Rodrigo Arias Mallo
92cd88e365
The input dataset is not enough to determine which script produced a given plot.
64 lines
1.7 KiB
R
64 lines
1.7 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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library(viridis, warn.conflicts = FALSE)
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args = commandArgs(trailingOnly=TRUE)
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if (length(args)>0) { input_file = args[1] } else { input_file = "input" }
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if (length(args)>1) { output = args[2] } else { output = "?" }
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df = jsonlite::stream_in(file(input_file), verbose=FALSE) %>%
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jsonlite::flatten() %>%
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select(config.nblocks,
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config.ncomms,
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config.hw.cpusPerSocket,
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config.blocksPerCpu,
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unit,
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time) %>%
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rename(nblocks=config.nblocks,
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ncomms=config.ncomms,
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blocksPerCpu=config.blocksPerCpu) %>%
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mutate(nblocks = as.factor(nblocks)) %>%
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mutate(blocksPerCpu = as.factor(blocksPerCpu)) %>%
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mutate(unit = as.factor(unit)) %>%
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group_by(unit) %>%
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mutate(median.time = median(time)) %>%
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mutate(normalized.time = time / median.time - 1) %>%
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mutate(log.median.time = log(median.time)) %>%
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ungroup()
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dpi=300
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h=5
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w=5
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p = ggplot(df, aes(x=blocksPerCpu, y=normalized.time)) +
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geom_boxplot() +
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geom_hline(yintercept=c(-0.01, 0.01), linetype="dashed", color="red") +
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theme_bw() +
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labs(x="Blocks per CPU", y="Normalized time", title="HPCG granularity: normalized time",
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subtitle=output) +
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theme(plot.subtitle=element_text(size=8))
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ggsave("normalized.time.png", plot=p, width=w, height=h, dpi=dpi)
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ggsave("normalized.time.pdf", plot=p, width=w, height=h, dpi=dpi)
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p = ggplot(df, aes(x=blocksPerCpu, y=time)) +
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geom_point(shape=21, size=3) +
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theme_bw() +
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labs(x="Blocks per CPU", y="Time (s)", title="HPCG granularity: time",
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subtitle=output) +
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theme(plot.subtitle=element_text(size=8))
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ggsave("time.png", plot=p, width=w, height=h, dpi=dpi)
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ggsave("time.pdf", plot=p, width=w, height=h, dpi=dpi)
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