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\begin{figure}
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\machinetimewaste[1]{2011 data}{cluster_2011.pgf}
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\machinetimewaste[1]{2019 data}{cluster_all.pgf}
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\caption{Relative task time (in milliseconds) spent in each execution phase w.r.t. task termination.}\label{fig:machinetimewaste-rel}
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\caption{Relative task time (in milliseconds) spent in each execution phase
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w.r.t. task termination in 2011 and 2019 traces. X axis shows task termination type,
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Y axis shows total time \% spent. Colors break down the time in execution phases. ``Unknown'' execution times are
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2019 specific and correspond to event time transitions that are not consider ``typical'' by Google.}\label{fig:machinetimewaste-rel}
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\end{figure}
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\begin{figure}
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@ -24,5 +27,6 @@
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\machinetimewaste{Cluster F}{cluster_f.pgf}
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\machinetimewaste{Cluster G}{cluster_g.pgf}
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\machinetimewaste{Cluster H}{cluster_h.pgf}
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\caption{Relative task time (in milliseconds) spent in each execution phase w.r.t. task termination.}\label{fig:machinetimewaste-rel-csts}
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\caption{Relative task time (in milliseconds) spent in each execution phase w.r.t. clusters in the
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2019 trace. Refer to figure~\ref{fig:machinetimewaste-rel} for axes description.}\label{fig:machinetimewaste-rel-csts}
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\end{figure}
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@ -649,7 +649,7 @@
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\definecolor{textcolor}{rgb}{0.000000,0.000000,0.000000}%
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\pgfsetstrokecolor{textcolor}%
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\pgfsetfillcolor{textcolor}%
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\pgftext[x=2.050000in,y=2.723333in,,base]{\color{textcolor}\rmfamily\fontsize{12.000000}{14.400000}\selectfont Cluster 2011}%
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\pgftext[x=2.050000in,y=2.723333in,,base]{\color{textcolor}\rmfamily\fontsize{12.000000}{14.400000}\selectfont 2011 data}%
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\end{pgfscope}%
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\begin{pgfscope}%
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\pgfsetbuttcap%
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@ -1,5 +1,13 @@
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\newcommand{\taskslowdown}[2]{
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\begin{subfigure}{0.24\textwidth}
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\begin{subfigure}{0.33\textwidth}
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\vspace{0.5cm}
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\begin{minipage}[c]{\textwidth}%
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\resizebox{\textwidth}{!}{#2}
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\end{minipage}
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\caption{#1}
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\end{subfigure}}
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\newcommand{\taskslowdownbig}[2]{
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\begin{subfigure}{0.49\textwidth}
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\vspace{0.5cm}
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\begin{minipage}[c]{\textwidth}%
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\resizebox{\textwidth}{!}{#2}
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@ -8,242 +16,307 @@
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\end{subfigure}}
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\begin{figure}
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\taskslowdown{Cluster A}{
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\begin{tabular}{rrr}
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\taskslowdownbig{2011 data}{
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\begin{tabular}{rlrrr}
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\toprule
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\textbf{Priority} & \textbf{\% finished tasks} & \textbf{Mean slowdown} \\
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\textbf{Priority} & \textbf{\% finished} & \textbf{Mean resp. (last evt.)} & \textbf{Mean resp. (all evts.)} & \textbf{Mean slowdown} \\
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\midrule
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Unknown & 10.620113\% & 1.097556 \\
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24 & 0.000000\% & -- \\
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25 & 0.333054\% & 82.973285 \\
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100 & 0.000000\% & -- \\
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101 & 81.917703\% & 30.798089 \\
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102 & 0.000000\% & -- \\
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103 & 14.990678\% & 1.130579 \\
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105 & 57.678214\% & 1.078733 \\
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107 & 53.926543\% & 1.016187 \\
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114 & 0.000000\% & -- \\
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115 & 4.108501\% & 1.004324 \\
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116 & 13.045304\% & 1.032749 \\
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117 & 0.000000\% & -- \\
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118 & 11.907081\% & 1.003494 \\
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119 & 21.264583\% & 1.504923 \\
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170 & 0.000000\% & -- \\
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200 & 27.211754\% & 4.116760 \\
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205 & 0.000000\% & -- \\
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210 & 0.000000\% & -- \\
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214 & 0.000000\% & -- \\
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215 & 0.000000\% & -- \\
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360 & 0.616372\% & 2.924018 \\
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400 & 0.000000\% & -- \\
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450 & 2.203423\% & 1.142450 \\
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500 & 0.000000\% & -- \\
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0 & 53.80\% & 2845 & 1767 & 3.37\\
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1 & 67.44\% & 3598 & 2939 &2.58\\
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2 & 90.78\% & 1835 & 1782 &1.15\\
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3 & 95.62\% & 9683 & 8294 &3.39\\
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4 & 78.05\% & 2006 & 1890 &1.69 \\
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5 & 100\% & 58 & 58 & 1 \\
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6 & 77.99\% & 567 & 567 & 1.02 \\
