Fix bugs in R script when there was no data available.

Utils/benchmark/gen_comm.R

@@ -6,36 +6,39 @@ gen_comm_plot <- function(db, d_breaks, model_wanted)
 	db <- subset(db, model == model_wanted)
 
 	db <- db[db$communication_vol > 0,]
-    g <- ggplot(data=db,aes_string(x="nnode", y="communication_vol", color="algo"))
-    g <- g + geom_line()
-    g <- g + facet_wrap(npart ~ height ~ bsize, scales="free",
-                        labeller = labeller(npart = as_labeller(npart_labeller),
-                                            height = as_labeller(height_labeller),
-											bsize = as_labeller(group_size_labeller),
-                                            .default=label_both,
-                                            .multi_line=FALSE))
-
-    # Set our own colors, linetypes and point shapes.
-    g <- g + scale_color_manual(name="Algorithm",
-                                breaks=get_breaks_runtime(),
-                                labels=get_labels_runtime(),
-                                values=get_colors_runtime())
-
-    # Set X/Y labels.
-    g <- g + xlab("Number of nodes")
-    g <- g + ylab("Volume of Communication (MB)")
-
-    g <- g + scale_x_continuous(breaks=c(1, 2, 3, 4, 5, 6, 9, 12, 16, 20, 24))
-
-    # Save generated plot.
-	output <- paste(get_output_directory(), "/", model_wanted, "-comm.pdf", sep="")
-    ggsave(output, g, width=29.7, height=21, units=c("cm"), device=cairo_pdf)
+	if (nrow(db) > 0)
+	{
+		g <- ggplot(data=db,aes_string(x="nnode", y="communication_vol", color="algo", group="algo"))
+		g <- g + geom_line()
+		g <- g + facet_wrap(npart ~ height ~ bsize, scales="free",
+							labeller = labeller(npart = as_labeller(npart_labeller),
+												height = as_labeller(height_labeller),
+												bsize = as_labeller(group_size_labeller),
+												.default=label_both,
+												.multi_line=FALSE))
+
+		# Set our own colors, linetypes and point shapes.
+		g <- g + scale_color_manual(name="Algorithm",
+									breaks=get_breaks_runtime(),
+									labels=get_labels_runtime(),
+									values=get_colors_runtime())
+
+		# Set X/Y labels.
+		g <- g + xlab("Number of nodes")
+		g <- g + ylab("Volume of Communication (MB)")
+
+		g <- g + scale_x_continuous(breaks=c(1, 2, 3, 4, 5, 6, 9, 12, 16, 20, 24))
+
+		# Save generated plot.
+		output <- paste(get_output_directory(), "/", model_wanted, "-comm.pdf", sep="")
+		ggsave(output, g, width=29.7, height=21, units=c("cm"), device=cairo_pdf)
+	}
 }
 
 gen_comm <- function(dbfile)
 {
     data <- get_data_subset(dbfile, 0L, 0L, "False", get_bsize_reference())
-	data <- subset(data, algo != get_one_node_reference_algorithm() & algo != "simple-mpi")
+	data <- subset(data, algo != get_one_node_reference_algorithm() & algo != "simple-mpi" & bsize == get_bsize_reference())
 	all_model <- unique(data$model)
 	for (i in 1:length(all_model))
 	{

Utils/benchmark/gen_group_size_plots.R

@@ -2,10 +2,44 @@ library(plyr)
 library(ggplot2)
 library(scales)
 
