| 1 | \documentclass[english,aspectratio=169,svgnames,notes=hide,14pt,xcolor={dvipsnames}]{beamer} | 
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| 2 | \usepackage{graphicx} | 
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| 3 | \usepackage{epic,eepic} | 
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| 4 | \usepackage{presentationstyle} | 
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| 5 |  | 
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| 6 | \title{The \CFA Scheduler} | 
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| 7 | \subtitle{PhD Comprehensive II Research Proposal} | 
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| 8 | \author{Thierry Delisle} | 
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| 9 | % \affil[1]{School of Computer Science, University of Waterloo} | 
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| 10 | % \affil[ ]{\textit {tdelisle@uwaterloo.ca}} | 
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| 11 |  | 
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| 12 | \begin{document} | 
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| 13 | %============================== | 
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| 14 | \miniframesoff | 
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| 15 | \begin{frame}[noframenumbering,plain] | 
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| 16 | \titlepage | 
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| 17 | \end{frame} | 
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| 18 | %============================== | 
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| 19 | \section{Introduction} | 
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| 20 | %------------------------------ | 
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| 21 | \begin{frame}[noframenumbering] | 
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| 22 | \tableofcontents | 
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| 23 | \end{frame} | 
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| 24 | \miniframeson | 
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| 25 | %============================== | 
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| 26 | \AtBeginSection[]{ | 
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| 27 | \miniframesoff | 
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| 28 | \begin{frame} | 
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| 29 | \vfill | 
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| 30 | \centering | 
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| 31 | \begin{beamercolorbox}[sep=8pt,center,shadow=false,rounded=false]{title} | 
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| 32 | \usebeamerfont{title}\insertsectionhead\par% | 
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| 33 | \end{beamercolorbox} | 
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| 34 | \vfill | 
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| 35 | \end{frame} | 
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| 36 | \miniframeson | 
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| 37 | } | 
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| 38 | \section{Concurrency and \CFA} | 
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| 39 | \begin{frame}{Project} | 
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| 40 | \begin{center} | 
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| 41 | {\large Produce a scheduler for \CFA that is simple for programmers to understand and offers good general performance.} | 
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| 42 | \end{center} | 
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| 43 | \end{frame} | 
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| 44 | %------------------------------ | 
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| 45 | \begin{frame}{\CFA} | 
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| 46 | \CFA is a modern extension of C. | 
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| 47 | It adds to C : overloading, constructors/destructors, polymorphism, and much more. | 
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| 48 |  | 
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| 49 | ~\newline | 
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| 50 | For this project, the relevant aspects are: | 
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| 51 | \begin{itemize} | 
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| 52 | \item Fast and safe system language. | 
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| 53 | \item Threading. | 
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| 54 | \item Manual memory management. | 
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| 55 | \end{itemize} | 
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| 56 |  | 
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| 57 | \end{frame} | 
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| 58 | %------------------------------ | 
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| 59 | \begin{frame}{Concurrency in \CFA} | 
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| 60 | User Level Threading | 
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| 61 | \begin{itemize} | 
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| 62 | \item M:N threading. | 
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| 63 | \item User Level Context Switching causes kernel-threads to run a different user-thread. | 
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| 64 | \end{itemize} | 
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| 65 | ~\newline | 
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| 66 | Threads organized in clusters: | 
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| 67 | \begin{itemize} | 
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| 68 | \item Clusters have their own kernel threads. | 
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| 69 | \item Threads in a cluster are on run on the kernel threads of that cluster. | 
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| 70 | \end{itemize} | 
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| 71 | \end{frame} | 
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| 72 | %------------------------------ | 
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| 73 | \begin{frame}{Concurrency in \CFA} | 
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| 74 | \begin{table} | 
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| 75 | {\resizebox{1\textwidth}{!}{\input{system.dark.pstex_t}}} | 
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| 76 | \end{table} | 
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| 77 | \end{frame} | 
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| 78 | %------------------------------ | 
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| 79 | \begin{frame}{Scheduling goal for \CFA} | 
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| 80 | {\large | 
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| 81 | \begin{center} | 
