library(ggplot2) library(dplyr, warn.conflicts = FALSE) 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] } if (length(args)>1) { output = args[2] } else { output = "?" } # Load the dataset in NDJSON format dataset = jsonlite::stream_in(file(input_file), verbose=FALSE) %>% jsonlite::flatten() # We only need the nblocks and time df = select(dataset, config.unitName, config.nodes, config.ntasksPerNode, config.cpusPerTask, config.threshold, size, bw) %>% rename(unitName=config.unitName) %>% rename(threshold=config.threshold) nodes = unique(df$config.nodes) tasksPerNode = unique(df$config.ntasksPerNode) cpusPerTask = unique(df$config.cpusPerTask) df$unitName = as.factor(df$unitName) df$sizeFactor = as.factor(df$size) df$threshold = as.factor(df$threshold) df = group_by(df, unitName, sizeFactor) %>% mutate(medianBw = median(bw)) %>% ungroup() breaks = 10^(-10:10) minor_breaks <- rep(1:9, 21)*(10^rep(-10:10, each=9)) p = ggplot(data=df, aes(x=size, y=bw)) + labs(x="Size (bytes)", y="Bandwidth (MB/s)", title=sprintf("OSU bandwidth benchmark: nodes=%d tasksPerNode=%d cpusPerTask=%d", nodes, tasksPerNode, cpusPerTask), subtitle=output) + geom_boxplot(aes(color=threshold, group=interaction(threshold, sizeFactor))) + scale_x_continuous(trans=log2_trans()) + #scale_y_log10(breaks = breaks, minor_breaks = minor_breaks) + theme_bw() + theme(legend.position = c(0.8, 0.2)) ppi=300 h=4 w=8 ggsave("boxplot.pdf", plot=p, width=w, height=h, dpi=ppi) ggsave("boxplot.png", plot=p, width=w, height=h, dpi=ppi) p = ggplot(data=df, aes(x=size, y=medianBw)) + labs(x="Size (bytes)", y="Bandwidth (MB/s)", title=sprintf("OSU benchmark: osu_bw", nodes, tasksPerNode, cpusPerTask), subtitle=output) + geom_line(aes(color=threshold, linetype=threshold)) + geom_point(aes(color=threshold, shape=threshold)) + geom_hline(yintercept = 100e3 / 8, color="red") + annotate("text", x = 8, y = (100e3 / 8) * 0.95, label = "12.5GB/s (100Gb/s)") + scale_x_continuous(trans=log2_trans()) + #scale_y_log10(breaks = breaks, minor_breaks = minor_breaks) + theme_bw() + theme(legend.position = c(0.8, 0.2)) ggsave("median-lines.png", plot=p, width=w, height=h, dpi=ppi) ggsave("median-lines.pdf", plot=p, width=w, height=h, dpi=ppi)