From b5111b6e512dc8c27b84ed785c74b4e728a591ee Mon Sep 17 00:00:00 2001 From: mjkwiatkowski Date: Sun, 21 Jun 2026 11:20:14 +0200 Subject: feat: finished 1/2 of Table 1.1 --- main.tex | 16 +++++++++++++--- 1 file changed, 13 insertions(+), 3 deletions(-) (limited to 'main.tex') diff --git a/main.tex b/main.tex index ada40ac..7ce64ac 100644 --- a/main.tex +++ b/main.tex @@ -6,7 +6,7 @@ \begin{frame}\frametitle{Motivation} \begin{tcolorbox}[title=Context] - 21\textsuperscript{st} century datacenters are primarily heterogeneous~\cite{DBLP:conf/date/MilojicicFDR21} and + 21\textsuperscript{st} century datacenters (DC) are mostly heterogeneous~\cite{DBLP:conf/date/MilojicicFDR21} and modern computational needs of AI drive managers to diversify datacenters even more~\cite{DBLP:journals/computer/AthavaleBBMMPS24}. In result datacenters become extremely complex and hard to operate with millions of CPU's, GPU's etc. \end{tcolorbox} @@ -61,6 +61,7 @@ I hope it fits its purpose well. \end{tcolorbox} \input{images/table.tex} + % Research on DTs for datacenters have been separate, siloed efforts focused on either datacenter cooling, network performance, power consumption or visualization efforts. \end{frame} \begin{frame}\frametitle{\textbf{RQ1}: Literature Review II} @@ -73,11 +74,17 @@ \begin{center} \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}. + % It has come to the point where datacenters are being build in the Pan-Arctic region, such as Finland,Russia,Sweden etc. with Iceland leading in number of DCs https://www.datacentermap.com/iceland/ + % The SmarDC digital twin is purely to get more training data for AI models. + % Not really a digital twin per se. \tiny - \textbf{Figure 1.3:} To answer \textbf{RQ1} we designed a generic datacenter digital twin system model based on a comprehensive literature review and findings from \textbf{Table 1.1}. + \textbf{Figure 1.3:} To answer \textbf{RQ1} we designed a generic datacenter digital twin system model based on a comprehensive literature review and findings from \textbf{Table 1.1}. The \emph{Infrastructure Model} simulates the structure of the DC and the \emph{Operations model} simulates the behaviour of the DC. % Consider splitting the figure into 2 a.k.a. top and bottom. + % By the AIAA definition, the DT mimicks the structure and behaviour. % Data Lake -> Data Storage + % Use cases of DT's found by Brewer et al.: augmented reality, forensic analysis and diagnostics, predictive modelling, failure detection, operational optimization, ``what-if''' scenarios and virtual prototyping. \end{frame} \begin{frame}\frametitle{\textbf{RQ2}: Reference Architecture} @@ -87,9 +94,12 @@ \end{center} \vspace{-0.2cm} \tiny - \textbf{Figure 1.4:} The predictive datacenter digital twin architecture. + \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} \hfill + % 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 \begin{minipage}[b]{0.42\linewidth} \begin{tcolorbox}[title=Functional Req.] -- cgit v1.2.3