2022-07-19 18:05:37 +02:00
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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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library(readr)
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# Load the arguments (argv)
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args = commandArgs(trailingOnly=TRUE)
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input_file = args[1]
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df = read_delim(input_file, delim=",", comment="#") %>%
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mutate(run = as.factor(run)) %>%
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mutate(time_per_task_per_cpu = time_per_task_per_cpu * 1e9)
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2022-07-19 18:09:15 +02:00
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dpi = 96
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2022-07-19 18:05:37 +02:00
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h = 2
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w = 6
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# ---------------------------------------------------------------------
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#p = ggplot(df, aes(x=run, y=time_per_task_per_cpu)) +
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# geom_point() +
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# theme_bw() +
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# labs(
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# x = "Number of run",
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# y="get_ready_task() time (ns)",
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# title="Nanos6: get ready task time")
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p = ggplot(df, aes(x=time_per_task_per_cpu)) +
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geom_boxplot() +
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theme_bw() +
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scale_x_continuous(breaks = breaks_pretty(10)) +
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labs(
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x="Average duration per task per CPU (ns / task * CPU)",
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title="bench6.sched_get: average time to schedule N ready tasks")
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ggsave(sprintf("%s.png", input_file), plot=p, width=w, height=h, dpi=dpi)
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