creams: add granularity experiment with 16 nodes

garlic/fig/creams/granularity16.R

@@ -0,0 +1,136 @@
+library(ggplot2)
+library(dplyr, warn.conflicts = FALSE)
+library(scales)
+library(jsonlite)
+library(viridis, warn.conflicts = FALSE)
+library(stringr)
+
+args = commandArgs(trailingOnly=TRUE)
+
+# Set the input dataset if given in argv[1], or use "input" as default
+if (length(args)>0) { input_file = args[1] } else { input_file = "input" }
+if (length(args)>1) { output = args[2] } else { output = "?" }
+
+df = jsonlite::stream_in(file(input_file), verbose=FALSE) %>%
+
+  jsonlite::flatten() %>%
+
+  select(unit,
+    config.nodes,
+    config.gitBranch,
+    config.granul,
+    config.iterations,
+    config.sizeFactor,
+    config.nz,
+    time,
+    total_time) %>%
+
+  rename(nodes=config.nodes,
+    gitBranch=config.gitBranch,
+    granul=config.granul,
+    sizeFactor=config.sizeFactor,
+    nz=config.nz,
+    iterations=config.iterations) %>%
+
+  # Remove the "garlic/" prefix from the gitBranch
+  mutate(branch = str_replace(gitBranch, "garlic/", "")) %>%
+
+  # Computations  before converting to factor
+  mutate(time.nodes = time * nodes) %>%
+  mutate(time.elem = time / sizeFactor) %>%
+  mutate(time.nodes.iter = time.nodes / iterations) %>%
+
+  # Convert to factors
+  mutate(unit = as.factor(unit)) %>%
+  mutate(nodes = as.factor(nodes)) %>%
+  mutate(gitBranch = as.factor(gitBranch)) %>%
+  mutate(granul = as.factor(granul)) %>%
+  mutate(iterations = as.factor(iterations)) %>%
+  mutate(sizeFactor = as.factor(sizeFactor)) %>%
+  mutate(nz = as.factor(nz)) %>%
+  mutate(unit = as.factor(unit)) %>%
+
+  # Compute median times
+  group_by(unit) %>%
+  mutate(median.time = median(time)) %>%
+  mutate(median.time.nodes = median(time.nodes)) %>%
+  mutate(median.time.elem = median(time.elem)) %>%
+  mutate(normalized.time = time / median.time - 1) %>%
+  mutate(log.median.time = log(median.time)) %>%
+  mutate(log.median.time.elem = log(median.time.elem)) %>%
+  mutate(median.time.nodes.iter = median(time.nodes.iter)) %>%
+  ungroup() %>%
+  group_by(sizeFactor) %>%
+  mutate(optimal.granul = (median.time.elem == min(median.time.elem))) %>%
+  ungroup()
+
+dfopt = df %>% filter(optimal.granul == TRUE)
+
+dpi = 300
+h = 4
+w = 10
+
+# ---------------------------------------------------------------------
+
+#p = ggplot(df, aes(x=sizeFactor, y=normalized.time, fill=granul, color=iterations)) +
+#  geom_boxplot() +
+#  geom_hline(yintercept=c(-0.01, 0.01), linetype="dashed", color="red") +
+#  theme_bw() +
+#  facet_wrap(branch ~ .) +
+#  labs(x="nodes", y="Normalized time",
+#    title="Creams strong scaling: normalized time", 
+#    subtitle=output) + 
+#  theme(plot.subtitle=element_text(size=8))
+#
+#ggsave("normalized.time.png", plot=p, width=w, height=h, dpi=dpi)
+#ggsave("normalized.time.pdf", plot=p, width=w, height=h, dpi=dpi)
+
+# ---------------------------------------------------------------------
+
+p = ggplot(df, aes(x=granul, y=time.elem, color=branch)) +
+  geom_point(shape=21, size=3) +
+#  geom_line(aes(y=median.time, group=gitBranch)) +
+  theme_bw() +
+  facet_wrap(sizeFactor ~ ., labeller=label_both, nrow=1) +
+  labs(x="Granularity", y="Time / k (s)",
+    #title="Creams size: time per object", 
+    subtitle=output) + 
+  theme(plot.subtitle=element_text(size=8, family="mono"),
+    legend.position="bottom")
+
+ggsave("time.png", plot=p, width=w, height=h, dpi=dpi)
+ggsave("time.pdf", plot=p, width=w, height=h, dpi=dpi)
+
+# ---------------------------------------------------------------------
+
+p = ggplot(df, aes(x=granul, y=median.time.elem, color=sizeFactor)) +
+  geom_line(aes(group=sizeFactor)) +
+  geom_point(data=dfopt, aes(x=granul, y=median.time.elem)) +
+  theme_bw() +
+  labs(x="Granularity", y="Time / k (s)",
+    color="Size factor k",
+    subtitle=output) + 
+  theme(plot.subtitle=element_text(size=8, family="mono"),
+    legend.position="bottom")
+
+ggsave("median.time.png", plot=p, width=5, height=5, dpi=dpi)
+ggsave("median.time.pdf", plot=p, width=5, height=5, dpi=dpi)
+
+# ---------------------------------------------------------------------
+
+p = ggplot(df, aes(x=granul, y=sizeFactor, fill=log.median.time.elem)) +
+  geom_raster() +
+  scale_fill_viridis(option="plasma") +
+  coord_fixed() +
+  theme_bw() +
+  theme(axis.text.x=element_text(angle = -45, hjust = 0)) +
+  theme(plot.subtitle=element_text(size=8)) +
+  #guides(fill = guide_colorbar(barwidth=15, title.position="top")) +
+  guides(fill = guide_colorbar(barwidth=12, title.vjust=0.8)) +
+  labs(x="Granularity", y="Size factor", fill="Time / k (s)", subtitle=output) +
+  theme(plot.subtitle=element_text(size=8, family="mono"),
+    legend.position="bottom")
+
+k=1
+ggsave("heatmap.png", plot=p, width=4.8*k, height=5*k, dpi=300)
+ggsave("heatmap.pdf", plot=p, width=4.8*k, height=5*k, dpi=300)

garlic/fig/index.nix

@@ -57,6 +57,7 @@ in
     ss = stdPlot ./creams/ss.R [ ss ];
     granularity = stdPlot ./creams/granularity.R [ granularity ];
     size = stdPlot ./creams/size.R [ size ];
+    granularity16 = stdPlot ./creams/granularity16.R [ granularity16 ];
 
     # Extended version (we could use another R script for those plots
     big.ss = stdPlot ./creams/ss.R [ big.ss ];