forked from rarias/bscpkgs
70 lines
2.2 KiB
R
70 lines
2.2 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,
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config.unitName,
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config.nodes,
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config.ntasksPerNode,
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config.cpusPerTask,
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config.PSM2_MQ_EAGER_SDMA_SZ,
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config.PSM2_MTU,
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size, bw, config.iterations) %>%
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rename(unitName=config.unitName,
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iterations=config.iterations,
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PSM2_MQ_EAGER_SDMA_SZ.val=config.PSM2_MQ_EAGER_SDMA_SZ,
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PSM2_MTU.val=config.PSM2_MTU) %>%
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mutate(bw = bw / 1000.0)
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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$size)
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df$sizeKB = df$size / 1024
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df$PSM2_MQ_EAGER_SDMA_SZ = as.factor(df$PSM2_MQ_EAGER_SDMA_SZ.val)
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df$PSM2_MTU = as.factor(df$PSM2_MTU.val)
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iterations = unique(df$iterations)
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df = group_by(df, unitName, sizeFactor) %>%
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mutate(median.bw = 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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ppi=300
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h=3
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w=6
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p = ggplot(data=df, aes(x=sizeKB, y=bw)) +
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geom_vline(aes(xintercept = PSM2_MQ_EAGER_SDMA_SZ.val/1024), color="blue") +
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geom_vline(aes(xintercept = PSM2_MTU.val/1024), color="red") +
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labs(x="Message size (KiB)", y="Bandwidth (GB/s)",
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#title=sprintf("OSU benchmark: osu_bw --iterations %d", iterations),
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subtitle=output) +
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geom_point(shape=21, size=2) +
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#annotate("text", x = 10.2, y = 8.5e3, label = "MTU = 10KB", color="red", hjust=0) +
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facet_wrap(vars(PSM2_MTU), nrow=3, labeller = "label_both") +
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#scale_x_continuous(breaks = unique(df$sizeKB), minor_breaks=NULL) +
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scale_x_continuous(n.breaks = 12) +
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theme_bw() +
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theme(plot.subtitle = element_text(size=8, family="mono"))
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ggsave("bw.png", plot=p, width=w, height=h, dpi=ppi)
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ggsave("bw.pdf", plot=p, width=w, height=h, dpi=ppi)
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