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| 82 | The \CFA scheduler should be \textit{viable} for any workload. | 
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| 83 | \end{center} | 
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| 84 | } | 
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| 85 | ~\newline | 
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| 86 | This implies: | 
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| 87 | \begin{enumerate} | 
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| 88 | \item Producing a scheduler with sufficient fairness guarantees. | 
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| 89 | \item Handling kernel-threads running out of work. | 
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| 90 | \item Handling blocking I/O operations. | 
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| 91 | \end{enumerate} | 
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| 92 | \end{frame} | 
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| 93 | %============================== | 
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| 94 | \section{Scheduling in Practice} | 
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| 95 | %------------------------------ | 
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| 96 | \begin{frame}{In the Wild} | 
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| 97 | Schedulers found in production application generally fall into two categories: | 
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| 98 | \newline | 
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| 99 |  | 
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| 100 | \begin{itemize} | 
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| 101 | \item Feedback Scheduling\newline | 
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| 102 | \item Priority Scheduling (explicit or not)\newline | 
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| 103 | \end{itemize} | 
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| 104 | \end{frame} | 
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| 105 | %------------------------------ | 
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| 106 | \begin{frame}{Feedback Scheduling} | 
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| 107 | Most operating systems based their scheduling on feedback loops. | 
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| 108 | ~\newline | 
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| 109 |  | 
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| 110 | The scheduler runs a thread and adjusts some metric to choose when to run it, e.g., least CPU time first. | 
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| 111 | ~\newline | 
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| 112 |  | 
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| 113 | Relies on the following assumptions: | 
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| 114 | \begin{enumerate} | 
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| 115 | \item Threads live long enough for useful feedback information to be to gathered. | 
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| 116 | \item Threads belong to multiple users so fairness across threads is insufficient. | 
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| 117 | \end{enumerate} | 
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| 118 | \end{frame} | 
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| 119 | %------------------------------ | 
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| 120 | \begin{frame}{Priority Scheduling} | 
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| 121 | \begin{center} | 
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| 122 | {\large | 
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| 123 | Runs all ready threads in group \textit{A} before any ready threads in group \textit{B}. | 
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| 124 | } | 
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| 125 | \end{center} | 
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| 126 | \vspace{1em} | 
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| 127 |  | 
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| 128 | Explicit priorities: | 
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| 129 | \begin{itemize} | 
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| 130 | \item Threads given a priority at creation, e.g., Thread A has priority 1, Thread B has priority 6. | 
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| 131 | \end{itemize} | 
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| 132 | \vspace{0.75em} | 
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| 133 |  | 
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| 134 | Implicit priorities: | 
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| 135 | \begin{itemize} | 
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| 136 | \item Certain threads are preferred, based on various metrics, e.g., last run, last run on this CPU. | 
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| 137 | \end{itemize} | 
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| 138 | \end{frame} | 
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| 139 | %------------------------------ | 
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| 140 | \begin{frame}{Priority Scheduling: Work-Stealing} | 
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| 141 | Work-Stealing is a very popular strategy. | 
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| 142 | \begin{block}{Algorithm} | 
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| 143 | \begin{enumerate} | 
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| 144 | \item Each processor has a list of ready threads. | 
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| 145 | \item Each processor runs threads from its ready queue first. | 
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| 146 | \item If a processor's ready queue is empty, attempt to run threads from some other processor's ready queue. | 
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| 147 | \end{enumerate} | 
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| 148 | \end{block} | 
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| 149 | ~ | 
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| 150 |  | 
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| 151 | Work-Stealing has implicit priorities: For a given processor, threads on it's queue have higher priority. | 
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| 152 |  | 
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| 153 | Processors begin busy for long periods can mean starvation. | 
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| 154 | \end{frame} | 
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| 155 | %------------------------------ | 
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| 156 | \begin{frame}{Scheduling in Practice: Summary} | 
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| 157 | \begin{columns} | 
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| 158 | \begin{column}{0.5\textwidth} | 
