Add experiments with jemalloc and CPU affinity

This commit is contained in:
2020-10-19 18:44:20 +02:00
parent ed8a6416a0
commit 1321b6a888
7 changed files with 396 additions and 34 deletions

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@@ -9,19 +9,28 @@ bs_unique = unique(df$blocksize)
nbs=length(bs_unique)
# Normalize the time by the median
D=group_by(df, blocksize) %>% mutate(tnorm = time / median(time) - 1)
D=group_by(df, blocksize) %>%
mutate(tnorm = time / median(time) - 1) # %>%
# mutate(bad = (abs(tnorm) >= 0.01)) %>%
# mutate(color = ifelse(bad,"red","black"))
ppi=300
h=5
w=5
png("box.png", width=w*ppi, height=h*ppi, res=ppi)
D$bad = cut(abs(D$tnorm), breaks=c(-Inf, 0.01, +Inf), labels=c("good", "bad"))
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(D, aes(x=blocksize, y=tnorm)) +
# Labels
labs(x="Blocksize", y="Normalized time",
title="Nbody granularity",
labs(x="Block size", y="Normalized time",
title="Nbody normalized time",
subtitle="@expResult@") +
# Center the title
@@ -43,32 +52,31 @@ p = ggplot(D, aes(x=blocksize, y=tnorm)) +
geom_hline(yintercept=c(-0.01, 0.01),
linetype="dashed", color="red")
# Render the plot
print(p)
# Save the png image
dev.off()
D=group_by(df, blocksize) %>% mutate(tnorm = time / median(time) - 1)
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)) +
labs(x="Blocksize", y="Time (s)",
title="Nbody granularity",
subtitle="@expResult@") +
geom_point(
#position=position_jitter(width=0.2, heigh=0)
shape=21, size=1.5) +
scale_x_continuous(trans=log2_trans(),
breaks=bs_unique) +
scale_y_continuous(trans=log2_trans())
# 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=bad)) +
#
# labs(x="Blocksize", y="Time (s)",
# title="Nbody granularity",
# subtitle="@expResult@") +
#
# geom_point(shape=21, size=1.5) +
# scale_color_manual(values=c("black", "red")) +
# scale_x_continuous(trans=log2_trans(),
# breaks=bs_unique) +
# scale_y_continuous(trans=log2_trans())
#
## Render the plot
#print(p)
# Save the png image
dev.off()
#dev.off()