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8 & 45.48\% & 1159 & 1151 & 1.01 \\
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9 & 23.35\% & 504 & 496 & 1.07 \\
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\bottomrule
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\end{tabular}
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}
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\taskslowdownbig{2019 data}{
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\begin{tabular}{rlrrr}
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\toprule
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\textbf{Priority} & \textbf{\% finished} & \textbf{Mean resp. (last evt.)} & \textbf{Mean resp. (all evts.)} & \textbf{Mean slowdown} \\
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\midrule
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0 & 42.86\% & 1373.0 & 0.0 & 1.136770 \\
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3 & 0.0\% & -- & 0.0 & -- \\
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5 & 0.0\% & -- & 0.0 & -- \\
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10 & 0.0\% & -- & 0.0 & -- \\
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19 & 0.0\% & -- & 0.0 & -- \\
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24 & 0.0\% & -- & 0.0 & -- \\
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25 & 1.31\% & 86732.0 & 22.0 & 11.772172 \\
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50 & 0.0\% & -- & 0.0 & -- \\
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80 & 0.0\% & -- & 0.0 & -- \\
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100 & 0.0\% & -- & 0.0 & -- \\
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101 & 5.2\% & 65233.0 & 673.0 & 36.358841 \\
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102 & 0.0\% & -- & 0.0 & -- \\
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103 & 1.05\% & 8210.0 & 28.0 & 1.257530 \\
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105 & 22.9\% & 3651.0 & 616.0 & 1.733089 \\
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107 & 18.51\% & 1025.0 & 308.0 & 1.017332 \\
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114 & 0.07\% & 29364.0 & 2.0 & 1.003503 \\
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115 & 1.74\% & 10059.0 & 22.0 & 3.461721 \\
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116 & 3.03\% & 18226.0 & 71.0 & 1.102756 \\
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117 & 0.0\% & 2430.0 & 1.0 & 1.000000 \\
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118 & 1.28\% & 15072.0 & 163.0 & 3.340741 \\
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119 & 4.49\% & 19449.0 & 280.0 & 5.326446 \\
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170 & 0.0\% & -- & 0.0 & -- \\
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197 & 0.0\% & -- & 0.0 & -- \\
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199 & 0.0\% & -- & 0.0 & -- \\
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200 & 13.54\% & 54789.0 & 24.0 & 6.684155 \\
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201 & 0.0\% & -- & 0.0 & -- \\
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205 & 0.0\% & -- & 0.0 & -- \\
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210 & 0.0\% & -- & 0.0 & -- \\
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214 & 0.0\% & -- & 0.0 & -- \\
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215 & 0.0\% & -- & 0.0 & -- \\
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220 & 0.0\% & -- & 0.0 & -- \\
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360 & 3.36\% & 788069.0 & 42.0 & 2.241646 \\
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400 & 0.0\% & -- & 0.0 & -- \\
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450 & 1.15\% & 1182248.0 & 197.0 & 1.068893 \\
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500 & 0.0\% & -- & 0.0 & -- \\
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\bottomrule
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\end{tabular}
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}
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\caption{Mean task slowdown for each cluster and each task \textbf{Priority}}\label{fig:taskslowdown}
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\end{figure}
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\begin{figure}
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\taskslowdown{Cluster A}{
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\begin{tabular}{rrp{1.5cm}p{1.5cm}p{1.5cm}}
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\toprule
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\textbf{Priority} & \textbf{\% finished} & \textbf{Mean resp. (last evt.)} & \textbf{Mean resp. (all evts.)} & \textbf{Mean slowdown} \\
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\midrule
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24 & 0.0\% & -- & -- & -- \\
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25 & 0.33\% & 5769.0 & 1203.0 & 82.97 \\
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100 & 0.0\% & -- & -- & -- \\
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101 & 81.92\% & 63305.0 & 6346.0 & 30.80 \\
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102 & 0.0\% & -- & -- & -- \\
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103 & 14.99\% & 3074.0 & 3033.0 & 1.13 \\
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105 & 57.68\% & 1666.0 & 1750.0 & 1.08 \\
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107 & 53.93\% & 1022.0 & 1031.0 & 1.02 \\
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114 & 0.0\% & -- & -- & -- \\
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115 & 4.11\% & 2041.0 & 2042.0 & 1.00 \\
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116 & 13.05\% & 4443.0 & 4443.0 & 1.03 \\
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117 & 0.0\% & -- & -- & -- \\
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118 & 11.91\% & 1817.0 & 1814.0 & 1.00 \\
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119 & 21.26\% & 2250.0 & 2877.0 & 1.50 \\
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170 & 0.0\% & -- & -- & -- \\
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200 & 27.21\% & 4546.0 & 16845.0 & 4.12 \\
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205 & 0.0\% & -- & -- & -- \\
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210 & 0.0\% & -- & -- & -- \\
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214 & 0.0\% & -- & -- & -- \\
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215 & 0.0\% & -- & -- & -- \\
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360 & 0.62\% & 514181.0 & 400580.0 & 2.92 \\
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400 & 0.0\% & -- & -- & -- \\
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450 & 2.2\% & 686817.0 & 653878.0 & 1.14 \\
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500 & 0.0\% & -- & -- & -- \\
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\bottomrule
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\end{tabular}
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}
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\taskslowdown{Cluster B}{
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\begin{tabular}{rrr}
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\begin{tabular}{rrp{1.5cm}p{1.5cm}p{1.5cm}}
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\toprule
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\textbf{Priority} & \textbf{\% finished tasks} & \textbf{Mean slowdown} \\
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\textbf{Priority} & \textbf{\% finished} & \textbf{Mean resp. (last evt.)} & \textbf{Mean resp. (all evts.)} & \textbf{Mean slowdown} \\
