library(ggplot2) library(dplyr) 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] } # 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.unitName, config.nodes, config.ntasksPerNode, config.cpusPerTask, size, bw) %>% rename(unitName=config.unitName) 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) ppi=300 h=8 w=12 png("bw.png", width=w*ppi, height=h*ppi, res=ppi) 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=input_file) + geom_boxplot(aes(color=unitName, group=interaction(unitName, sizeFactor))) + scale_x_continuous(trans=log2_trans()) + scale_y_log10(breaks = breaks, minor_breaks = minor_breaks) + theme_bw() + theme(legend.position = c(0.15, 0.9)) # Render the plot print(p) ## Save the png image dev.off()