71 lines
1.9 KiB
R
71 lines
1.9 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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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.hw.cpusPerSocket,
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config.nodes,
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config.nprocs.x,
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config.nprocs.y,
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config.nprocs.z,
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config.blocksPerCpu,
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config.sizePerCpu.z,
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unit,
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time
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) %>%
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rename(nblocks=config.nblocks,
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cpusPerSocket=config.hw.cpusPerSocket,
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nodes=config.nodes,
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blocksPerCpu=config.blocksPerCpu,
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sizePerCpu.z=config.sizePerCpu.z,
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npx=config.nprocs.x,
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npy=config.nprocs.y,
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npz=config.nprocs.z
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) %>%
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mutate(axisColor=as.factor(ifelse(npx != 1, "X", ifelse(npy != 1, "Y", "Z")))) %>%
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mutate(time.sizeZ = time / sizePerCpu.z) %>%
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mutate(nblocks = as.factor(nblocks)) %>%
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mutate(blocksPerCpu = as.factor(blocksPerCpu)) %>%
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mutate(nodes = as.factor(nodes)) %>%
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mutate(unit = as.factor(unit)) %>%
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mutate(sizePerCpu.z = as.factor(sizePerCpu.z)) %>%
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mutate(timePerNprocs = time * npz) %>%
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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=7
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w=7
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p = ggplot(df, aes(x=nodes, y=time, fill=sizePerCpu.z)) +
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geom_boxplot() +
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theme_bw() +
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labs(x="Nodes", y="Time (s)", title="HPCG weak scaling in Z",
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color="Size per CPU in Z",
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subtitle=input_file) +
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theme(plot.subtitle=element_text(size=8),
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legend.position="bottom")
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ggsave("time.nodes.png", plot=p, width=w, height=h, dpi=dpi)
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ggsave("time.nodes.pdf", plot=p, width=w, height=h, dpi=dpi)
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