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| 159 | \textbf{Feedback Scheduling} | 
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| 160 | \newline | 
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| 161 |  | 
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| 162 | \begin{itemize} | 
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| 163 | \item Inappropriate for short lived threads. | 
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| 164 | \item Overkill for cooperating threads.\newline | 
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| 165 | \end{itemize} | 
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| 166 | \end{column} | 
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| 167 | \begin{column}{0.5\textwidth} | 
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| 168 | \textbf{Priority Scheduling} | 
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| 169 | \newline | 
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| 170 |  | 
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| 171 | \begin{itemize} | 
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| 172 | \item Allows lasting starvation.\newline | 
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| 173 | \item Hard to reason about.\newline~\newline | 
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| 174 | \end{itemize} | 
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| 175 | \end{column} | 
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| 176 | \end{columns} | 
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| 177 |  | 
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| 178 | ~\newline | 
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| 179 | ~\newline | 
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| 180 | \CFA would benefit from something different. | 
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| 181 | \end{frame} | 
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| 182 | %============================== | 
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| 183 | \section{Project: Proposal \& Details} | 
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| 184 | %------------------------------ | 
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| 185 | \begin{frame}{Central Ready-Queue} | 
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| 186 | \CFA will have a single ready-queue per cluster. | 
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| 187 | \newline | 
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| 188 |  | 
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| 189 | The ready-queue will be sharded internally to reduce contention. | 
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| 190 | \newline | 
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| 191 |  | 
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| 192 | No strong coupling between internal queues and processors. | 
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| 193 | \newline | 
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| 194 |  | 
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| 195 | Constrasts with work-stealing which has a queue per processor. | 
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| 196 | \newline | 
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| 197 | \end{frame} | 
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| 198 | %------------------------------ | 
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| 199 | \begin{frame}{Central Ready-Queue} | 
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| 200 | \begin{table} | 
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| 201 | {\resizebox{0.8\textwidth}{!}{\input{base.dark.pstex_t}}} | 
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| 202 | \end{table} | 
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| 203 | ~ | 
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| 204 | \end{frame} | 
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| 205 | %------------------------------ | 
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| 206 | \begin{frame}{Central Ready-Queue Challenges} | 
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| 207 | \begin{columns} | 
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| 208 | \begin{column}{0.55\textwidth} | 
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| 209 | Semi-``Empty'' ready-queues means success rate of randomly guessing goes down. | 
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| 210 | \end{column} | 
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| 211 | \begin{column}{0.45\textwidth} | 
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| 212 | \begin{table} | 
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| 213 | {\resizebox{1\textwidth}{!}{\input{empty.dark.pstex_t}}} | 
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| 214 | \end{table} | 
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| 215 | \end{column} | 
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| 216 | \end{columns} | 
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| 217 |  | 
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| 218 | Possible solutions: | 
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| 219 | \begin{itemize} | 
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| 220 | \item Data structure tracking the work, can be dense or sparse, global or sharded. | 
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| 221 | \item Add bias towards certain sub-queues. | 
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| 222 | \end{itemize} | 
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| 223 | \end{frame} | 
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| 224 | %------------------------------ | 
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| 225 | \begin{frame}{Dynamic Resizing} | 
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| 226 | Processors can be added at anytime on a cluster. | 
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| 227 | \newline | 
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| 228 |  | 
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| 229 | The array of queues needs to be adjusted in consequence. | 
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| 230 | \newline | 
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| 231 |  | 
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| 232 | Solution: Global Reader-Writer lock | 
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| 233 | \begin{itemize} | 
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| 234 | \item Acquire for reading for normal scheduling operations. | 
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| 235 | \item Acquire for writing when resizing the array and creating/deleting internal queues. | 
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| 236 | \end{itemize} | 
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| 237 | \end{frame} | 
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| 238 | %------------------------------ | 
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| 239 | \begin{frame}{Idle Sleep} | 
