Comments (2)
@Xarthisius I think you and possibly @cindytsai have looked at this. Would you be able to take this on and look at producing some simple scaling plots, even if they don't demonstrate great performance?
from yt-4.0-paper.
I found something I did on 03/08/2023:
import time
import yt
from yt.config import ytcfg
yt.enable_parallelism()
ds = yt.load("/dpool/kacperk/second_star/DD0182/DD0182")
ds.index
start_time = time.time()
v, c = ds.find_max(("gas", "density"))
if yt.is_root():
print(v, c)
max_time = time.time() - start_time
print("--- (max) %.2f seconds ---" % max_time)
start_time = time.time()
p = yt.ProjectionPlot(ds, "z", ("gas", "density"), width=(1.0, 'unitary'))
if yt.is_root():
prj_time = time.time() - start_time
print("--- (prj) %.2f seconds ---" % prj_time)
nprocs = int(ytcfg.get("yt", "internals", "global_parallel_size"))
with open("results.csv", "a") as fp:
fp.write("%i,%.2f,%.2f\n" % (nprocs, max_time , prj_time))
p.save()
Run via:
#!/bin/bash
for i in {1..10}; do
for n in 1 2 4 8 16 32 ; do
mpiexec -n $n -bind-to core python canary.py --parallel
done
done
on Intel(R) Xeon(R) CPU E5-2650 v3 @ 2.30GHz
(20 cores, but 40 with HT)
Results:
results.csv
You explained to me why max
was so slow and not scaling on slack, but it's lost in +30d history and I don't remember.
from yt-4.0-paper.
Related Issues (20)
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from yt-4.0-paper.