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\midrule
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0 & 45.193049\% & 1.176397 \\
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25 & 0.018094\% & 133.481864 \\
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80 & 0.000000\% & -- \\
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100 & 0.000000\% & -- \\
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101 & 66.479321\% & 433.414195 \\
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103 & 0.106377\% & 1.645114 \\
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105 & 0.463292\% & 2.408090 \\
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107 & 0.000000\% & -- \\
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114 & 0.676897\% & 1.003422 \\
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115 & 4.117647\% & 5.916852 \\
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116 & 8.316438\% & 1.109652 \\
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117 & 0.000000\% & -- \\
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118 & 0.311290\% & 1.000000 \\
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119 & 0.195997\% & 2.555160 \\
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170 & 0.000000\% & -- \\
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199 & 0.000000\% & -- \\
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200 & 30.916717\% & 9.707524 \\
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205 & 0.000000\% & -- \\
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210 & 0.000000\% & -- \\
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214 & 0.000000\% & -- \\
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215 & 0.000000\% & -- \\
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360 & 3.502999\% & 1.612147 \\
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450 & 0.612913\% & 1.057515 \\
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0 & 45.19\% & 1351.0 & 1467.0 & 1.18 \\
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25 & 0.02\% & 10696.0 & 4121.0 & 133.48 \\
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80 & 0.0\% & -- & -- & -- \\
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100 & 0.0\% & -- & -- & -- \\
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101 & 66.48\% & 6069.0 & 5402.0 & 433.41 \\
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103 & 0.11\% & 19430.0 & 14897.0 & 1.65 \\
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105 & 0.46\% & 934421.0 & 392431.0 & 2.41 \\
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107 & 0.0\% & -- & -- & -- \\
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114 & 0.68\% & 32949.0 & 30470.0 & 1.00 \\
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115 & 4.12\% & 25585.0 & 107089.0 & 5.92 \\
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116 & 8.32\% & 29290.0 & 29017.0 & 1.11 \\
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117 & 0.0\% & -- & -- & -- \\
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118 & 0.31\% & 2776.0 & 2776.0 & 1.00 \\
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119 & 0.2\% & 193081.0 & 304469.0 & 2.56 \\
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170 & 0.0\% & -- & -- & -- \\
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199 & 0.0\% & -- & -- & -- \\
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200 & 30.92\% & 182604.0 & 466329.0 & 9.71 \\
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205 & 0.0\% & -- & -- & -- \\
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210 & 0.0\% & -- & -- & -- \\
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214 & 0.0\% & -- & -- & -- \\
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215 & 0.0\% & -- & -- & -- \\
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360 & 3.5\% & 1048245.0 & 495124.0 & 1.61 \\
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450 & 0.61\% & 1579367.0 & 1529555.0 & 1.06 \\
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\bottomrule
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\end{tabular}
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}
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\taskslowdown{Cluster C}{
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\begin{tabular}{rrr}
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\begin{tabular}{rrp{1.5cm}p{1.5cm}p{1.5cm}}
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\toprule
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\textbf{Priority} & \textbf{\% finished tasks} & \textbf{Mean slowdown} \\
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\textbf{Priority} & \textbf{\% finished} & \textbf{Mean resp. (last evt.)} & \textbf{Mean resp. (all evts.)} & \textbf{Mean slowdown} \\
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\midrule
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0 & 50.887820\% & 1.105787 \\
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3 & 0.000000\% & -- \\
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10 & 0.000000\% & -- \\
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25 & 22.468276\% & 8.191258 \\
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100 & 0.000000\% & -- \\
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101 & 52.628263\% & 421.490544 \\
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103 & 0.005336\% & 2.794339 \\
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105 & 0.023521\% & 1.372291 \\
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107 & 0.000245\% & 14.708268 \\
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114 & 0.022221\% & 1.011266 \\
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115 & 0.281832\% & 1.980743 \\
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116 & 0.013836\% & 1.022119 \\
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117 & 93.165468\% & 1.000000 \\
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118 & 0.004137\% & 1.100009 \\
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119 & 2.215917\% & 2.044049 \\
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170 & 0.000000\% & -- \\
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200 & 3.606796\% & 4.139724 \\
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205 & 0.000000\% & -- \\
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210 & 0.000000\% & -- \\
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214 & 0.000000\% & -- \\
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215 & 0.000000\% & -- \\
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360 & 4.367418\% & 2.061085 \\
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450 & 1.512578\% & 1.066014 \\
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0 & 50.89\% & 933.0 & 1002.0 & 1.11 \\
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3 & 0.0\% & -- & -- & -- \\
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10 & 0.0\% & -- & -- & -- \\
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25 & 22.47\% & 171281.0 & 4551.0 & 8.19 \\
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100 & 0.0\% & -- & -- & -- \\
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101 & 52.63\% & 6271.0 & 2498.0 & 421.49 \\
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103 & 0.01\% & 3344.0 & 7444.0 & 2.79 \\
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105 & 0.02\% & 1202141.0 & 863764.0 & 1.37 \\
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107 & 0.0\% & 7033.0 & 93102.0 & 14.71 \\
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114 & 0.02\% & 3148.0 & 3142.0 & 1.01 \\
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115 & 0.28\% & 14729.0 & 27168.0 & 1.98 \\
