bscpkgs/garlic/fig/fwi/strong_scaling.R
2021-04-07 12:44:14 +02:00

121 lines
3.3 KiB
R

library(ggplot2)
library(dplyr)
library(scales)
library(jsonlite)
args=commandArgs(trailingOnly=TRUE)
# Read the timetable from args[1]
input_file = "input.json"
if (length(args)>0) { input_file = args[1] }
# Load the dataset in NDJSON format
dataset = jsonlite::stream_in(file(input_file)) %>%
jsonlite::flatten()
# Select block size to display
useBlocksize = 1
# We only need the nblocks and time
df = select(dataset, config.blocksize, config.gitBranch, config.nodes, time) %>%
rename(
blocksize=config.blocksize,
gitBranch=config.gitBranch,
nodes=config.nodes
) %>%
filter(blocksize == useBlocksize | blocksize == 0) %>%
group_by(nodes, gitBranch) %>%
mutate(mtime = median(time)) %>%
mutate(nxmtime = mtime * nodes) %>%
mutate(nxtime = time * nodes) %>%
ungroup()
df$gitBranch = as.factor(df$gitBranch)
df$blocksize = as.factor(df$blocksize)
df$nodes = as.factor(df$nodes)
ppi=300
h=5
w=5
####################################################################
### Line plot (time)
####################################################################
png("time.png", width=w*ppi, height=h*ppi, res=ppi)
p = ggplot(df, aes(x=nodes, y=time, group=gitBranch, color=gitBranch)) +
geom_point() +
geom_line() +
theme_bw() +
labs(x="Nodes", y="Time (s)", title="FWI strong scaling",
subtitle=input_file) +
theme(plot.subtitle=element_text(size=8)) +
theme(legend.position = c(0.6, 0.75))
# Render the plot
print(p)
# Save the png image
dev.off()
####################################################################
### Line plot (timei x nodes)
####################################################################
png("nxtime.png", width=w*ppi, height=h*ppi, res=ppi)
p = ggplot(df, aes(x=nodes, y=nxtime, group=gitBranch, color=gitBranch)) +
geom_point() +
geom_line() +
theme_bw() +
labs(x="Nodes", y="Time * Nodes (s)", title="FWI strong scaling",
subtitle=input_file) +
theme(plot.subtitle=element_text(size=8)) +
theme(legend.position = c(0.15, 0.80)) +
theme(legend.text = element_text(size = 7))
# Render the plot
print(p)
# Save the png image
dev.off()
####################################################################
### Line plot (median time)
####################################################################
png("mediantime.png", width=w*ppi, height=h*ppi, res=ppi)
p = ggplot(df, aes(x=nodes, y=mtime, group=gitBranch, color=gitBranch)) +
geom_point() +
geom_line() +
theme_bw() +
labs(x="Nodes", y="Median Time (s)", title="FWI strong scaling",
subtitle=input_file) +
theme(plot.subtitle=element_text(size=8)) +
theme(legend.position = c(0.5, 0.88))
# Render the plot
print(p)
# Save the png image
dev.off()
####################################################################
### Line plot (nodes x median time)
####################################################################
png("nxmtime.png", width=w*ppi, height=h*ppi, res=ppi)
p = ggplot(df, aes(x=nodes, y=nxmtime, group=gitBranch, color=gitBranch)) +
geom_point() +
geom_line() +
theme_bw() +
labs(x="Nodes", y="Median Time * Nodes (s)", title="FWI strong scaling",
subtitle=input_file) +
theme(plot.subtitle=element_text(size=8)) +
theme(legend.position = c(0.5, 0.88))
# Render the plot
print(p)
# Save the png image
dev.off()