-gen_group_size_plot <- function(d, model_wanted)
+gen_group_size_plot_comm <- function(d, model_wanted)
 {
 	d <- subset(d, model == model_wanted)
 	d$global_time <- d$global_time/1000
+	d <- d[d$communication_vol >= 0,]
+	if(nrow(d) > 0)
+	{
+	g <- ggplot(data=d,aes_string(x="bsize", y="communication_vol", color="algo", group="algo"))
+    g <- g + geom_line()
+	g <- g + facet_wrap(npart ~ height ~ nnode, scales="free",
+						labeller = labeller(npart = as_labeller(npart_labeller),
+											height = as_labeller(height_labeller),
+											nnode = as_labeller(nnode_labeller),
+											.default=label_both,
+											.multi_line=FALSE))
+
+    # Set our own colors, linetypes and point shapes.
+	g <- g + scale_color_manual(name="Algorithm",
+								breaks=get_breaks_runtime(),
+								labels=get_labels_runtime(),
+								values=get_colors_runtime())
+
+    # Set X/Y labels.
+	g <- g + xlab("bsize")
+	g <- g + ylab("Communication volume (MB)")
+
+    # Save generated plot.
+	output <- paste(get_output_directory(), "/", model_wanted, "-bsize-volume.pdf", sep="")
+	ggsave(output, g, width=29.7, height=21, units=c("cm"), device=cairo_pdf)
+	}
+}
+gen_group_size_plot_speed <- function(d, model_wanted)
+{
+	d <- subset(d, model == model_wanted)
+	d$global_time <- d$global_time/1000
+	d <- d[d$global_time > 0,]
+	if(nrow(d) > 0)
+	{
 	g <- ggplot(data=d,aes_string(x="bsize", y="global_time", color="algo", group="algo"))
     g <- g + geom_line()
 	g <- g + facet_wrap(npart ~ height ~ nnode, scales="free",
@@ -24,10 +58,12 @@ gen_group_size_plot <- function(d, model_wanted)
     # Set X/Y labels.
 	g <- g + xlab("bsize")
 	g <- g + ylab("Time (s)")
+	#g <- g + scale_x_continuous(breaks=c(8, 16, 32, 64, 128, 512, 1024, 2048, 4096))
 
     # Save generated plot.
-	output <- paste(get_output_directory(), "/", model_wanted, "-bsize.pdf", sep="")
+	output <- paste(get_output_directory(), "/", model_wanted, "-bsize-speed.pdf", sep="")
 	ggsave(output, g, width=29.7, height=21, units=c("cm"), device=cairo_pdf)
+	}
 }
 
 gen_group_size <- function(dbfile)
@@ -41,6 +77,7 @@ gen_group_size <- function(dbfile)
 	all_model <- unique(data$model)
 	for (i in 1:length(all_model))
 	{
-		gen_group_size_plot(data, all_model[i])
+		gen_group_size_plot_speed(data, all_model[i])
+		gen_group_size_plot_comm(data, all_model[i])
 	}
 }

Utils/benchmark/gen_normalized_time_plots.R

@@ -43,28 +43,31 @@ gen_normalized_time_plot <- function(db, d_breaks, model_wanted)
 	db <- subset(db, algo != get_one_node_reference_algorithm())
 	db <- db[!(is.na(db$efficiency)),]
 
-    g <- ggplot(data=db,aes_string(x="nnode", y="efficiency", color="algo"))
-    g <- g + geom_line()
-    g <- g + facet_wrap(npart ~ height, scales="free",
-                        labeller = labeller(npart = as_labeller(npart_labeller),
-                                            height = as_labeller(height_labeller),
-                                            .default=label_both,
-                                            .multi_line=FALSE))
+	if(nrow(db) > 0)
+	{
+		g <- ggplot(data=db,aes_string(x="nnode", y="efficiency", color="algo"))
+		g <- g + geom_line()
+		g <- g + facet_wrap(npart ~ height, scales="free",
+							labeller = labeller(npart = as_labeller(npart_labeller),
+												height = as_labeller(height_labeller),
+												.default=label_both,
+												.multi_line=FALSE))
 
