update

process_comms.R

@@ -46,12 +46,14 @@ my.theme <- theme_bw() +
 		   legend.background = element_rect(fill = "transparent"),
                    legend.key = element_rect(fill = "transparent", colour = NA),
 )
-my.comms <- comms.stats[comms.stats$s != 1 & comms.stats$iter < 12,]
+my.comms <- comms.stats[comms.stats$s != 1 & comms.stats$iter < 9 &
+		 	comms.stats$s < 9,]
+print(my.comms)
 plt.comms <- ggplot(data=my.comms,
-              aes(x=as.factor(iter),y=total_volume,color=abs(s),shape=ifelse(s==-1,"21","22"))) +
+              aes(x=as.factor(iter),y=total_volume,color=as.factor(abs(s)),shape=ifelse(s==-1,"21","22"))) +
 	geom_line(data=my.comms[my.comms$s != -1,],aes(group=s),linewidth=2) +
 	geom_point(data=my.comms[my.comms$s != -1,],size=10) +
-    	scale_color_gradient(name="s",low="#18730a",high="#1ee000") +
+    	scale_color_manual(name="s",values=c(`2`="#18730a",`4`="#1ee000",`8`="#00ff00")) +
 	geom_line(data=my.comms[my.comms$s == -1,],aes(group=s),color="#8a0608",linewidth=2) +
 	geom_point(data=my.comms[my.comms$s == -1,],color="#8a0608",size=10) +
  	scale_shape(solid=FALSE,name="Approach",

process_weak.R

@@ -52,9 +52,11 @@ pdfname <- "strong.pdf"
 # here rome is on a weak scalability regime
 rome <- read.csv("csv/rome.4.strong.csv")
 skylake <- read.csv("csv/skylake.4.csv")
+print("???")
 for (nodes in c(16,36,64)) {
 	rome <- rbind(rome, read.csv(paste("csv/rome",nodes,"strong","csv",sep=".")))
 	skylake <- rbind(skylake, read.csv(paste("csv/skylake",nodes,"csv",sep=".")))
+	print("???")
 }
 rome$arch = "rome"
 rome$ncpu = 128
@@ -62,6 +64,11 @@ skylake$arch = "skylake"
 skylake$ncpu = 48
 tbl <- rbind(rome,skylake)
 print("===")
+tbl <- subset(tbl, arch == "rome" & X == 144*1024 | arch =="skylake" & X == 64*1024)
+tbl <- subset(tbl, cell_ns != 16)
+tbl <- subset(tbl, s <= iter)
+tbl <- subset(tbl, iter == 38)
+print(tbl)
 
 #tbl <- rbind(tbl,tbl_64)
 
@@ -73,6 +80,7 @@ stats <- ddply(tbl,
                    summarize, med_time=median(time),
                               min_time=min(time),
                               max_time=max(time))
+print(stats)
 
 simpleCap <- function(x) {
   s <- strsplit(x, " ")[[1]]
@@ -120,15 +128,16 @@ my_labeller <- function(data) {
 stats$med_floprate <- with(stats,iter*9*X*Y/med_time/10^9)
 stats$max_floprate <- with(stats,iter*9*X*Y/max_time/10^9)
 stats$min_floprate <- with(stats,iter*9*X*Y/min_time/10^9)
-color_values <- c(`0`="#8a0608",`4`="#146e2c",`16`="#27c250",`40`="#1df557")
+color_values <- c(`0`="#8a0608",`4`="#146e2c",`16`="#27c250",`38`="#1df557")
 my.tbl <- stats#"[stats$arch == "skylake",]
 plt <- ggplot(data = my.tbl,aes(x=P,y=100*med_floprate/(P*ncpu*9/cell_ns), #iter/med_time,
 	fill=as.factor(s),color=as.factor(s))) +
 	#geom_ribbon(aes(ymin=iter/min_time,ymax=iter/max_time),alpha=0.2) +
 #	geom_ribbon(aes(ymin=min_floprate,ymax=max_floprate),alpha=0.2) +
-	geom_ribbon(aes(ymin=100*min_floprate/(P*ncpu*9/cell_ns),ymax=100*max_floprate/(P*ncpu*9/cell_ns)),alpha=0.2) +
-	geom_line() +
-	geom_point(shape=21,size=10,fill=NA) +
+#	geom_ribbon(aes(ymin=100*min_floprate/(P*ncpu*9/cell_ns),ymax=100*max_floprate/(P*ncpu*9/cell_ns)),alpha=0.2) +
+	geom_line(linewidth=4) +
+	geom_point(shape=21,stroke=3,size=8,fill="white") +
+	geom_point(shape=21,stroke=3,size=8,fill=NA) +
 	scale_y_continuous(guide=guide_axis(check.overlap=TRUE),
 			   limits=c(0,NA),
                            labels = function(x) format(x,big.mark=",",scientific=FALSE),
@@ -147,4 +156,4 @@ plt <- ggplot(data = my.tbl,aes(x=P,y=100*med_floprate/(P*ncpu*9/cell_ns), #iter
 			   values=color_values)+
 	my.theme
 
-ggsave(pdfname, plt, width=60, height=40, units="cm", device=cairo_pdf, bg="transparent")
+ggsave(pdfname, plt, width=60, height=36, units="cm", device=cairo_pdf, bg="transparent")