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116 & 0.01\% & 2846.0 & 2851.0 & 1.02 \\
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117 & 93.17\% & 2144.0 & 2144.0 & 1.00 \\
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118 & 0.0\% & 1114.0 & 1112.0 & 1.10 \\
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119 & 2.22\% & 573740.0 & 242446.0 & 2.04 \\
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170 & 0.0\% & -- & -- & -- \\
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200 & 3.61\% & 352603.0 & 357993.0 & 4.14 \\
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205 & 0.0\% & -- & -- & -- \\
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210 & 0.0\% & -- & -- & -- \\
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214 & 0.0\% & -- & -- & -- \\
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215 & 0.0\% & -- & -- & -- \\
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360 & 4.37\% & 769284.0 & 442062.0 & 2.06 \\
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450 & 1.51\% & 1390175.0 & 1319771.0 & 1.07 \\
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\bottomrule
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\end{tabular}
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}
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\taskslowdown{Cluster D}{
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\begin{tabular}{rrr}
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\begin{tabular}{rrp{1.5cm}p{1.5cm}p{1.5cm}}
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\toprule
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\textbf{Priority} & \textbf{\% finished tasks} & \textbf{Mean slowdown} \\
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\textbf{Priority} & \textbf{\% finished} & \textbf{Mean resp. (last evt.)} & \textbf{Mean resp. (all evts.)} & \textbf{Mean slowdown} \\
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\midrule
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0 & 26.522899\% & 1.116002 \\
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5 & 0.000000\% & -- \\
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25 & 16.293068\% & 65.676400 \\
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100 & 0.000000\% & -- \\
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101 & 45.314870\% & 315.954065 \\
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103 & 0.004540\% & 1.065721 \\
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105 & 0.051712\% & 2.897040 \\
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107 & 0.000350\% & 1.551354 \\
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114 & 0.000000\% & -- \\
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115 & 5.189033\% & 2.186562 \\
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116 & 0.126154\% & 1.278510 \\
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117 & 85.714286\% & 1.000000 \\
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118 & 0.054055\% & 2.048749 \\
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119 & 0.441844\% & 3.020486 \\
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197 & 0.000000\% & -- \\
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199 & 0.000000\% & -- \\
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200 & 6.528759\% & 5.514350 \\
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205 & 0.000000\% & -- \\
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210 & 0.000000\% & -- \\
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214 & 0.000000\% & -- \\
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215 & 0.000000\% & -- \\
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360 & 1.594977\% & 2.476706 \\
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450 & 0.611145\% & 1.330248 \\
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0 & 26.52\% & 1398.0 & 1469.0 & 1.12 \\
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5 & 0.0\% & -- & -- & -- \\
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25 & 16.29\% & 21432.0 & 4037.0 & 65.68 \\
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100 & 0.0\% & -- & -- & -- \\
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101 & 45.31\% & 8391.0 & 3317.0 & 315.95 \\
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103 & 0.0\% & 6791.0 & 6647.0 & 1.07 \\
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105 & 0.05\% & 825749.0 & 924081.0 & 2.90 \\
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107 & 0.0\% & 300532.0 & 174837.0 & 1.55 \\
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114 & 0.0\% & -- & -- & -- \\
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115 & 5.19\% & 12598.0 & 26142.0 & 2.19 \\
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116 & 0.13\% & 9268.0 & 10955.0 & 1.28 \\
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117 & 85.71\% & 10969.0 & 10969.0 & 1.00 \\
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118 & 0.05\% & 24041.0 & 30599.0 & 2.05 \\
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119 & 0.44\% & 184484.0 & 172746.0 & 3.02 \\
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197 & 0.0\% & -- & -- & -- \\
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199 & 0.0\% & -- & -- & -- \\
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200 & 6.53\% & 279565.0 & 349364.0 & 5.51 \\
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205 & 0.0\% & -- & -- & -- \\
|
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210 & 0.0\% & -- & -- & -- \\
|
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214 & 0.0\% & -- & -- & -- \\
|
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215 & 0.0\% & -- & -- & -- \\
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360 & 1.59\% & 650116.0 & 390151.0 & 2.48 \\
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450 & 0.61\% & 938727.0 & 523665.0 & 1.33 \\
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\bottomrule
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\end{tabular}
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}
|
||||
\taskslowdown{Cluster E}{
|
||||
\begin{tabular}{rrr}
|
||||
\begin{tabular}{rrp{1.5cm}p{1.5cm}p{1.5cm}}
|
||||
\toprule
|
||||
\textbf{Priority} & \textbf{\% finished tasks} & \textbf{Mean slowdown} \\
|
||||
\textbf{Priority} & \textbf{\% finished} & \textbf{Mean resp. (last evt.)} & \textbf{Mean resp. (all evts.)} & \textbf{Mean slowdown} \\
|
||||
\midrule
|
||||
0 & 42.805214\% & 1.439544 \\
|
||||
25 & 5.344531\% & 2.676136 \\
|
||||
100 & 0.000000\% & -- \\
|
||||
101 & 0.015918\% & 1.122507 \\
|
||||
103 & 0.021660\% & 3.163046 \\
|
||||
105 & 0.404803\% & 14.750313 \\
|
||||
107 & 0.000000\% & -- \\
|
||||
114 & 0.000000\% & -- \\
|
||||
115 & 0.027326\% & 1.000000 \\
|
||||
116 & 0.000000\% & -- \\
|
||||
117 & 0.000000\% & -- \\
|
||||
118 & 0.000000\% & -- \\
|
||||
119 & 0.458256\% & 10.310893 \\
|
||||
170 & 0.000000\% & -- \\
|
||||
200 & 1.959258\% & 8.535722 \\
|
||||
201 & 0.000000\% & -- \\
|
||||
205 & 0.000000\% & -- \\
|
||||
210 & 0.000000\% & -- \\
|
||||
215 & 0.000000\% & -- \\
|
||||
220 & 0.000000\% & -- \\
|
||||
360 & 37.157031\% & 2.873243 \\
|
||||
450 & 0.548458\% & 1.113283 \\
|
||||
0 & 42.81\% & 802.0 & 1127.0 & 1.44 \\
|
||||
25 & 5.34\% & 32247.0 & 38946.0 & 2.68 \\
|
||||
100 & 0.0\% & -- & -- & -- \\
|
||||
101 & 0.02\% & 30603.0 & 27726.0 & 1.12 \\
|
||||
103 & 0.02\% & 76294.0 & 48552.0 & 3.16 \\
|
||||
105 & 0.4\% & 106677.0 & 64190.0 & 14.75 \\
|
||||
107 & 0.0\% & -- & -- & -- \\
|
||||
114 & 0.0\% & -- & -- & -- \\
|
||||
115 & 0.03\% & 67237.0 & 65369.0 & 1.00 \\
|
||||
116 & 0.0\% & -- & -- & -- \\
|
||||
117 & 0.0\% & -- & -- & -- \\
|
||||
118 & 0.0\% & -- & -- & -- \\
|
||||
119 & 0.46\% & 62123.0 & 83322.0 & 10.31 \\
|
||||
170 & 0.0\% & -- & -- & -- \\
|
||||
200 & 1.96\% & 231639.0 & 414149.0 & 8.54 \\
