105 lines
2.2 KiB
R
105 lines
2.2 KiB
R
library(ggplot2)
|
|
library(dplyr)
|
|
library(scales)
|
|
library(jsonlite)
|
|
|
|
args=commandArgs(trailingOnly=TRUE)
|
|
|
|
# Read the timetable from args[1]
|
|
input_file = "timetable.json.gz"
|
|
if (length(args)>0) { input_file = args[1] }
|
|
|
|
# Load the dataset in NDJSON format
|
|
dataset = jsonlite::stream_in(file(input_file)) %>%
|
|
jsonlite::flatten()
|
|
|
|
# We only need the cpu bind, blocksize and time
|
|
df = select(dataset, config.enableJemalloc, config.blocksize, time) %>%
|
|
rename(blocksize=config.blocksize,
|
|
jemalloc=config.enableJemalloc)
|
|
|
|
# Use the blocksize as factor
|
|
df$blocksize = as.factor(df$blocksize)
|
|
df$jemalloc = as.factor(df$jemalloc)
|
|
|
|
# Split by malloc variant
|
|
D=df %>% group_by(jemalloc, blocksize) %>%
|
|
mutate(tnorm = time / median(time) - 1)
|
|
|
|
bs_unique = unique(df$blocksize)
|
|
nbs=length(bs_unique)
|
|
|
|
|
|
print(D)
|
|
|
|
ppi=300
|
|
h=5
|
|
w=5
|
|
|
|
png("box.png", width=w*ppi, height=h*ppi, res=ppi)
|
|
#
|
|
#
|
|
#
|
|
# Create the plot with the normalized time vs blocksize
|
|
p = ggplot(data=D, aes(x=blocksize, y=tnorm)) +
|
|
|
|
# Labels
|
|
labs(x="Block size", y="Normalized time",
|
|
title="Nbody normalized time",
|
|
subtitle=input_file) +
|
|
|
|
# Center the title
|
|
#theme(plot.title = element_text(hjust = 0.5)) +
|
|
|
|
# Black and white mode (useful for printing)
|
|
#theme_bw() +
|
|
|
|
# Add the maximum allowed error lines
|
|
geom_hline(yintercept=c(-0.01, 0.01),
|
|
linetype="dashed", color="red") +
|
|
|
|
# Draw boxplots
|
|
geom_boxplot(aes(fill=freeCpu)) +
|
|
|
|
# # Use log2 scale in x
|
|
# scale_x_continuous(trans=log2_trans(),
|
|
# breaks=bs_unique) +
|
|
#
|
|
scale_y_continuous(breaks = scales::pretty_breaks(n = 10)) +
|
|
|
|
theme_bw() +
|
|
|
|
theme(plot.subtitle=element_text(size=10)) +
|
|
|
|
theme(legend.position = c(0.85, 0.85)) #+
|
|
|
|
# Place each variant group in one separate plot
|
|
|
|
|
|
|
|
# Render the plot
|
|
print(p)
|
|
|
|
## Save the png image
|
|
dev.off()
|
|
#
|
|
png("scatter.png", width=w*ppi, height=h*ppi, res=ppi)
|
|
#
|
|
## Create the plot with the normalized time vs blocksize
|
|
p = ggplot(D, aes(x=blocksize, y=time, color=freeCpu)) +
|
|
|
|
labs(x="Block size", y="Time (s)",
|
|
title="Nbody granularity",
|
|
subtitle=input_file) +
|
|
theme_bw() +
|
|
|
|
geom_point(shape=21, size=3) +
|
|
#scale_x_continuous(trans=log2_trans()) +
|
|
scale_y_continuous(trans=log2_trans())
|
|
|
|
# Render the plot
|
|
print(p)
|
|
|
|
# Save the png image
|
|
dev.off()
|