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| 240 | Processors which cannot find threads to run should sleep, using \texttt{pthread\_cond\_wait}, \texttt{sigwaitinfo}, etc. | 
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| 241 | \newline | 
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| 242 |  | 
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| 243 | Scheduling a thread may \textit{need} to wake sleeping processors. | 
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| 244 | \begin{itemize} | 
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| 245 | \item Threads can be scheduled from processors terminating or running outside the cluster. | 
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| 246 | In this case, all processors on the cluster could be sleeping. | 
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| 247 | \end{itemize} | 
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| 248 | ~ | 
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| 249 |  | 
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| 250 | If \textit{some} processors are sleeping, waking more may be wasteful. | 
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| 251 |  | 
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| 252 | A heuristic for this case is outside the scope of this project. | 
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| 253 | \end{frame} | 
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| 254 | %------------------------------ | 
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| 255 | \begin{frame}{Asynchronous I/O} | 
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| 256 | \begin{itemize} | 
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| 257 | \item I/O Operations should block user-threads rather than kernel-threads. \vspace{1cm} | 
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| 258 | \item This requires 3 components: | 
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| 259 | \begin{enumerate} | 
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| 260 | \item an OS abstraction layer over the asynchronous interface,  \vspace{0.2cm} | 
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| 261 | \item an event-engine to (de)multiplex the operations,  \vspace{0.2cm} | 
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| 262 | \item and a synchronous interface for users to use.  \vspace{0.2cm} | 
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| 263 | \end{enumerate} | 
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| 264 | \end{itemize} | 
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| 265 | \end{frame} | 
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| 266 | %------------------------------ | 
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| 267 | \begin{frame}{Asynchronous I/O: OS Abstraction} | 
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| 268 | \framesubtitle{\vskip0.5mm\large\texttt{select}} | 
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| 269 | \vskip5mm | 
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| 270 |  | 
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| 271 | {\large ``select() allows a program to monitor multiple file descriptors, waiting until one | 
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| 272 | or more of the file descriptors become ``ready'' for some class of I/O operation.''} | 
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| 273 |  | 
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| 274 | \hspace*\fill{\small--- Linux Programmer's Manual} | 
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| 275 |  | 
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| 276 | \vskip5mm | 
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| 277 | \begin{itemize} | 
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| 278 | \item[+] moderate overhead per \texttt{syscall} | 
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| 279 | \item[-] Relies on \texttt{syscall}s returning \texttt{EWOULDBLOCK}. | 
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| 280 | \end{itemize} | 
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| 281 | \end{frame} | 
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| 282 | %------------------------------ | 
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| 283 | \begin{frame}{Asynchronous I/O: OS Abstraction} | 
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| 284 | \framesubtitle{\vskip0.5mm\large\texttt{epoll}} | 
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| 285 | \vskip2mm | 
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| 286 |  | 
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| 287 | More recent system call with a similar purpose. | 
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| 288 |  | 
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| 289 | \vskip5mm | 
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| 290 | \begin{itemize} | 
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| 291 | \item[+] Smaller overhead per \texttt{syscall}. | 
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| 292 | \item[+] Shown to work well for sockets. | 
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| 293 | \item[-] Still relies on \texttt{syscall}s returning \texttt{EWOULDBLOCK}. | 
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| 294 | \item[-] Does not support linux pipes and TTYs. | 
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| 295 | \end{itemize} | 
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| 296 | \end{frame} | 
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| 297 | %------------------------------ | 
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| 298 | \begin{frame}{Asynchronous I/O: OS Abstraction} | 
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| 299 | \framesubtitle{\vskip0.5mm\large Kernel Threads} | 
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| 300 | \vskip2mm | 
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| 301 |  | 
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| 302 | Use a pool of kernel-threads, to which blocking calls are delegated. | 
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| 303 |  | 
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| 304 | \vskip5mm | 
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| 305 | \begin{itemize} | 
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| 306 | \item Technique used by many existing systems, e.g., Go, libuv | 
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| 307 | \item[+] Definitely works for all \texttt{syscall}s. | 
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| 308 | \item[$-$] Can require many kernel threads. | 
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| 309 | \end{itemize} | 
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| 310 | \end{frame} | 
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| 311 | %------------------------------ | 
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| 312 | \begin{frame}{Asynchronous I/O: OS Abstraction} | 
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| 313 | \framesubtitle{\vskip0.5mm\large\texttt{io\_uring}} | 
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| 314 | \vskip2mm | 
