r--images/23_Jun_2026_102028.pdfbin0 -> 12607 bytes
-rw-r--r--indent.log2
-rw-r--r--main.tex62
-rw-r--r--style/style.tex2
11 files changed, 136 insertions, 96 deletions
diff --git a/build/main.aux b/build/main.aux
index 177765d..df962c6 100644
--- a/build/main.aux
+++ b/build/main.aux
@@ -30,7 +30,6 @@
\@writefile{nav}{\headcommand {\beamer@framepages {6}{6}}}
\@writefile{nav}{\headcommand {\slideentry {0}{0}{7}{7/7}{}{0}}}
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diff --git a/build/main.fdb_latexmk b/build/main.fdb_latexmk
index 999582c..d40cb78 100644
--- a/build/main.fdb_latexmk
+++ b/build/main.fdb_latexmk
@@ -1,13 +1,13 @@
# Fdb version 4
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(generated)
"build/main.bbl"
"build/main.blg"
(rewritten before read)
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index 64330c4..9f3689a 100644
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diff --git a/build/main.log b/build/main.log
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--- a/indent.log
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+ Tue Jun 23 13:28:28 2026
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diff --git a/main.tex b/main.tex
index 051d295..5d3dfec 100644
--- a/main.tex
+++ b/main.tex
@@ -73,8 +73,10 @@
\begin{tcolorbox}[title=A holistic DCDT system model]
We propose a generic model of datacenter digital twinning that can be mapped to each system from \textbf{Table 1.1}. To answer \textbf{RQ2}, we design a ref. arch. for \emph{Operations Model}.
+ We introduce the \emph{Digital Thread}: a bridge between software and reality.
\end{tcolorbox}
\begin{center}
+ \vspace{-0.1cm}
\includegraphics[width=0.8\textwidth]{images/system_model2.pdf}
\end{center}
% The reason why the cooling system is in the graph is because of the fact that 40\% of total energy consumed in DCs comes from cooling~\cite{DBLP:conf/noms/ZhangZLZWC22}.
@@ -103,48 +105,66 @@
\end{center}
\vspace{-0.2cm}
\tiny
- \textbf{Figure 1.4:} The predictive datacenter digital twin architecture. \end{minipage}
+ \textbf{Figure 1.4:} The predictive datacenter digital twin reference 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}
-
+% You should skip \hfill completely or in favour of \hspace very minimally.
\begin{frame}\frametitle{\textbf{RQ3}: Experimental Setup}
+ % The software stack of \emph{Sunfish} includes state-of-the-art software.
+ %The time-series data flows first to the \texttt{Grafana} dashboard, \texttt{PostgreSQL} database and \texttt{Redis} cache, as advised in~\cite{DBLP:conf/sc/TaheriBPRHDEWPM24}.
+
\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.
+ \begin{tcolorbox}[title=Setup Recipe]
+ \scriptsize
+ \textbf{Step 1.} Ensure Redis and PostgreSQL servers are up and alive.\newline
+
+ \textbf{Step 2.} Run a Confluent Kafka setup: Kafka Connect, Schema Registry and a Kafka server.\newline
+
+ \textbf{Step 3.} Start the Python HTTP Server, and the Python Redis Monitor.\newline
+
+ \textbf{Step 4.} Run the (modified) OpenDC (physical twin) with example experiment.\newline
+
+ \textbf{Step 5.} \emph{Sunfish} will automatically start a second OpenDC instance, and start the data analysis.
+ \end{tcolorbox}
+ \vspace{0.5cm}
\end{minipage}
- \hfill
+ \hspace{0.35cm}
\begin{minipage}[b]{0.45\linewidth}
+ \vspace{-0.2cm}
\begin{center}
- \includegraphics[width=0.7\linewidth]{images/scrs.jpg}
+ \includegraphics[width=1.2\linewidth]{images/predictive_analyticsv2.pdf}
\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}.
+ \vspace{-0.4cm}
+ \textbf{Figure 1.5:} We can't just go and test digital twins on large systems as large systems often aren't at hand.
+ Answering \textbf{RQ3} we provide a novel way to evaluate datacenter digital twins through discrete-event simulation instead.
\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).
- Insights from predictive digital twinning yield noticeable performance difference.
+ % You have some model, and this can be based on multiple traces.
+ %Get insight from CINECA --> you get a probability of certain hosts failing.
+ % Anomaly detection --> CINECA, how good their detection is?
+ %If you incorporate that? If you can make the case that because of our new digital twin we can incorporate such models, anomaly/failure detection, from CINECA.
+ %If we had that in, we can reach these kinds of gains.
+ % @Mateusz there is really not a possibility to incorporate CINECA's models, so to address Dante's feedback, I created this experiment.
+
+ \begin{tcolorbox}[title=Failure Detection: Main Finding I]
+ On average, \emph{Sunfish} can detect 14.5\% of unexpected failures in the physical twin.
+ We show, that digital twinning \emph{can} be used for failure detection.
+
\end{tcolorbox}
\begin{minipage}[b]{0.45\linewidth}
\begin{center}
- \includegraphics[width=1.1\textwidth]{images/18_Jun_2026_201008.pdf}
+ \includegraphics[width=1.1\textwidth]{images/23_Jun_2026_102028.pdf}
\end{center}
\vspace{-0.3cm}
\tiny
- \textbf{Figure 1.5:} Experiment 1 -- on the \emph{x}-axis are different community failure traces.
- On the \emph{y}-axis is the mean number of times a task has failed, during the entire workload.
- Vertical bars is standard deviation, measured over 5 repetitions.
+ \textbf{Figure 1.5:} Experiment 1 Setup: The Digital Twin estimates the failures based on the Normal Distribution \emph{N\textasciitilde($\mu$,$\sigma$)} with $\mu = 1.5$ and $\sigma = 0.5$.
+ ``Real'' OpenDC failures come from a WhatsApp user reports.
\end{minipage}
% Explain what the axis are in the figure caption.
% Talk about the experimental setup in the figure.
@@ -153,7 +173,7 @@
\begin{frame}\frametitle{\textbf{RQ3}: Experimental Results II}
- \begin{tcolorbox}[title=Main Finding II]
+ \begin{tcolorbox}[title=Failure Prediction: Main Finding II]
Here explain what did you find.
\end{tcolorbox}
diff --git a/style/style.tex b/style/style.tex
index c79e56f..36caa33 100644
--- a/style/style.tex
+++ b/style/style.tex
@@ -1,6 +1,6 @@
\usetheme{Rochester}
\usepackage[dvipsnames]{xcolor}
-\usepackage{helvet, textpos, stix, caption, booktabs, array, lipsum, fontawesome5, circledsteps, url, inconsolata}
+\usepackage{helvet, textpos, stix, caption, booktabs, array, lipsum, fontawesome5, circledsteps, url, inconsolata, amsmath, amssymb}
\newcommand\myCircled[2][]{\ifmmode
\Circled[fill color=black,inner color=white,#1]{\mathsf{#2}}