|
||||
201 & 0.0\% & -- & -- & -- \\
|
||||
205 & 0.0\% & -- & -- & -- \\
|
||||
210 & 0.0\% & -- & -- & -- \\
|
||||
215 & 0.0\% & -- & -- & -- \\
|
||||
220 & 0.0\% & -- & -- & -- \\
|
||||
360 & 37.16\% & 611504.0 & 439280.0 & 2.87 \\
|
||||
450 & 0.55\% & 803792.0 & 824467.0 & 1.11 \\
|
||||
\bottomrule
|
||||
\end{tabular}
|
||||
|
||||
}
|
||||
\taskslowdown{Cluster F}{
|
||||
\begin{tabular}{rrr}
|
||||
\begin{tabular}{rrp{1.5cm}p{1.5cm}p{1.5cm}}
|
||||
\toprule
|
||||
\textbf{Priority} & \textbf{\% finished tasks} & \textbf{Mean slowdown} \\
|
||||
\textbf{Priority} & \textbf{\% finished} & \textbf{Mean resp. (last evt.)} & \textbf{Mean resp. (all evts.)} & \textbf{Mean slowdown} \\
|
||||
\midrule
|
||||
0 & 45.208221\% & 1.088162 \\
|
||||
25 & 0.647505\% & 2.230960 \\
|
||||
100 & 0.000000\% & -- \\
|
||||
101 & 40.296631\% & 323.858714 \\
|
||||
103 & 0.058418\% & 1.167347 \\
|
||||
105 & 0.222372\% & 1.550453 \\
|
||||
107 & 0.060860\% & 1.012727 \\
|
||||
114 & 0.006958\% & 1.000000 \\
|
||||
115 & 3.647104\% & 5.094215 \\
|
||||
116 & 0.000000\% & -- \\
|
||||
117 & 0.000086\% & 1.000000 \\
|
||||
118 & 0.002082\% & 1.000000 \\
|
||||
119 & 31.354662\% & 7.608799 \\
|
||||
200 & 3.653528\% & 5.943247 \\
|
||||
201 & 0.000000\% & -- \\
|
||||
360 & 7.424790\% & 2.171524 \\
|
||||
450 & 0.992623\% & 1.021053 \\
|
||||
0 & 45.21\% & 2929.0 & 2973.0 & 1.09 \\
|
||||
25 & 0.65\% & 184518.0 & 34096.0 & 2.23 \\
|
||||
100 & 0.0\% & -- & -- & -- \\
|
||||
101 & 40.3\% & 8160.0 & 10083.0 & 323.86 \\
|
||||
103 & 0.06\% & 46444.0 & 47234.0 & 1.17 \\
|
||||
105 & 0.22\% & 1111530.0 & 1173594.0 & 1.55 \\
|
||||
107 & 0.06\% & 80151.0 & 78835.0 & 1.01 \\
|
||||
114 & 0.01\% & 677.0 & 677.0 & 1.00 \\
|
||||
115 & 3.65\% & 121345.0 & 252663.0 & 5.09 \\
|
||||
116 & 0.0\% & -- & -- & -- \\
|
||||
117 & 0.0\% & 15875.0 & 15875.0 & 1.00 \\
|
||||
118 & 0.0\% & 30045.0 & 25492.0 & 1.00 \\
|
||||
119 & 31.35\% & 154196.0 & 68833.0 & 7.61 \\
|
||||
200 & 3.65\% & 297168.0 & 492372.0 & 5.94 \\
|
||||
201 & 0.0\% & -- & -- & -- \\
|
||||
360 & 7.42\% & 963351.0 & 569428.0 & 2.17 \\
|
||||
450 & 0.99\% & 1115783.0 & 1113282.0 & 1.02 \\
|
||||
\bottomrule
|
||||
\end{tabular}
|
||||
|
||||
}
|
||||
\taskslowdown{Cluster G}{
|
||||
\begin{tabular}{rrr}
|
||||
\begin{tabular}{rrp{1.5cm}p{1.5cm}p{1.5cm}}
|
||||
\toprule
|
||||
\textbf{Priority} & \textbf{\% finished tasks} & \textbf{Mean slowdown} \\
|
||||
\textbf{Priority} & \textbf{\% finished} & \textbf{Mean resp. (last evt.)} & \textbf{Mean resp. (all evts.)} & \textbf{Mean slowdown} \\
|
||||
\midrule
|
||||
0 & 33.612201\% & 1.138988 \\
|
||||
25 & 0.233338\% & 8.692558 \\
|
||||
50 & 0.000000\% & -- \\
|
||||
100 & 0.000000\% & -- \\
|
||||
101 & 96.470338\% & 19.378523 \\
|
||||
103 & 0.032539\% & 1.271282 \\
|
||||
105 & 0.196286\% & 1.000738 \\
|
||||
107 & 0.000000\% & -- \\
|
||||
114 & 0.000000\% & -- \\
|
||||
115 & 7.633588\% & 1.802068 \\
|
||||
117 & 0.000000\% & -- \\
|
||||
118 & 48.969072\% & 3.877102 \\
|
||||
119 & 0.085944\% & 3.166077 \\
|
||||
170 & 0.000000\% & -- \\
|
||||
200 & 26.747126\% & 14.573912 \\
|
||||
360 & 1.618878\% & 2.119524 \\
|
||||
450 & 2.737219\% & 1.036927 \\
|
||||
0 & 33.61\% & 3010.0 & 3317.0 & 1.14 \\
|
||||
25 & 0.23\% & 61708.0 & 12156.0 & 8.69 \\
|
||||
50 & 0.0\% & -- & -- & -- \\
|
||||
100 & 0.0\% & -- & -- & -- \\
|
||||
101 & 96.47\% & 133953.0 & 7448.0 & 19.38 \\
|
||||
103 & 0.03\% & 118310.0 & 112746.0 & 1.27 \\
|
||||
105 & 0.2\% & 8271.0 & 8214.0 & 1.00 \\
|
||||
107 & 0.0\% & -- & -- & -- \\
|
||||
114 & 0.0\% & -- & -- & -- \\
|
||||
115 & 7.63\% & 34424.0 & 56315.0 & 1.80 \\
|
||||
117 & 0.0\% & -- & -- & -- \\
|
||||
118 & 48.97\% & 608526.0 & 474729.0 & 3.88 \\
|
||||
119 & 0.09\% & 124006.0 & 231395.0 & 3.17 \\
|
||||
170 & 0.0\% & -- & -- & -- \\
|
||||
200 & 26.75\% & 115953.0 & 399050.0 & 14.57 \\
|
||||
360 & 1.62\% & 786594.0 & 488025.0 & 2.12 \\
|
||||
450 & 2.74\% & 1204747.0 & 1188251.0 & 1.04 \\
|
||||
\bottomrule
|
||||
\end{tabular}
|
||||
|
||||
}
|
||||
\taskslowdown{Cluster H}{
|
||||
\begin{tabular}{rrr}
|
||||
\begin{tabular}{rrp{1.5cm}p{1.5cm}p{1.5cm}}
|
||||
\toprule
|
||||
\textbf{Priority} & \textbf{\% finished tasks} & \textbf{Mean slowdown} \\
|
||||
\textbf{Priority} & \textbf{\% finished} & \textbf{Mean resp. (last evt.)} & \textbf{Mean resp. (all evts.)} & \textbf{Mean slowdown} \\
|
||||
\midrule
|
||||
0 & 27.744380\% & 1.122458 \\
|
||||
19 & 0.000000\% & -- \\
|
||||
25 & 1.042767\% & 3.064188 \\
|
||||
101 & 100.000000\% & 76.438090 \\
|
||||
103 & 0.481256\% & 1.262067 \\
|
||||
105 & 1.427256\% & 4.205547 \\
|
||||
107 & 0.000000\% & -- \\
|
||||
115 & 5.122494\% & 1.000000 \\
|
||||
116 & 1.035309\% & 73.447995 \\
|
||||
117 & 0.000050\% & 1.000000 \\
|
||||
118 & 1.003331\% & 1.947121 \\
|
||||
119 & 0.145214\% & 7.301093 \\
|
||||
200 & 2.702770\% & 5.798142 \\
|
||||
201 & 0.000000\% & -- \\
|
||||
220 & 0.000000\% & -- \\
|
||||
360 & 4.425746\% & 2.018441 \\
|
||||
450 & 0.535389\% & 1.054678 \\
|
||||
0 & 27.74\% & 5663.0 & 6211.0 & 1.12 \\
|
||||
19 & 0.0\% & -- & -- & -- \\
|
||||
25 & 1.04\% & 304870.0 & 283847.0 & 3.06 \\
|
||||
101 & 100.0\% & 34063.0 & 12250.0 & 76.44 \\
|
||||
103 & 0.48\% & 272635.0 & 92894.0 & 1.26 \\
|
||||
105 & 1.43\% & 611763.0 & 393762.0 & 4.21 \\
|
||||
107 & 0.0\% & -- & -- & -- \\
|
||||
115 & 5.12\% & 28907.0 & 28907.0 & 1.00 \\
|
||||
116 & 1.04\% & 633.0 & 42105.0 & 73.45 \\
|
||||
117 & 0.0\% & 656.0 & 656.0 & 1.00 \\
|
||||
118 & 1.0\% & 197687.0 & 139121.0 & 1.95 \\
|
||||
119 & 0.15\% & 139907.0 & 15558.0 & 7.30 \\
|
||||
200 & 2.7\% & 298799.0 & 470783.0 & 5.80 \\
|
||||
201 & 0.0\% & -- & -- & -- \\
|
||||
220 & 0.0\% & -- & -- & -- \\
|
||||
360 & 4.43\% & 838719.0 & 397301.0 & 2.02 \\
|
||||
450 & 0.54\% & 1470577.0 & 1411397.0 & 1.05 \\
|
||||
\bottomrule
|
||||
\end{tabular}}
|
||||
\caption{Mean task slowdown for each cluster and each task priority}\label{fig:taskslowdown}
|
||||
\end{tabular}
|
||||
|
||||
}
|
||||
\caption{Mean task slowdown for each cluster and each task \textbf{Priority}}\label{fig:taskslowdown-csts}
|
||||
\end{figure}
|
||||
|
|
|
|||
|
|
@ -9,7 +9,7 @@
|
|||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 2,
|
||||
"execution_count": 5,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
|
|
@ -43,7 +43,7 @@
|
|||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 23,
|
||||
"execution_count": 38,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
|
|
@ -51,240 +51,284 @@
|
|||
"output_type": "stream",
|
||||
"text": [
|
||||
"\\taskslowdown{Cluster A}{\n",
|
||||
"\\begin{tabular}{rrr}\n",
|
||||
"\\begin{tabular}{rlrrr}\n",
|
||||
"\\toprule\n",
|
||||
" priority & finished\\% & m\\_slow\\_2 \\\\\n",
|
||||
" priority & finished\\% & m\\_last & m\\_all & m\\_slow\\_2 \\\\\n",
|
||||
"\\midrule\n",
|
||||
" -1 & 10.620113 & 1.097556 \\\\\n",
|
||||
" 24 & 0.000000 & NaN \\\\\n",
|
||||
" 25 & 0.333054 & 82.973285 \\\\\n",
|
||||
" 100 & 0.000000 & NaN \\\\\n",
|
||||
" 101 & 81.917703 & 30.798089 \\\\\n",
|
||||
" 102 & 0.000000 & NaN \\\\\n",
|
||||
" 103 & 14.990678 & 1.130579 \\\\\n",
|
||||
" 105 & 57.678214 & 1.078733 \\\\\n",
|
||||
" 107 & 53.926543 & 1.016187 \\\\\n",
|
||||
" 114 & 0.000000 & NaN \\\\\n",
|
||||
" 115 & 4.108501 & 1.004324 \\\\\n",
|
||||
" 116 & 13.045304 & 1.032749 \\\\\n",
|
||||
" 117 & 0.000000 & NaN \\\\\n",
|
||||
" 118 & 11.907081 & 1.003494 \\\\\n",
|
||||
" 119 & 21.264583 & 1.504923 \\\\\n",
|
||||
" 170 & 0.000000 & NaN \\\\\n",
|
||||
" 200 & 27.211754 & 4.116760 \\\\\n",
|
||||
" 205 & 0.000000 & NaN \\\\\n",
|
||||
" 210 & 0.000000 & NaN \\\\\n",
|
||||
" 214 & 0.000000 & NaN \\\\\n",
|
||||
" 215 & 0.000000 & NaN \\\\\n",
|
||||
" 360 & 0.616372 & 2.924018 \\\\\n",
|
||||
" 400 & 0.000000 & NaN \\\\\n",
|
||||