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| 315 |  | 
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| 316 | A very recent framework for asynchronous operations available in Linux 5.1 and later. | 
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| 317 | Uses two ring buffers to submit operations and poll completions. | 
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| 318 |  | 
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| 319 | \vskip5mm | 
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| 320 | \begin{itemize} | 
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| 321 | \item[+] Handles many \texttt{syscall}s. | 
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| 322 | \item[+] Does \textit{not} rely on \texttt{syscall}s returning \texttt{EWOULDBLOCK}. | 
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| 323 | \item[$-$] Requires synchronization on submission. | 
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| 324 | \item[$-$] System call itself is serialized in the kernel. | 
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| 325 | \end{itemize} | 
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| 326 | \end{frame} | 
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| 327 | %------------------------------ | 
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| 328 | \begin{frame}{Asynchronous I/O: Event Engine} | 
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| 329 | An event engine must be built to fit the chosen OS Abstraction. | 
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| 330 | \newline | 
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| 331 |  | 
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| 332 | The engine must park user-threads until operation is completed. | 
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| 333 | \newline | 
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| 334 |  | 
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| 335 | Depending on the chosen abstraction the engine may need to serialize operation submission. | 
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| 336 | \newline | 
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| 337 |  | 
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| 338 | Throughput and latency are important metrics. | 
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| 339 | \end{frame} | 
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| 340 | %------------------------------ | 
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| 341 | \begin{frame}{Asynchronous I/O: The interface} | 
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| 342 | The Asynchronous I/O needs an interface. | 
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| 343 | \newline | 
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| 344 |  | 
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| 345 | Several options to take into consideration: | 
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| 346 | \begin{itemize} | 
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| 347 | \item Adding to existing call interface, e.g., \texttt{read} and \texttt{cfaread}.  \vspace{0.2cm} | 
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| 348 | \item Replacing existing call interface.  \vspace{0.2cm} | 
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| 349 | \item True asynchronous interface, e.g., callbacks, futures.  \vspace{0.2cm} | 
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| 350 | \end{itemize} | 
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| 351 |  | 
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| 352 | \end{frame} | 
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| 353 | %============================== | 
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| 354 | \section{Conclusion} | 
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| 355 | %------------------------------ | 
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| 356 | \begin{frame}{Summary} | 
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| 357 | Runtime system and scheduling are still open topics. | 
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| 358 | \newline | 
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| 359 | \newline | 
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| 360 |  | 
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| 361 | This work offers a novel runtime and scheduling package. | 
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| 362 | \newline | 
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| 363 | \newline | 
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| 364 |  | 
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| 365 | Existing work only offers fragments that users must assemble themselves when possible. | 
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| 366 | \end{frame} | 
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| 367 | %------------------------------ | 
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| 368 | \begin{frame}{Timeline} | 
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| 369 | \begin{tabular}{ || m{0.1mm} m{0.75cm} m{1cm} | l } | 
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| 370 | % \hline | 
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| 371 | \phantom{100000cm} \phantom{100000cm} \phantom{100000cm} & {\small May Oct} & {\small 2020 2020} & Creation of the performance benchmark. \\ | 
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| 372 | \hline | 
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| 373 | \phantom{100000cm} \phantom{100000cm} \phantom{100000cm} & {\small Nov Mar} & {\small 2020 2021} & Completion of the implementation. \\ | 
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| 374 | \hline | 
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| 375 | \phantom{100000cm} \phantom{100000cm} \phantom{100000cm} & {\small Mar Apr} & {\small 2021 2021} & Final performance experiments. \\ | 
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| 376 | \hline | 
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| 377 | \phantom{100000cm} \phantom{100000cm} \phantom{100000cm} & {\small May Aug} & {\small 2021 2021} & Thesis writing and defense. \\ | 
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| 378 | % \hline | 
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| 379 | \end{tabular} | 
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| 380 | \end{frame} | 
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| 381 |  | 
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| 382 | %------------------------------ | 
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| 383 | \begin{frame}{} | 
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| 384 | \begin{center} | 
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| 385 | {\large Questions?} | 
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| 386 | \end{center} | 
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| 387 | \end{frame} | 
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| 388 | \end{document} | 
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