diff --git a/garlic/fig/heat/mode.R b/garlic/fig/heat/mode.R
new file mode 100644
index 0000000..66bde82
--- /dev/null
+++ b/garlic/fig/heat/mode.R
@@ -0,0 +1,81 @@
+library(ggplot2)
+library(dplyr)
+library(scales)
+library(jsonlite)
+library(viridis)
+
+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)) %>%
+	jsonlite::flatten()
+
+# We only need the nblocks and time
+df = select(dataset, config.cbs, config.rbs,
+    ctf_mode.runtime,
+    ctf_mode.task,
+    ctf_mode.dead,
+    time) %>%
+	rename(
+    cbs=config.cbs,
+    rbs=config.rbs,
+    runtime=ctf_mode.runtime,
+    task=ctf_mode.task,
+    dead=ctf_mode.dead,
+  )
+
+df$cbs = as.factor(df$cbs)
+df$rbs = as.factor(df$rbs)
+
+# Normalize the time by the median
+df = df %>%
+	mutate(runtime = runtime * 1e-9) %>%
+	mutate(dead = dead * 1e-9) %>%
+	mutate(task = task * 1e-9) %>%
+  group_by(cbs, rbs) %>%
+	mutate(median.time = median(time)) %>%
+	mutate(log.median.time = log(median.time)) %>%
+	mutate(median.dead = median(dead)) %>%
+	mutate(median.runtime = median(runtime)) %>%
+	mutate(median.task = median(task)) %>%
+  ungroup()# %>%
+
+print(df)
+
+heatmap_plot = function(df, colname, title) {
+  p = ggplot(df, aes(x=cbs, y=rbs, fill=!!ensym(colname))) +
+    geom_raster() +
+    #scale_fill_gradient(high="black", low="white") +
+    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="cbs", y="rbs",
+      title=sprintf("Heat granularity: %s", title), 
+      subtitle=input_file) +
+    theme(legend.position="bottom")
+
+  k=1
+  ggsave(sprintf("%s.png", colname), plot=p, width=4.8*k, height=5*k, dpi=300)
+  ggsave(sprintf("%s.pdf", colname), plot=p, width=4.8*k, height=5*k, dpi=300)
+}
+
+heatmap_plot(df, "median.runtime", "runtime")
+heatmap_plot(df, "median.dead", "not used")
+heatmap_plot(df, "median.task", "task")
+
+cutlevel = 0.5
+# To plot the median.time we crop the larger values:
+df_filtered = filter(df, between(median.time,
+  median(time) - (cutlevel * sd(time)),
+  median(time) + (cutlevel * sd(time))))
+
+heatmap_plot(df, "median.time", "execution time (seconds)")
+heatmap_plot(df, "log.median.time", "execution time")
diff --git a/garlic/fig/index.nix b/garlic/fig/index.nix
index ada3a2b..65034f7 100644
--- a/garlic/fig/index.nix
+++ b/garlic/fig/index.nix
@@ -47,6 +47,7 @@ in
   heat = with exp.heat; {
     granul = stdPlot ./heat/granul.R [ granul ];
     cache = customPlot ./heat/cache.R (ds.perf.stat cache.result);
+    ctf = customPlot ./heat/mode.R (ds.ctf.mode ctf.result);
   };
 
   creams = with exp.creams; {