" 450 & 2.203423 & 1.142450 \\\\\n",
|
||||
" 500 & 0.000000 & NaN \\\\\n",
|
||||
" -1 & 10.62\\% & 783.0 & 593.0 & 1.10 \\\\\n",
|
||||
" 24 & 0.0\\% & NaN & NaN & NaN \\\\\n",
|
||||
" 25 & 0.33\\% & 5769.0 & 1203.0 & 82.97 \\\\\n",
|
||||
" 100 & 0.0\\% & NaN & NaN & NaN \\\\\n",
|
||||
" 101 & 81.92\\% & 63305.0 & 6346.0 & 30.80 \\\\\n",
|
||||
" 102 & 0.0\\% & NaN & NaN & NaN \\\\\n",
|
||||
" 103 & 14.99\\% & 3074.0 & 3033.0 & 1.13 \\\\\n",
|
||||
" 105 & 57.68\\% & 1666.0 & 1750.0 & 1.08 \\\\\n",
|
||||
" 107 & 53.93\\% & 1022.0 & 1031.0 & 1.02 \\\\\n",
|
||||
" 114 & 0.0\\% & NaN & NaN & NaN \\\\\n",
|
||||
" 115 & 4.11\\% & 2041.0 & 2042.0 & 1.00 \\\\\n",
|
||||
" 116 & 13.05\\% & 4443.0 & 4443.0 & 1.03 \\\\\n",
|
||||
" 117 & 0.0\\% & NaN & NaN & NaN \\\\\n",
|
||||
" 118 & 11.91\\% & 1817.0 & 1814.0 & 1.00 \\\\\n",
|
||||
" 119 & 21.26\\% & 2250.0 & 2877.0 & 1.50 \\\\\n",
|
||||
" 170 & 0.0\\% & NaN & NaN & NaN \\\\\n",
|
||||
" 200 & 27.21\\% & 4546.0 & 16845.0 & 4.12 \\\\\n",
|
||||
" 205 & 0.0\\% & NaN & NaN & NaN \\\\\n",
|
||||
" 210 & 0.0\\% & NaN & NaN & NaN \\\\\n",
|
||||
" 214 & 0.0\\% & NaN & NaN & NaN \\\\\n",
|
||||
" 215 & 0.0\\% & NaN & NaN & NaN \\\\\n",
|
||||
" 360 & 0.62\\% & 514181.0 & 400580.0 & 2.92 \\\\\n",
|
||||
" 400 & 0.0\\% & NaN & NaN & NaN \\\\\n",
|
||||
" 450 & 2.2\\% & 686817.0 & 653878.0 & 1.14 \\\\\n",
|
||||
" 500 & 0.0\\% & NaN & NaN & NaN \\\\\n",
|
||||
"\\bottomrule\n",
|
||||
"\\end{tabular}\n",
|
||||
"\n",
|
||||
"}\n",
|
||||
"\\taskslowdown{Cluster B}{\n",
|
||||
"\\begin{tabular}{rrr}\n",
|
||||
"\\begin{tabular}{rlrrr}\n",
|
||||
"\\toprule\n",
|
||||
" priority & finished\\% & m\\_slow\\_2 \\\\\n",
|
||||
" priority & finished\\% & m\\_last & m\\_all & m\\_slow\\_2 \\\\\n",
|
||||
"\\midrule\n",
|
||||
" 0 & 45.193049 & 1.176397 \\\\\n",
|
||||
" 25 & 0.018094 & 133.481864 \\\\\n",
|
||||
" 80 & 0.000000 & NaN \\\\\n",
|
||||
" 100 & 0.000000 & NaN \\\\\n",
|
||||
" 101 & 66.479321 & 433.414195 \\\\\n",
|
||||
" 103 & 0.106377 & 1.645114 \\\\\n",
|
||||
" 105 & 0.463292 & 2.408090 \\\\\n",
|
||||
" 107 & 0.000000 & NaN \\\\\n",
|
||||
" 114 & 0.676897 & 1.003422 \\\\\n",
|
||||
" 115 & 4.117647 & 5.916852 \\\\\n",
|
||||
" 116 & 8.316438 & 1.109652 \\\\\n",
|
||||
" 117 & 0.000000 & NaN \\\\\n",
|
||||
" 118 & 0.311290 & 1.000000 \\\\\n",
|
||||
" 119 & 0.195997 & 2.555160 \\\\\n",
|
||||
" 170 & 0.000000 & NaN \\\\\n",
|
||||
" 199 & 0.000000 & NaN \\\\\n",
|
||||
" 200 & 30.916717 & 9.707524 \\\\\n",
|
||||
" 205 & 0.000000 & NaN \\\\\n",
|
||||
" 210 & 0.000000 & NaN \\\\\n",
|
||||
" 214 & 0.000000 & NaN \\\\\n",
|
||||
" 215 & 0.000000 & NaN \\\\\n",
|
||||
" 360 & 3.502999 & 1.612147 \\\\\n",
|
||||
" 450 & 0.612913 & 1.057515 \\\\\n",
|
||||
" 0 & 45.19\\% & 1351.0 & 1467.0 & 1.18 \\\\\n",
|
||||
" 25 & 0.02\\% & 10696.0 & 4121.0 & 133.48 \\\\\n",
|
||||
" 80 & 0.0\\% & NaN & NaN & NaN \\\\\n",
|
||||
" 100 & 0.0\\% & NaN & NaN & NaN \\\\\n",
|
||||
" 101 & 66.48\\% & 6069.0 & 5402.0 & 433.41 \\\\\n",
|
||||
" 103 & 0.11\\% & 19430.0 & 14897.0 & 1.65 \\\\\n",
|
||||
" 105 & 0.46\\% & 934421.0 & 392431.0 & 2.41 \\\\\n",
|
||||
" 107 & 0.0\\% & NaN & NaN & NaN \\\\\n",
|
||||
" 114 & 0.68\\% & 32949.0 & 30470.0 & 1.00 \\\\\n",
|
||||
" 115 & 4.12\\% & 25585.0 & 107089.0 & 5.92 \\\\\n",
|
||||
" 116 & 8.32\\% & 29290.0 & 29017.0 & 1.11 \\\\\n",
|
||||
" 117 & 0.0\\% & NaN & NaN & NaN \\\\\n",
|
||||
" 118 & 0.31\\% & 2776.0 & 2776.0 & 1.00 \\\\\n",
|
||||
" 119 & 0.2\\% & 193081.0 & 304469.0 & 2.56 \\\\\n",
|
||||
" 170 & 0.0\\% & NaN & NaN & NaN \\\\\n",
|
||||
" 199 & 0.0\\% & NaN & NaN & NaN \\\\\n",
|
||||
" 200 & 30.92\\% & 182604.0 & 466329.0 & 9.71 \\\\\n",
|
||||
" 205 & 0.0\\% & NaN & NaN & NaN \\\\\n",
|
||||
" 210 & 0.0\\% & NaN & NaN & NaN \\\\\n",
|
||||
" 214 & 0.0\\% & NaN & NaN & NaN \\\\\n",
|
||||
" 215 & 0.0\\% & NaN & NaN & NaN \\\\\n",
|
||||
" 360 & 3.5\\% & 1048245.0 & 495124.0 & 1.61 \\\\\n",
|
||||
" 450 & 0.61\\% & 1579367.0 & 1529555.0 & 1.06 \\\\\n",
|
||||
"\\bottomrule\n",
|
||||
"\\end{tabular}\n",
|
||||
"\n",
|
||||
"}\n",
|
||||
"\\taskslowdown{Cluster C}{\n",
|
||||
"\\begin{tabular}{rrr}\n",
|
||||
"\\begin{tabular}{rlrrr}\n",
|
||||
"\\toprule\n",
|
||||
" priority & finished\\% & m\\_slow\\_2 \\\\\n",
|
||||
" priority & finished\\% & m\\_last & m\\_all & m\\_slow\\_2 \\\\\n",
|
||||
"\\midrule\n",
|
||||
" 0 & 50.887820 & 1.105787 \\\\\n",
|
||||
" 3 & 0.000000 & NaN \\\\\n",
|
||||
" 10 & 0.000000 & NaN \\\\\n",
|
||||
" 25 & 22.468276 & 8.191258 \\\\\n",
|
||||
" 100 & 0.000000 & NaN \\\\\n",
|
||||
" 101 & 52.628263 & 421.490544 \\\\\n",
|
||||
" 103 & 0.005336 & 2.794339 \\\\\n",
|
||||
" 105 & 0.023521 & 1.372291 \\\\\n",
|
||||
" 107 & 0.000245 & 14.708268 \\\\\n",
|
||||
" 114 & 0.022221 & 1.011266 \\\\\n",
|
||||
" 115 & 0.281832 & 1.980743 \\\\\n",
|
||||
" 116 & 0.013836 & 1.022119 \\\\\n",
|
||||
" 117 & 93.165468 & 1.000000 \\\\\n",
|
||||
" 118 & 0.004137 & 1.100009 \\\\\n",
|
||||
" 119 & 2.215917 & 2.044049 \\\\\n",
|
||||
" 170 & 0.000000 & NaN \\\\\n",
|
||||
" 200 & 3.606796 & 4.139724 \\\\\n",
|
||||
" 205 & 0.000000 & NaN \\\\\n",
|
||||
" 210 & 0.000000 & NaN \\\\\n",
|
||||
" 214 & 0.000000 & NaN \\\\\n",
|
||||
" 215 & 0.000000 & NaN \\\\\n",
|
||||
" 360 & 4.367418 & 2.061085 \\\\\n",
|
||||
" 450 & 1.512578 & 1.066014 \\\\\n",
|
||||
" 0 & 50.89\\% & 933.0 & 1002.0 & 1.11 \\\\\n",
|
||||
" 3 & 0.0\\% & NaN & NaN & NaN \\\\\n",
|
||||
" 10 & 0.0\\% & NaN & NaN & NaN \\\\\n",
|
||||
" 25 & 22.47\\% & 171281.0 & 4551.0 & 8.19 \\\\\n",
|
||||
" 100 & 0.0\\% & NaN & NaN & NaN \\\\\n",
|
||||
" 101 & 52.63\\% & 6271.0 & 2498.0 & 421.49 \\\\\n",
|
||||
" 103 & 0.01\\% & 3344.0 & 7444.0 & 2.79 \\\\\n",
|
||||
" 105 & 0.02\\% & 1202141.0 & 863764.0 & 1.37 \\\\\n",
|
||||
" 107 & 0.0\\% & 7033.0 & 93102.0 & 14.71 \\\\\n",
|
||||
" 114 & 0.02\\% & 3148.0 & 3142.0 & 1.01 \\\\\n",
|
||||
" 115 & 0.28\\% & 14729.0 & 27168.0 & 1.98 \\\\\n",
|
||||
" 116 & 0.01\\% & 2846.0 & 2851.0 & 1.02 \\\\\n",
|
||||
" 117 & 93.17\\% & 2144.0 & 2144.0 & 1.00 \\\\\n",
|
||||
" 118 & 0.0\\% & 1114.0 & 1112.0 & 1.10 \\\\\n",
|
||||
" 119 & 2.22\\% & 573740.0 & 242446.0 & 2.04 \\\\\n",
|
||||
" 170 & 0.0\\% & NaN & NaN & NaN \\\\\n",
|
||||
" 200 & 3.61\\% & 352603.0 & 357993.0 & 4.14 \\\\\n",
|
||||
" 205 & 0.0\\% & NaN & NaN & NaN \\\\\n",
|
||||
" 210 & 0.0\\% & NaN & NaN & NaN \\\\\n",
|
||||
" 214 & 0.0\\% & NaN & NaN & NaN \\\\\n",
|
||||
" 215 & 0.0\\% & NaN & NaN & NaN \\\\\n",
|
||||
" 360 & 4.37\\% & 769284.0 & 442062.0 & 2.06 \\\\\n",
|
||||
" 450 & 1.51\\% & 1390175.0 & 1319771.0 & 1.07 \\\\\n",
|
||||
"\\bottomrule\n",
|
||||
"\\end{tabular}\n",
|
||||
"\n",
|
||||
"}\n",
|
||||
"\\taskslowdown{Cluster D}{\n",
|
||||
"\\begin{tabular}{rrr}\n",
|
||||
"\\begin{tabular}{rlrrr}\n",
|
||||
"\\toprule\n",
|
||||
" priority & finished\\% & m\\_slow\\_2 \\\\\n",
|
||||
" priority & finished\\% & m\\_last & m\\_all & m\\_slow\\_2 \\\\\n",
|
||||
"\\midrule\n",
|
||||
" 0 & 26.522899 & 1.116002 \\\\\n",
|
||||
" 5 & 0.000000 & NaN \\\\\n",
|
||||
" 25 & 16.293068 & 65.676400 \\\\\n",
|
||||
" 100 & 0.000000 & NaN \\\\\n",
|
||||
" 101 & 45.314870 & 315.954065 \\\\\n",
|
||||
" 103 & 0.004540 & 1.065721 \\\\\n",
|
||||
" 105 & 0.051712 & 2.897040 \\\\\n",
|
||||
" 107 & 0.000350 & 1.551354 \\\\\n",
|
||||
" 114 & 0.000000 & NaN \\\\\n",
|
||||
" 115 & 5.189033 & 2.186562 \\\\\n",
|
||||
" 116 & 0.126154 & 1.278510 \\\\\n",
|
||||
" 117 & 85.714286 & 1.000000 \\\\\n",
|
||||
" 118 & 0.054055 & 2.048749 \\\\\n",
|
||||
" 119 & 0.441844 & 3.020486 \\\\\n",
|
||||
" 197 & 0.000000 & NaN \\\\\n",
|
||||
" 199 & 0.000000 & NaN \\\\\n",
|
||||
" 200 & 6.528759 & 5.514350 \\\\\n",
|
||||
" 205 & 0.000000 & NaN \\\\\n",
|
||||
" 210 & 0.000000 & NaN \\\\\n",
|
||||
" 214 & 0.000000 & NaN \\\\\n",
|
||||
" 215 & 0.000000 & NaN \\\\\n",
|