-    # Set our own colors, linetypes and point shapes.
-    g <- g + scale_color_manual(name="Algorithm",
-                                breaks=get_breaks_runtime(),
-                                labels=get_labels_runtime(),
-                                values=get_colors_runtime())
+		# Set our own colors, linetypes and point shapes.
+		g <- g + scale_color_manual(name="Algorithm",
+									breaks=get_breaks_runtime(),
+									labels=get_labels_runtime(),
+									values=get_colors_runtime())
 
-    # Set X/Y labels.
-    g <- g + xlab("Number of nodes")
-    g <- g + ylab("Normalized time")
+		# Set X/Y labels.
+		g <- g + xlab("Number of nodes")
+		g <- g + ylab("Normalized time")
 
 
-    # Save generated plot.
-	output <- paste(get_output_directory(), "/", model_wanted, "-normalized-time.pdf", sep="")
-    ggsave(output, g, width=29.7, height=21, units=c("cm"), device=cairo_pdf)
+		# Save generated plot.
+		output <- paste(get_output_directory(), "/", model_wanted, "-normalized-time.pdf", sep="")
+		ggsave(output, g, width=29.7, height=21, units=c("cm"), device=cairo_pdf)
+	}
 }
 
 gen_normalized_time <- function(dbfile)

Utils/benchmark/gen_parallel_efficiency_plots.R

@@ -39,27 +39,30 @@ gen_pareff_plot <- function(db, d_breaks, model_wanted)
     db <- calc_parallel_efficiency(db, d_breaks)
 
 	db <- db[!(is.na(db$efficiency)),]
-    g <- ggplot(data=db,aes_string(x="nnode", y="efficiency", color="algo"))
-    g <- g + geom_line()
-    g <- g + facet_wrap(npart ~ height, scales="free",
-                        labeller = labeller(npart = as_labeller(npart_labeller),
-                                            height = as_labeller(height_labeller),
-                                            .default=label_both,
-                                            .multi_line=FALSE))
+	if(nrow(db) > 0)
+	{
+		g <- ggplot(data=db,aes_string(x="nnode", y="efficiency", color="algo"))
+		g <- g + geom_line()
+		g <- g + facet_wrap(npart ~ height, scales="free",
+							labeller = labeller(npart = as_labeller(npart_labeller),
+												height = as_labeller(height_labeller),
+												.default=label_both,
+												.multi_line=FALSE))
 
-    # Set our own colors, linetypes and point shapes.
-    g <- g + scale_color_manual(name="Algorithm",
-                                breaks=get_breaks_runtime(),
-                                labels=get_labels_runtime(),
-                                values=get_colors_runtime())
+		# Set our own colors, linetypes and point shapes.
+		g <- g + scale_color_manual(name="Algorithm",
+									breaks=get_breaks_runtime(),
+									labels=get_labels_runtime(),
+									values=get_colors_runtime())
 
-    # Set X/Y labels.
-    g <- g + xlab("Number of nodes")
-    g <- g + ylab("Parallel efficiency")
+		# Set X/Y labels.
+		g <- g + xlab("Number of nodes")
+		g <- g + ylab("Parallel efficiency")
 
-    # Save generated plot.
-	output <- paste(get_output_directory(), "/", model_wanted, "-parallel-efficiency.pdf", sep="")
-    ggsave(output, g, width=29.7, height=21, units=c("cm"), device=cairo_pdf)
+		# Save generated plot.
+		output <- paste(get_output_directory(), "/", model_wanted, "-parallel-efficiency.pdf", sep="")
+		ggsave(output, g, width=29.7, height=21, units=c("cm"), device=cairo_pdf)
+	}
 }
 
 gen_pareff <- function(dbfile)

Utils/benchmark/gen_speedup_plots.R

@@ -16,6 +16,10 @@ calc_speedup <- function(data, ref_algo)
 		}
 		else
 		{
+			if(nrow(tmp_ref) > 1)
+			{
+				print(nrow(tmp_ref))
+			}
 			data$speedup[i] <- tmp_ref$global_time / data$global_time[i]
 		}
     }