Minor improvements.

master
Julian M. Kunkel 2020-08-25 18:29:23 +01:00
parent cc929d7db1
commit 4231ebec31
6 changed files with 21 additions and 22 deletions

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@ -213,12 +213,12 @@ We believe this will then allow a near-online analysis of a job.
\begin{subfigure}{0.31\textwidth}
\centering
\includegraphics[width=\textwidth]{progress_4296426-out-boxplot}
\caption{Job-S} \label{fig:perf-job-S}
\caption{Job-S (runtime=15,551\,s, segments=25)} \label{fig:perf-job-S}
\end{subfigure}
\begin{subfigure}{0.31\textwidth}
\centering
\includegraphics[width=\textwidth]{progress_5024292-out-boxplot}
\caption{Job-M} \label{fig:perf-job-M}
\caption{Job-M (runtime=28,828\,s, segments=48)} \label{fig:perf-job-M}
\end{subfigure}
\begin{subfigure}{0.31\textwidth}
\centering
@ -226,7 +226,7 @@ We believe this will then allow a near-online analysis of a job.
\caption{Job-L} \label{fig:perf-job-L}
\end{subfigure}
\caption{Runtime overview for all algorithms and jobs}
\caption{Runtime of the algorithms to compute the similarity to reference jobs}
\label{fig:performance}
\end{figure}
@ -333,50 +333,49 @@ For Job-L, the two hex algorithms include with (12 and 13) a bit more diverse us
\end{subfigure}
\caption{User information for each jobs}
\caption{User information for all 100 top ranked jobs}
\label{fig:userids}
\end{figure}
\begin{figure}
\begin{subfigure}{0.31\textwidth}
\centering
\includegraphics[width=\textwidth]{job_similarities_4296426-out/jobs-nodes}
\caption{Job-S} \label{fig:nodes-job-S}
\end{subfigure}
\begin{subfigure}{0.31\textwidth}
%\begin{subfigure}{0.31\textwidth}
%\centering
%\includegraphics[width=\textwidth]{job_similarities_4296426-out/jobs-nodes}
%\caption{Job-S} \label{fig:nodes-job-S}
%\end{subfigure}
\begin{subfigure}{0.48\textwidth}
\centering
\includegraphics[width=\textwidth]{job_similarities_5024292-out/jobs-nodes}
\caption{Job-M} \label{fig:nodes-job-M}
\caption{Job-M (ref. job runs on 128 nodes)} \label{fig:nodes-job-M}
\end{subfigure}
\begin{subfigure}{0.31\textwidth}
\begin{subfigure}{0.48\textwidth}
\centering
\includegraphics[width=\textwidth]{job_similarities_7488914-out/jobs-nodes}
\caption{Job-L} \label{fig:nodes-job-L}
\caption{Job-L (reference job runs on 20 nodes)} \label{fig:nodes-job-L}
\end{subfigure}
\centering
\caption{Distribution of node counts}
\caption{Distribution of node counts (for Job-S nodes=1 in all cases)}
\label{fig:nodes-job}
\end{figure}
\begin{figure}
\begin{subfigure}{0.31\textwidth}
\centering
\includegraphics[width=\textwidth]{job_similarities_4296426-out/jobs-elapsed}
\caption{Job-S} \label{fig:runtime-job-S}
\caption{Job-S ($job=10^{4.19}$)} \label{fig:runtime-job-S}
\end{subfigure}
\begin{subfigure}{0.31\textwidth}
\centering
\includegraphics[width=\textwidth]{job_similarities_5024292-out/jobs-elapsed}
\caption{Job-M} \label{fig:runtime-job-M}
\caption{Job-M ($job=10^{4.46}$)} \label{fig:runtime-job-M}
\end{subfigure}
\begin{subfigure}{0.31\textwidth}
\centering
\includegraphics[width=\textwidth]{job_similarities_7488914-out/jobs-elapsed}
\caption{Job-L} \label{fig:runtime-job-L}
\caption{Job-L ($job=10^{5.3}$)} \label{fig:runtime-job-L}
\end{subfigure}
\centering
\caption{Distribution of elapsed runtime}
\caption{Distribution of runtime for all 100 top ranked jobs}
\label{fig:runtime-job}
\end{figure}

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@ -14,8 +14,8 @@ data = read.csv(file)
e = data %>% filter(jobs_done >= (jobs_total - 9998))
e$time_per_100k = e$elapsed / (e$jobs_done / 100000)
ggplot(e, aes(alg_name, time_per_100k, fill=alg_name)) + geom_boxplot() + theme(legend.position=c(0.2, 0.7)) + xlab("Algorithm") + ylab("Runtime in s per 100k jobs") + stat_summary(aes(label=round(..y..,0)), position = position_nudge(x = 0, y = 250), fun=mean, geom="text", size=4)
ggsave(paste(prefix, "-boxplot.png", sep=""), width=5, height=4)
ggplot(e, aes(alg_name, time_per_100k, fill=alg_name)) + geom_boxplot() + theme(legend.position=c(0.2, 0.7)) + xlab("Algorithm") + ylab("Runtime in s per 100k jobs") + stat_summary(aes(label=round(..y..,0)), position = position_nudge(x = 0, y = 200), fun=mean, geom="text", size=4) + theme(legend.title = element_blank())
ggsave(paste(prefix, "-boxplot.png", sep=""), width=4, height=4)
# Development when adding more jobs
ggplot(data, aes(x=jobs_done, y=elapsed, color=alg_name)) + geom_point() + ylab("Cummulative runtime in s") + xlab("Jobs processed") + theme(legend.position = "bottom") #+ scale_x_log10() + scale_y_log10()

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@ -122,7 +122,7 @@ for (alg_name in levels(data$alg_name)){
res.jobs = rbind(res.jobs, cbind(alg_name, metadata[metadata$jobid %in% result[, alg_name],]))
}
ggplot(res.jobs, aes(alg_name, total_nodes, fill=alg_name)) + geom_boxplot() + scale_y_continuous(trans = log2_trans(), breaks = trans_breaks("log2", function(x) 2^x), labels = trans_format("log2", math_format(2^.x))) + theme(legend.position = "none")
ggplot(res.jobs, aes(alg_name, total_nodes, fill=alg_name)) + geom_boxplot() + scale_y_continuous(trans = log2_trans(), breaks = trans_breaks("log2", function(x) 2^x), labels = trans_format("log2", math_format(2^.x))) + theme(legend.position = "none") + xlab("Algorithm")
ggsave("jobs-nodes.png", width=6, height=4)
ggplot(res.jobs, aes(alg_name, elapsed, fill=alg_name)) + geom_boxplot() + scale_y_continuous(trans = log2_trans(), breaks = trans_breaks("log10", function(x) 10^x), labels = trans_format("log10", math_format(10^.x))) + ylab("Runtime in s") + xlab("Algorithm") + theme(legend.position = "none")