||||
" 360 & 1.594977 & 2.476706 \\\\\n",
|
||||
" 450 & 0.611145 & 1.330248 \\\\\n",
|
||||
" 0 & 26.52\\% & 1398.0 & 1469.0 & 1.12 \\\\\n",
|
||||
" 5 & 0.0\\% & NaN & NaN & NaN \\\\\n",
|
||||
" 25 & 16.29\\% & 21432.0 & 4037.0 & 65.68 \\\\\n",
|
||||
" 100 & 0.0\\% & NaN & NaN & NaN \\\\\n",
|
||||
" 101 & 45.31\\% & 8391.0 & 3317.0 & 315.95 \\\\\n",
|
||||
" 103 & 0.0\\% & 6791.0 & 6647.0 & 1.07 \\\\\n",
|
||||
" 105 & 0.05\\% & 825749.0 & 924081.0 & 2.90 \\\\\n",
|
||||
" 107 & 0.0\\% & 300532.0 & 174837.0 & 1.55 \\\\\n",
|
||||
" 114 & 0.0\\% & NaN & NaN & NaN \\\\\n",
|
||||
" 115 & 5.19\\% & 12598.0 & 26142.0 & 2.19 \\\\\n",
|
||||
" 116 & 0.13\\% & 9268.0 & 10955.0 & 1.28 \\\\\n",
|
||||
" 117 & 85.71\\% & 10969.0 & 10969.0 & 1.00 \\\\\n",
|
||||
" 118 & 0.05\\% & 24041.0 & 30599.0 & 2.05 \\\\\n",
|
||||
" 119 & 0.44\\% & 184484.0 & 172746.0 & 3.02 \\\\\n",
|
||||
" 197 & 0.0\\% & NaN & NaN & NaN \\\\\n",
|
||||
" 199 & 0.0\\% & NaN & NaN & NaN \\\\\n",
|
||||
" 200 & 6.53\\% & 279565.0 & 349364.0 & 5.51 \\\\\n",
|
||||
" 205 & 0.0\\% & NaN & NaN & NaN \\\\\n",
|
||||
" 210 & 0.0\\% & NaN & NaN & NaN \\\\\n",
|
||||
" 214 & 0.0\\% & NaN & NaN & NaN \\\\\n",
|
||||
" 215 & 0.0\\% & NaN & NaN & NaN \\\\\n",
|
||||
" 360 & 1.59\\% & 650116.0 & 390151.0 & 2.48 \\\\\n",
|
||||
" 450 & 0.61\\% & 938727.0 & 523665.0 & 1.33 \\\\\n",
|
||||
"\\bottomrule\n",
|
||||
"\\end{tabular}\n",
|
||||
"\n",
|
||||
"}\n",
|
||||
"\\taskslowdown{Cluster E}{\n",
|
||||
"\\begin{tabular}{rrr}\n",
|
||||
"\\begin{tabular}{rlrrr}\n",
|
||||
"\\toprule\n",
|
||||
" priority & finished\\% & m\\_slow\\_2 \\\\\n",
|
||||
" priority & finished\\% & m\\_last & m\\_all & m\\_slow\\_2 \\\\\n",
|
||||
"\\midrule\n",
|
||||
" 0 & 42.805214 & 1.439544 \\\\\n",
|
||||
" 25 & 5.344531 & 2.676136 \\\\\n",
|
||||
" 100 & 0.000000 & NaN \\\\\n",
|
||||
" 101 & 0.015918 & 1.122507 \\\\\n",
|
||||
" 103 & 0.021660 & 3.163046 \\\\\n",
|
||||
" 105 & 0.404803 & 14.750313 \\\\\n",
|
||||
" 107 & 0.000000 & NaN \\\\\n",
|
||||
" 114 & 0.000000 & NaN \\\\\n",
|
||||
" 115 & 0.027326 & 1.000000 \\\\\n",
|
||||
" 116 & 0.000000 & NaN \\\\\n",
|
||||
" 117 & 0.000000 & NaN \\\\\n",
|
||||
" 118 & 0.000000 & NaN \\\\\n",
|
||||
" 119 & 0.458256 & 10.310893 \\\\\n",
|
||||
" 170 & 0.000000 & NaN \\\\\n",
|
||||
" 200 & 1.959258 & 8.535722 \\\\\n",
|
||||
" 201 & 0.000000 & NaN \\\\\n",
|
||||
" 205 & 0.000000 & NaN \\\\\n",
|
||||
" 210 & 0.000000 & NaN \\\\\n",
|
||||
" 215 & 0.000000 & NaN \\\\\n",
|
||||
" 220 & 0.000000 & NaN \\\\\n",
|
||||
" 360 & 37.157031 & 2.873243 \\\\\n",
|
||||
" 450 & 0.548458 & 1.113283 \\\\\n",
|
||||
" 0 & 42.81\\% & 802.0 & 1127.0 & 1.44 \\\\\n",
|
||||
" 25 & 5.34\\% & 32247.0 & 38946.0 & 2.68 \\\\\n",
|
||||
" 100 & 0.0\\% & NaN & NaN & NaN \\\\\n",
|
||||
" 101 & 0.02\\% & 30603.0 & 27726.0 & 1.12 \\\\\n",
|
||||
" 103 & 0.02\\% & 76294.0 & 48552.0 & 3.16 \\\\\n",
|
||||
" 105 & 0.4\\% & 106677.0 & 64190.0 & 14.75 \\\\\n",
|
||||
" 107 & 0.0\\% & NaN & NaN & NaN \\\\\n",
|
||||
" 114 & 0.0\\% & NaN & NaN & NaN \\\\\n",
|
||||
" 115 & 0.03\\% & 67237.0 & 65369.0 & 1.00 \\\\\n",
|
||||
" 116 & 0.0\\% & NaN & NaN & NaN \\\\\n",
|
||||
" 117 & 0.0\\% & NaN & NaN & NaN \\\\\n",
|
||||
" 118 & 0.0\\% & NaN & NaN & NaN \\\\\n",
|
||||
" 119 & 0.46\\% & 62123.0 & 83322.0 & 10.31 \\\\\n",
|
||||
" 170 & 0.0\\% & NaN & NaN & NaN \\\\\n",
|
||||
" 200 & 1.96\\% & 231639.0 & 414149.0 & 8.54 \\\\\n",
|
||||
" 201 & 0.0\\% & NaN & NaN & NaN \\\\\n",
|
||||
" 205 & 0.0\\% & NaN & NaN & NaN \\\\\n",
|
||||
" 210 & 0.0\\% & NaN & NaN & NaN \\\\\n",
|
||||
" 215 & 0.0\\% & NaN & NaN & NaN \\\\\n",
|
||||
" 220 & 0.0\\% & NaN & NaN & NaN \\\\\n",
|
||||
" 360 & 37.16\\% & 611504.0 & 439280.0 & 2.87 \\\\\n",
|
||||
" 450 & 0.55\\% & 803792.0 & 824467.0 & 1.11 \\\\\n",
|
||||
"\\bottomrule\n",
|
||||
"\\end{tabular}\n",
|
||||
"\n",
|
||||
"}\n",
|
||||
"\\taskslowdown{Cluster F}{\n",
|
||||
"\\begin{tabular}{rrr}\n",
|
||||
"\\begin{tabular}{rlrrr}\n",
|
||||
"\\toprule\n",
|
||||
" priority & finished\\% & m\\_slow\\_2 \\\\\n",
|
||||
" priority & finished\\% & m\\_last & m\\_all & m\\_slow\\_2 \\\\\n",
|
||||
"\\midrule\n",
|
||||
" 0 & 45.208221 & 1.088162 \\\\\n",
|
||||
" 25 & 0.647505 & 2.230960 \\\\\n",
|
||||
" 100 & 0.000000 & NaN \\\\\n",
|
||||
" 101 & 40.296631 & 323.858714 \\\\\n",
|
||||
" 103 & 0.058418 & 1.167347 \\\\\n",
|
||||
" 105 & 0.222372 & 1.550453 \\\\\n",
|
||||
" 107 & 0.060860 & 1.012727 \\\\\n",
|
||||
" 114 & 0.006958 & 1.000000 \\\\\n",
|
||||
" 115 & 3.647104 & 5.094215 \\\\\n",
|
||||
" 116 & 0.000000 & NaN \\\\\n",
|
||||
" 117 & 0.000086 & 1.000000 \\\\\n",
|
||||
" 118 & 0.002082 & 1.000000 \\\\\n",
|
||||
" 119 & 31.354662 & 7.608799 \\\\\n",
|
||||
" 200 & 3.653528 & 5.943247 \\\\\n",
|
||||
" 201 & 0.000000 & NaN \\\\\n",
|
||||
" 360 & 7.424790 & 2.171524 \\\\\n",
|
||||
" 450 & 0.992623 & 1.021053 \\\\\n",
|
||||
" 0 & 45.21\\% & 2929.0 & 2973.0 & 1.09 \\\\\n",
|
||||
" 25 & 0.65\\% & 184518.0 & 34096.0 & 2.23 \\\\\n",
|
||||
" 100 & 0.0\\% & NaN & NaN & NaN \\\\\n",
|
||||
" 101 & 40.3\\% & 8160.0 & 10083.0 & 323.86 \\\\\n",
|
||||
" 103 & 0.06\\% & 46444.0 & 47234.0 & 1.17 \\\\\n",
|
||||
" 105 & 0.22\\% & 1111530.0 & 1173594.0 & 1.55 \\\\\n",
|
||||
" 107 & 0.06\\% & 80151.0 & 78835.0 & 1.01 \\\\\n",
|
||||
" 114 & 0.01\\% & 677.0 & 677.0 & 1.00 \\\\\n",
|
||||
" 115 & 3.65\\% & 121345.0 & 252663.0 & 5.09 \\\\\n",
|
||||
" 116 & 0.0\\% & NaN & NaN & NaN \\\\\n",
|
||||
" 117 & 0.0\\% & 15875.0 & 15875.0 & 1.00 \\\\\n",
|
||||
" 118 & 0.0\\% & 30045.0 & 25492.0 & 1.00 \\\\\n",
|
||||
" 119 & 31.35\\% & 154196.0 & 68833.0 & 7.61 \\\\\n",
|
||||
" 200 & 3.65\\% & 297168.0 & 492372.0 & 5.94 \\\\\n",
|
||||
" 201 & 0.0\\% & NaN & NaN & NaN \\\\\n",
|
||||
" 360 & 7.42\\% & 963351.0 & 569428.0 & 2.17 \\\\\n",
|
||||
" 450 & 0.99\\% & 1115783.0 & 1113282.0 & 1.02 \\\\\n",
|
||||
"\\bottomrule\n",
|
||||
"\\end{tabular}\n",
|
||||
"\n",
|
||||
"}\n",
|
||||
"\\taskslowdown{Cluster G}{\n",
|
||||
"\\begin{tabular}{rrr}\n",
|
||||
"\\begin{tabular}{rlrrr}\n",
|
||||
"\\toprule\n",
|
||||
" priority & finished\\% & m\\_slow\\_2 \\\\\n",
|
||||
" priority & finished\\% & m\\_last & m\\_all & m\\_slow\\_2 \\\\\n",
|
||||
"\\midrule\n",
|
||||
" 0 & 33.612201 & 1.138988 \\\\\n",
|
||||
" 25 & 0.233338 & 8.692558 \\\\\n",
|
||||
" 50 & 0.000000 & NaN \\\\\n",
|
||||
" 100 & 0.000000 & NaN \\\\\n",
|
||||
" 101 & 96.470338 & 19.378523 \\\\\n",
|
||||
" 103 & 0.032539 & 1.271282 \\\\\n",
|
||||
" 105 & 0.196286 & 1.000738 \\\\\n",
|
||||
" 107 & 0.000000 & NaN \\\\\n",
|
||||
" 114 & 0.000000 & NaN \\\\\n",
|
||||
" 115 & 7.633588 & 1.802068 \\\\\n",
|
||||
" 117 & 0.000000 & NaN \\\\\n",
|
||||
" 118 & 48.969072 & 3.877102 \\\\\n",
|
||||
" 119 & 0.085944 & 3.166077 \\\\\n",
|
||||
" 170 & 0.000000 & NaN \\\\\n",
|
||||
" 200 & 26.747126 & 14.573912 \\\\\n",
|
||||
" 360 & 1.618878 & 2.119524 \\\\\n",
|
||||
" 450 & 2.737219 & 1.036927 \\\\\n",
|
||||
" 0 & 33.61\\% & 3010.0 & 3317.0 & 1.14 \\\\\n",
|
||||
" 25 & 0.23\\% & 61708.0 & 12156.0 & 8.69 \\\\\n",
|
||||
" 50 & 0.0\\% & NaN & NaN & NaN \\\\\n",
|
||||
" 100 & 0.0\\% & NaN & NaN & NaN \\\\\n",
|
||||
" 101 & 96.47\\% & 133953.0 & 7448.0 & 19.38 \\\\\n",
|
||||
" 103 & 0.03\\% & 118310.0 & 112746.0 & 1.27 \\\\\n",
|
||||
" 105 & 0.2\\% & 8271.0 & 8214.0 & 1.00 \\\\\n",
|
||||
" 107 & 0.0\\% & NaN & NaN & NaN \\\\\n",
|
||||
" 114 & 0.0\\% & NaN & NaN & NaN \\\\\n",
|
||||
" 115 & 7.63\\% & 34424.0 & 56315.0 & 1.80 \\\\\n",
|
||||
" 117 & 0.0\\% & NaN & NaN & NaN \\\\\n",
|
||||
" 118 & 48.97\\% & 608526.0 & 474729.0 & 3.88 \\\\\n",
|
||||
" 119 & 0.09\\% & 124006.0 & 231395.0 & 3.17 \\\\\n",
|
||||
" 170 & 0.0\\% & NaN & NaN & NaN \\\\\n",
|
||||
" 200 & 26.75\\% & 115953.0 & 399050.0 & 14.57 \\\\\n",
|
||||
" 360 & 1.62\\% & 786594.0 & 488025.0 & 2.12 \\\\\n",
