creams: add figures for scalability

garlic/fig/creams/ss.R

@@ -0,0 +1,107 @@
+library(ggplot2)
+library(dplyr)
+library(scales)
+library(jsonlite)
+
+args=commandArgs(trailingOnly=TRUE)
+
+# Read the timetable from args[1]
+input_file = "input.json"
+if (length(args)>0) { input_file = args[1] }
+
+# Load the dataset in NDJSON format
+dataset = jsonlite::stream_in(file(input_file), verbose=FALSE) %>%
+	jsonlite::flatten()
+
+# We only need some colums
+df = select(dataset, unit, config.nodes, config.gitBranch, time) %>%
+	rename(nodes=config.nodes, gitBranch=config.gitBranch)
+
+df$unit = as.factor(df$unit)
+df$nnodes = df$nodes
+df$nodes = as.factor(df$nodes)
+df$gitBranch = as.factor(df$gitBranch)
+
+# Remove the "garlic/" prefix from the gitBranch
+levels(df$gitBranch) <- substring((levels(df$gitBranch)), 8)
+
+# Compute new columns
+D=group_by(df, unit) %>%
+	mutate(tnorm = time / median(time) - 1) %>%
+	mutate(bad = ifelse(max(abs(tnorm)) >= 0.01, 1, 0)) %>%
+  mutate(variability = ifelse(bad > 0, "large", "ok")) %>%
+	mutate(mtime = median(time)) %>%
+	mutate(nmtime = mtime*nnodes) %>%
+	mutate(ntime = time*nnodes) %>%
+  ungroup() %>%
+  mutate(min_nmtime = min(nmtime)) %>%
+  mutate(rnmtime = nmtime / min_nmtime) %>%
+  mutate(rntime = ntime / min_nmtime) %>%
+  mutate(rmeff = 1.0 / rnmtime) %>%
+  mutate(reff = 1.0 / rntime) %>%
+	group_by(gitBranch) %>%
+	mutate(tmax = max(mtime)) %>%
+	mutate(speedup=tmax/time) %>%
+	mutate(eff=speedup/nnodes) %>%
+	mutate(mspeedup=tmax/mtime) %>%
+  mutate(meff=mspeedup/nnodes) %>%
+  ungroup()
+
+D$bad = as.factor(D$bad > 0)
+D$variability = as.factor(D$variability)
+
+ppi=300
+h=5
+w=5
+
+png("variability.png", width=1.5*w*ppi, height=h*ppi, res=ppi)
+p = ggplot(data=D, aes(x=nodes, y=tnorm, color=variability)) +
+	theme_bw() +
+	theme(plot.subtitle=element_text(size=8)) +
+	# Add the maximum allowed error lines
+	geom_hline(yintercept=c(-0.01, 0.01),
+		linetype="dashed", color="gray") +
+	# Draw boxplots
+	geom_boxplot(aes(fill=gitBranch)) +
+	scale_color_manual(values=c("brown", "black")) +
+	# Labels
+	labs(x="Nodes", y="Normalized time", title="Creams strong scaling",
+    subtitle=input_file)
+print(p)
+dev.off()
+
+png("time.png", width=w*1.5*ppi, height=h*ppi, res=ppi)
+p = ggplot(D, aes(x=nodes, y=mtime, color=gitBranch)) +
+	theme_bw() +
+	theme(plot.subtitle=element_text(size=8)) +
+	geom_line(aes(group=gitBranch)) +
+	#geom_point() +
+	geom_point(aes(shape=variability), size=3) +
+	scale_shape_manual(values=c(21, 19)) +
+  #  position=position_dodge(width=0.3)) +
+	#scale_x_continuous(trans=log2_trans()) +
+	scale_y_continuous(trans=log2_trans()) +
+	labs(x="Nodes", y="Time (s)",
+    title="Creams strong scaling (lower is better)",
+    subtitle=input_file)
+print(p)
+dev.off()
+
+png("refficiency.png", width=w*1.5*ppi, height=h*ppi, res=ppi)
+p = ggplot(D, aes(x=nodes, y=rmeff, color=gitBranch)) +
+	theme_bw() +
+	theme(plot.subtitle=element_text(size=8)) +
+	geom_line(aes(group=gitBranch)) +
+	geom_point(aes(shape=variability), size=3) +
+	#geom_boxplot(aes(y=reff),
+  #  position=position_dodge(width=0.0)) +
+	scale_shape_manual(values=c(21, 19)) +
+	#geom_point(aes(y=rntime),
+  #  position=position_dodge(width=0.3)) +
+	#scale_x_continuous(trans=log2_trans()) +
+	#scale_y_continuous(trans=log2_trans()) +
+	labs(x="Nodes", y="Relative efficiency (to best)",
+    title="Creams strong scaling (higher is better)",
+    subtitle=input_file)
+print(p)
+dev.off()

garlic/fig/index.nix

@@ -54,4 +54,11 @@ in
       dataset = test;
     };
   };
+
+  creams = {
+    ss = with ds.creams; rPlot {
+      script = ./creams/ss.R;
+      dataset = ss.all;
+    };
+  };
 }