Changeset 8040286 for doc/theses/thierry_delisle_PhD/thesis/text/core.tex

Timestamp:

Aug 5, 2022, 4:18:02 PM (3 years ago)

Author:

Thierry Delisle <tdelisle@…>

Branches:

ADT, ast-experimental, master, pthread-emulation

Children:

62c5a55

Parents:

511a9368

Message:

Filled in several citations and did some of the todos

File:

• doc/theses/thierry_delisle_PhD/thesis/text/core.tex (modified) (4 diffs)

doc/theses/thierry_delisle_PhD/thesis/text/core.tex

@@ -15 +15 @@
 For threading, a simple and common execution mental-model is the ``Ideal multi-tasking CPU'' :
 
-\begin{displayquote}[Linux CFS\cit{https://www.kernel.org/doc/Documentation/scheduler/sched-design-CFS.txt}]
+\begin{displayquote}[Linux CFS\cite{MAN:linux/cfs}]
         {[The]} ``Ideal multi-tasking CPU'' is a (non-existent  :-)) CPU that has 100\% physical power and which can run each task at precise equal speed, in parallel, each at [an equal fraction of the] speed.  For example: if there are 2 tasks running, then it runs each at 50\% physical power --- i.e., actually in parallel.
         \label{q:LinuxCFS}
@@ -183 +183 @@
 This suggests to the following approach:
 
-\subsection{Dynamic Entropy}\cit{https://xkcd.com/2318/}
+\subsection{Dynamic Entropy}\cite{xkcd:dynamicentropy}
 The Relaxed-FIFO approach can be made to handle the case of mostly empty subqueues by tweaking the \glsxtrlong{prng}.
 The \glsxtrshort{prng} state can be seen as containing a list of all the future subqueues that will be accessed.
 While this concept is not particularly useful on its own, the consequence is that if the \glsxtrshort{prng} algorithm can be run \emph{backwards}, then the state also contains a list of all the subqueues that were accessed.
-Luckily, bidirectional \glsxtrshort{prng} algorithms do exist, \eg some Linear Congruential Generators\cit{https://en.wikipedia.org/wiki/Linear\_congruential\_generator} support running the algorithm backwards while offering good quality and performance.
+Luckily, bidirectional \glsxtrshort{prng} algorithms do exist, \eg some Linear Congruential Generators\cite{wiki:lcg} support running the algorithm backwards while offering good quality and performance.
 This particular \glsxtrshort{prng} can be used as follows:
 \begin{itemize}
@@ -220 +220 @@
         \input{base.pstex_t}
         \caption[Base \CFA design]{Base \CFA design \smallskip\newline A pool of subqueues offers the sharding, two per \glspl{proc}.
-        Each \gls{proc} can access all of the subqueues. 
+        Each \gls{proc} can access all of the subqueues.
         Each \at is timestamped when enqueued.}
         \label{fig:base}
@@ -245 +245 @@
 \end{figure}
 
-A simple solution to this problem is to use an exponential moving average\cit{https://en.wikipedia.org/wiki/Moving\_average\#Exponential\_moving\_average} (MA) instead of a raw timestamps, shown in Figure~\ref{fig:base-ma}.
+A simple solution to this problem is to use an exponential moving average\cite{wiki:ma} (MA) instead of a raw timestamps, shown in Figure~\ref{fig:base-ma}.
 Note, this is more complex because the \at at the head of a subqueue is still waiting, so its wait time has not ended.
 Therefore, the exponential moving average is actually an exponential moving average of how long each dequeued \at has waited.