|
||||
" 450 & 2.74\\% & 1204747.0 & 1188251.0 & 1.04 \\\\\n",
|
||||
"\\bottomrule\n",
|
||||
"\\end{tabular}\n",
|
||||
"\n",
|
||||
"}\n",
|
||||
"\\taskslowdown{Cluster H}{\n",
|
||||
"\\begin{tabular}{rrr}\n",
|
||||
"\\begin{tabular}{rlrrr}\n",
|
||||
"\\toprule\n",
|
||||
" priority & finished\\% & m\\_slow\\_2 \\\\\n",
|
||||
" priority & finished\\% & m\\_last & m\\_all & m\\_slow\\_2 \\\\\n",
|
||||
"\\midrule\n",
|
||||
" 0 & 27.744380 & 1.122458 \\\\\n",
|
||||
" 19 & 0.000000 & NaN \\\\\n",
|
||||
" 25 & 1.042767 & 3.064188 \\\\\n",
|
||||
" 101 & 100.000000 & 76.438090 \\\\\n",
|
||||
" 103 & 0.481256 & 1.262067 \\\\\n",
|
||||
" 105 & 1.427256 & 4.205547 \\\\\n",
|
||||
" 107 & 0.000000 & NaN \\\\\n",
|
||||
" 115 & 5.122494 & 1.000000 \\\\\n",
|
||||
" 116 & 1.035309 & 73.447995 \\\\\n",
|
||||
" 117 & 0.000050 & 1.000000 \\\\\n",
|
||||
" 118 & 1.003331 & 1.947121 \\\\\n",
|
||||
" 119 & 0.145214 & 7.301093 \\\\\n",
|
||||
" 200 & 2.702770 & 5.798142 \\\\\n",
|
||||
" 201 & 0.000000 & NaN \\\\\n",
|
||||
" 220 & 0.000000 & NaN \\\\\n",
|
||||
" 360 & 4.425746 & 2.018441 \\\\\n",
|
||||
" 450 & 0.535389 & 1.054678 \\\\\n",
|
||||
" 0 & 27.74\\% & 5663.0 & 6211.0 & 1.12 \\\\\n",
|
||||
" 19 & 0.0\\% & NaN & NaN & NaN \\\\\n",
|
||||
" 25 & 1.04\\% & 304870.0 & 283847.0 & 3.06 \\\\\n",
|
||||
" 101 & 100.0\\% & 34063.0 & 12250.0 & 76.44 \\\\\n",
|
||||
" 103 & 0.48\\% & 272635.0 & 92894.0 & 1.26 \\\\\n",
|
||||
" 105 & 1.43\\% & 611763.0 & 393762.0 & 4.21 \\\\\n",
|
||||
" 107 & 0.0\\% & NaN & NaN & NaN \\\\\n",
|
||||
" 115 & 5.12\\% & 28907.0 & 28907.0 & 1.00 \\\\\n",
|
||||
" 116 & 1.04\\% & 633.0 & 42105.0 & 73.45 \\\\\n",
|
||||
" 117 & 0.0\\% & 656.0 & 656.0 & 1.00 \\\\\n",
|
||||
" 118 & 1.0\\% & 197687.0 & 139121.0 & 1.95 \\\\\n",
|
||||
" 119 & 0.15\\% & 139907.0 & 15558.0 & 7.30 \\\\\n",
|
||||
" 200 & 2.7\\% & 298799.0 & 470783.0 & 5.80 \\\\\n",
|
||||
" 201 & 0.0\\% & NaN & NaN & NaN \\\\\n",
|
||||
" 220 & 0.0\\% & NaN & NaN & NaN \\\\\n",
|
||||
" 360 & 4.43\\% & 838719.0 & 397301.0 & 2.02 \\\\\n",
|
||||
" 450 & 0.54\\% & 1470577.0 & 1411397.0 & 1.05 \\\\\n",
|
||||
"\\bottomrule\n",
|
||||
"\\end{tabular}\n",
|
||||
"\n",
|
||||
"}\n",
|
||||
"\\begin{tabular}{rlrrr}\n",
|
||||
"\\toprule\n",
|
||||
" priority & finished\\% & m\\_last & m\\_all & m\\_slow\\_2 \\\\\n",
|
||||
"\\midrule\n",
|
||||
" -1 & 10.62\\% & 783.0 & 0.0 & 1.097556 \\\\\n",
|
||||
" 0 & 42.86\\% & 1373.0 & 0.0 & 1.136770 \\\\\n",
|
||||
" 3 & 0.0\\% & NaN & 0.0 & NaN \\\\\n",
|
||||
" 5 & 0.0\\% & NaN & 0.0 & NaN \\\\\n",
|
||||
" 10 & 0.0\\% & NaN & 0.0 & NaN \\\\\n",
|
||||
" 19 & 0.0\\% & NaN & 0.0 & NaN \\\\\n",
|
||||
" 24 & 0.0\\% & NaN & 0.0 & NaN \\\\\n",
|
||||
" 25 & 1.31\\% & 86732.0 & 22.0 & 11.772172 \\\\\n",
|
||||
" 50 & 0.0\\% & NaN & 0.0 & NaN \\\\\n",
|
||||
" 80 & 0.0\\% & NaN & 0.0 & NaN \\\\\n",
|
||||
" 100 & 0.0\\% & NaN & 0.0 & NaN \\\\\n",
|
||||
" 101 & 5.2\\% & 65233.0 & 673.0 & 36.358841 \\\\\n",
|
||||
" 102 & 0.0\\% & NaN & 0.0 & NaN \\\\\n",
|
||||
" 103 & 1.05\\% & 8210.0 & 28.0 & 1.257530 \\\\\n",
|
||||
" 105 & 22.9\\% & 3651.0 & 616.0 & 1.733089 \\\\\n",
|
||||
" 107 & 18.51\\% & 1025.0 & 308.0 & 1.017332 \\\\\n",
|
||||
" 114 & 0.07\\% & 29364.0 & 2.0 & 1.003503 \\\\\n",
|
||||
" 115 & 1.74\\% & 10059.0 & 22.0 & 3.461721 \\\\\n",
|
||||
" 116 & 3.03\\% & 18226.0 & 71.0 & 1.102756 \\\\\n",
|
||||
" 117 & 0.0\\% & 2430.0 & 1.0 & 1.000000 \\\\\n",
|
||||
" 118 & 1.28\\% & 15072.0 & 163.0 & 3.340741 \\\\\n",
|
||||
" 119 & 4.49\\% & 19449.0 & 280.0 & 5.326446 \\\\\n",
|
||||
" 170 & 0.0\\% & NaN & 0.0 & NaN \\\\\n",
|
||||
" 197 & 0.0\\% & NaN & 0.0 & NaN \\\\\n",
|
||||
" 199 & 0.0\\% & NaN & 0.0 & NaN \\\\\n",
|
||||
" 200 & 13.54\\% & 54789.0 & 24.0 & 6.684155 \\\\\n",
|
||||
" 201 & 0.0\\% & NaN & 0.0 & NaN \\\\\n",
|
||||
" 205 & 0.0\\% & NaN & 0.0 & NaN \\\\\n",
|
||||
" 210 & 0.0\\% & NaN & 0.0 & NaN \\\\\n",
|
||||
" 214 & 0.0\\% & NaN & 0.0 & NaN \\\\\n",
|
||||
" 215 & 0.0\\% & NaN & 0.0 & NaN \\\\\n",
|
||||
" 220 & 0.0\\% & NaN & 0.0 & NaN \\\\\n",
|
||||
" 360 & 3.36\\% & 788069.0 & 42.0 & 2.241646 \\\\\n",
|
||||
" 400 & 0.0\\% & NaN & 0.0 & NaN \\\\\n",
|
||||
" 450 & 1.15\\% & 1182248.0 & 197.0 & 1.068893 \\\\\n",
|
||||
" 500 & 0.0\\% & NaN & 0.0 & NaN \\\\\n",
|
||||
"\\bottomrule\n",
|
||||
"\\end{tabular}\n",
|
||||
"\n",
|
||||
|
|
@ -297,31 +341,73 @@
|
|||
"DIR = \"/Users/maggicl/Git/bachelorThesis/task_slowdown/\"\n",
|
||||
"\n",
|
||||
"df = {}\n",
|
||||
"dftotal = None\n",
|
||||
"\n",
|
||||
"for cluster in CLUSTERS:\n",
|
||||
" print(\"\\\\taskslowdown{Cluster \" + cluster.upper() + \"}{\")\n",
|
||||
" df[cluster] = pandas.read_csv(DIR + \"/\" + cluster + \"_slowdown_table.csv\")\n",
|
||||
" df[cluster][\"m_slow_2\"] = (df[cluster][\"s_all\"] / df[cluster][\"s_last\"]) \n",
|
||||
" df[cluster][\"m_slow_2\"] = (df[cluster][\"s_all\"] / df[cluster][\"s_last\"]).round(2)\n",
|
||||
" del df[cluster][\"s_slow\"]\n",
|
||||
" del df[cluster][\"m_slow\"]\n",
|
||||
" del df[cluster][\"m_all\"]\n",
|
||||
" del df[cluster][\"m_last\"]\n",
|
||||
" del df[cluster][\"s_all\"]\n",
|
||||
" del df[cluster][\"s_last\"]\n",
|
||||
" df[cluster][\"m_all\"] = (df[cluster][\"m_all\"] / 1000000).round(0)\n",
|
||||
" df[cluster][\"m_last\"] = (df[cluster][\"m_last\"] / 1000000).round(0)\n",
|
||||
" del df[cluster][\"c_zero_end\"]\n",
|
||||
" del df[cluster][\"n_fsh\"]\n",
|
||||
" del df[cluster][\"n_non\"]\n",
|
||||
" del df[cluster][\"Unnamed: 0\"]\n",
|
||||
" df[cluster][\"finished%\"] *= 100\n",
|
||||
" print(df[cluster].to_latex(index=False))\n",
|
||||
" print(\"}\")\n"
|
||||
" \n",
|
||||
" \n",
|
||||
" df2 = df[cluster].copy()\n",
|
||||
" df[cluster][\"c\"] = df2[\"m_all\"] / df2[\"s_all\"]\n",
|
||||
" del df2[\"s_all\"]\n",
|
||||
" del df2[\"s_last\"]\n",
|
||||
" del df2[\"n_fsh\"]\n",
|
||||
" del df2[\"n_non\"]\n",
|
||||
" #del df2[\"c\"]\n",
|
||||
" df2[\"finished%\"] = (df2[\"finished%\"] * 100).round(2).astype(str) + \"%\"\n",
|
||||
" print(df2.to_latex(index=False))\n",
|
||||
" print(\"}\")\n",
|
||||
" \n",
|
||||
" if dftotal is None:\n",
|
||||
" dftotal = df[cluster]\n",
|
||||
" else:\n",
|
||||
" dftotal = dftotal.append(df[cluster])\n",
|
||||
" \n",
|
||||
"dftotal = dftotal.groupby(\"priority\").sum().reset_index()\n",
|
||||
"dftotal[\"m_slow_2\"] = (dftotal[\"s_all\"] / dftotal[\"s_last\"]) \n",
|
||||
"dftotal[\"finished%\"] = (dftotal[\"n_fsh\"]) / (dftotal[\"n_fsh\"] + dftotal[\"n_non\"])\n",
|
||||
"dftotal[\"m_last\"] = (dftotal[\"s_last\"] / (dftotal[\"n_fsh\"] * 1000000)).round(0)\n",
|
||||
"dftotal[\"m_all\"] = (dftotal[\"s_all\"] * dftotal[\"c\"] / 1000000).round(0)\n",
|
||||
"del dftotal[\"s_all\"]\n",
|
||||
"del dftotal[\"s_last\"]\n",
|
||||
"del dftotal[\"n_fsh\"]\n",
|
||||
"del dftotal[\"n_non\"]\n",
|
||||
"del dftotal[\"c\"]\n",
|
||||
"\n",
|
||||
"df2 = dftotal.copy()\n",
|
||||
"df2[\"m_all\"] = df2[\"m_all\"].round(0)\n",
|
||||
"df2[\"m_last\"] = df2[\"m_last\"].round(0)\n",
|
||||
"#del df2[\"c\"]\n",
|
||||
"df2[\"finished%\"] = (df2[\"finished%\"] * 100).round(2).astype(str) + \"%\"\n",
|
||||
"print(df2.to_latex(index=False))\n",
|
||||
"print(\"}\")\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"execution_count": 7,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"outputs": [
|
||||
{
|
||||
"ename": "NameError",
|
||||
"evalue": "name 'wc' is not defined",
|
||||
"output_type": "error",
|
||||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)",
|
||||
"\u001b[0;32m<ipython-input-7-55b47c0da7a2>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mwc\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"\u001b[0;31mNameError\u001b[0m: name 'wc' is not defined"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"wc"
|
||||
]
|
||||
|
|
|
|||
Loading…
Reference in New Issue