From 7723404ed488c82aeeca9158594afe258a6e83eb Mon Sep 17 00:00:00 2001
From: David Hendriks <davidhendriks93@gmail.com>
Date: Fri, 21 Feb 2020 14:43:25 +0000
Subject: [PATCH] improved scaling tests
---
tests/population/scaling/plot_scaling_new.py | 40 +++++++++++++-------
tests/population/scaling/scaling_script.py | 2 +-
2 files changed, 27 insertions(+), 15 deletions(-)
diff --git a/tests/population/scaling/plot_scaling_new.py b/tests/population/scaling/plot_scaling_new.py
index 2535811ef..906a51a61 100644
--- a/tests/population/scaling/plot_scaling_new.py
+++ b/tests/population/scaling/plot_scaling_new.py
@@ -4,14 +4,13 @@ import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
import json
+import math
scaling_result_dir = 'scaling_results'
-
result_jsons = []
result_jsons.append(os.path.join(os.path.abspath(scaling_result_dir), 'david-Lenovo-IdeaPad-S340-14IWL_100_systems.json'))
-
-
+result_jsons.append(os.path.join(os.path.abspath(scaling_result_dir), 'david-Lenovo-IdeaPad-S340-14IWL_2500_systems.json'))
fig, ax1 = plt.subplots()
ax2 = ax1.twinx()
@@ -27,9 +26,9 @@ for jsonfile in result_jsons:
linear_stdev = np.std(linear_data)
cpus = []
- mp_speedups = []
- mp_efficiencies = []
- stddevs = []
+ speedups = []
+ efficiencies = []
+ stddev_speedups = []
for amt_cpus in result_data['mp']:
# Get mp data
@@ -37,39 +36,52 @@ for jsonfile in result_jsons:
mp_mean = np.mean(mp_data)
mp_stdev = np.std(mp_data)
- # Calc and append info
+ # Calc
amt_cpus = int(amt_cpus)
speedup = linear_mean/mp_mean
+ stddev_speedup = math.sqrt((linear_stdev/linear_mean)**2 + (mp_stdev/mp_mean)**2) * speedup
efficiency = speedup/int(amt_cpus)
+ # Add to lists
cpus.append(amt_cpus)
- mp_speedups.append(speedup)
- mp_efficiencies.append(efficiency)
- stddevs.append(mp_stdev)
+ efficiencies.append(efficiency)
+ speedups.append(speedup)
+ stddev_speedups.append(stddev_speedup)
# Plot
ax1.errorbar(
cpus,
- mp_speedups,
- stddevs,
+ speedups,
+ stddev_speedups,
linestyle="None",
marker="^",
label="Speed up & efficiency of {} systems".format(result_data['amt_systems']),
)
+ ax2.plot(cpus, efficiencies, alpha=0.5)
+
+ # x_position_shift += 0.1
ax1.set_title(
"Speed up ratio vs amount of cores for different amounts of systems on {}".format(
'name_testcase'
)
)
+
+ax1.plot([0, max(cpus)], [0, max(cpus)], label='100% scaling')
+
ax1.set_xlabel("Amount of cores used")
ax1.set_ylabel("Speed up ratio (time_linear/time_parallel)")
ax1.set_xlim(0, max(cpus) + 4)
-# ax1.set_ylim(0, max_speedup + 2)
-ax2.set_ylim(0, 1)
+# ax2.set_ylim(0, 1)
ax1.grid()
ax1.legend(loc=4)
plt.show()
+
+
+
+ # fig.savefig(os.path.join(img_dir, "speedup_scaling_{}.{}".format(name_testcase, "png")))
+ # fig.savefig(os.path.join(img_dir, "speedup_scaling_{}.{}".format(name_testcase, "pdf")))
+ # fig.savefig(os.path.join(img_dir, "speedup_scaling_{}.{}".format(name_testcase, "eps")))
\ No newline at end of file
diff --git a/tests/population/scaling/scaling_script.py b/tests/population/scaling/scaling_script.py
index 2e537af10..fafc8450b 100644
--- a/tests/population/scaling/scaling_script.py
+++ b/tests/population/scaling/scaling_script.py
@@ -30,7 +30,7 @@ for i in range(1, int(amount_of_cpus/stepsize) + 1 ):
amt_repeats = 5
-resolution = {'M_1': 10, 'per': 10}
+resolution = {'M_1': 50, 'per': 50}
total_systems = int(np.prod([el for el in resolution.values()]))
result_dir = 'scaling_results'
--
GitLab