Rodrigo Arias Mallo
92cd88e365
The input dataset is not enough to determine which script produced a given plot.
69 lines
2.4 KiB
R
69 lines
2.4 KiB
R
library(ggplot2)
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library(dplyr, warn.conflicts = FALSE)
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library(scales)
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library(jsonlite)
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args=commandArgs(trailingOnly=TRUE)
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# Read the timetable from args[1]
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input_file = "input.json"
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if (length(args)>0) { input_file = args[1] }
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if (length(args)>1) { output = args[2] } else { output = "?" }
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# Load the dataset in NDJSON format
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dataset = jsonlite::stream_in(file(input_file), verbose=FALSE) %>%
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jsonlite::flatten()
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# We only need the nblocks and time
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df = select(dataset, config.unitName, config.nodes, config.ntasksPerNode, config.cpusPerTask, config.threshold, size, bw) %>%
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rename(unitName=config.unitName) %>%
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rename(threshold=config.threshold)
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nodes = unique(df$config.nodes)
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tasksPerNode = unique(df$config.ntasksPerNode)
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cpusPerTask = unique(df$config.cpusPerTask)
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df$unitName = as.factor(df$unitName)
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df$sizeFactor = as.factor(df$size)
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df$threshold = as.factor(df$threshold)
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df = group_by(df, unitName, sizeFactor) %>%
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mutate(medianBw = median(bw)) %>%
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ungroup()
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breaks = 10^(-10:10)
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minor_breaks <- rep(1:9, 21)*(10^rep(-10:10, each=9))
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p = ggplot(data=df, aes(x=size, y=bw)) +
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labs(x="Size (bytes)", y="Bandwidth (MB/s)",
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title=sprintf("OSU bandwidth benchmark: nodes=%d tasksPerNode=%d cpusPerTask=%d",
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nodes, tasksPerNode, cpusPerTask),
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subtitle=output) +
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geom_boxplot(aes(color=threshold, group=interaction(threshold, sizeFactor))) +
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scale_x_continuous(trans=log2_trans()) +
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#scale_y_log10(breaks = breaks, minor_breaks = minor_breaks) +
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theme_bw() +
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theme(legend.position = c(0.8, 0.2))
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ppi=300
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h=4
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w=8
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ggsave("boxplot.pdf", plot=p, width=w, height=h, dpi=ppi)
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ggsave("boxplot.png", plot=p, width=w, height=h, dpi=ppi)
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p = ggplot(data=df, aes(x=size, y=medianBw)) +
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labs(x="Size (bytes)", y="Bandwidth (MB/s)",
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title=sprintf("OSU benchmark: osu_bw",
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nodes, tasksPerNode, cpusPerTask),
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subtitle=output) +
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geom_line(aes(color=threshold, linetype=threshold)) +
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geom_point(aes(color=threshold, shape=threshold)) +
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geom_hline(yintercept = 100e3 / 8, color="red") +
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annotate("text", x = 8, y = (100e3 / 8) * 0.95, label = "12.5GB/s (100Gb/s)") +
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scale_x_continuous(trans=log2_trans()) +
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#scale_y_log10(breaks = breaks, minor_breaks = minor_breaks) +
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theme_bw() +
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theme(legend.position = c(0.8, 0.2))
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ggsave("median-lines.png", plot=p, width=w, height=h, dpi=ppi)
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ggsave("median-lines.pdf", plot=p, width=w, height=h, dpi=ppi)
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