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plot_numeric.py
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plot_numeric.py
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import json
import matplotlib.pyplot as plt
import numpy as np
import matplotlib.ticker as ticker
from math import ceil, log, log2
file_list = ["pipe", "sypr", "syrk"]
file_list_15 = [x+"_15" for x in file_list]
file_list += file_list_15
file_list_full = ["result_datas/"+x+".json" for x in file_list]
x_range = [2, 3, 4, 5, 6]
x_range = [10**x for x in x_range]
plt.rc('ytick', labelsize=28) # fontsize of the tick labels
plt.rc('xtick', labelsize=21) # fontsize of the tick labels
plt.rc('legend', fontsize=14) # fontsize of the tick labels
for k in range(len(file_list_full)):
f = file_list_full[k]
with open(f, 'r') as j:
results = json.load(j)
print(results)
time_result = {}
pre_comp_time = []
for r in results:
time = r['time']
time = [float(x) for x in time]
time_result[r['method_name']] = time
if (r['method_name'] == "OURS MULTI THREAD"):
pre_comp_time = r["pre_comp"]
pre_comp_time = [float(x)/1000 for x in pre_comp_time]
multi_thread_factor = []
single_thread_factor = []
eigen_single_thread_factor = []
for i in range(5):
multi_thread_factor.append(
time_result["MKL MULTI THREAD"][i]/time_result["OURS MULTI THREAD"][i])
plt.plot(x_range, multi_thread_factor,
linewidth=3, label="Eight Threads Speedup", color="#1B9CFC")
if ("MKL SINGLE THREAD" in time_result):
for i in range(5):
single_thread_factor.append(
time_result["MKL SINGLE THREAD"][i]/time_result["OURS SINGLE THREAD"][i])
eigen_single_thread_factor.append(
time_result["EIGEN SINGLE THREAD"][i]/time_result["OURS SINGLE THREAD"][i])
plt.plot(x_range, single_thread_factor,
linewidth=3, label="Single Thread Speedup", color="#55E6C1")
plt.legend(fontsize=20)
# if "_15" in f:
# plt.yticks(list(range(0, 45, 5)))
# else:
plt.yticks(list(range(0, 19, 4)))
# plt.subplots_adjust(top=1, bottom=0, right=1, left=0,
# hspace=0, wspace=0)
ax = plt.axes()
ax.set_xscale('log')
# ax.xaxis.set_major_locator(ticker.FixedLocator(x_range))
ax.xaxis.set_minor_locator(ticker.FixedLocator([]))
ax.spines['top'].set_visible(False)
ax.spines['right'].set_visible(False)
save_plot_name = "test_result_graphs/" + \
(file_list[k].split('.')[0]) + ".pdf"
print(save_plot_name)
plt.savefig(save_plot_name, bbox_inches='tight',
pad_inches=0, dpi=200)
plt.close()
# plot the eigen difference
plt.plot(x_range, eigen_single_thread_factor,
linewidth=3, label="Single Thread Speedup Over Eigen", color="#d63031")
plt.yticks(list(range(0, 80, 10)))
ax = plt.axes()
if len(ax.lines) > 1:
plt.legend()
ax.set_xscale('log')
ax.xaxis.set_minor_locator(ticker.FixedLocator([]))
ax.yaxis.set_major_locator(ticker.FixedLocator(list(range(0, 80, 10))))
ax.spines['top'].set_visible(False)
ax.spines['right'].set_visible(False)
save_plot_name = "test_result_graphs/" + \
(file_list[k].split('.')[0]) + "_eigen.pdf"
print(save_plot_name)
plt.savefig(save_plot_name, bbox_inches='tight',
pad_inches=0, dpi=200)
plt.close()
plt.plot(x_range, pre_comp_time,
linewidth=3, label="Pre Computation Time", color="#b8e994")
# plt.legend(fontsize=16)
ax = plt.axes()
ax.set_xscale('log')
ax.xaxis.set_minor_locator(ticker.FixedLocator([]))
ax.yaxis.set_major_formatter(ticker.FormatStrFormatter('%.0e'))
ax.spines['top'].set_visible(False)
ax.spines['right'].set_visible(False)
save_plot_name = "test_result_graphs/" + \
(file_list[k].split('.')[0]) + "_pre_comp.pdf"
print(save_plot_name)
plt.savefig(save_plot_name, bbox_inches='tight',
pad_inches=0, dpi=200)
plt.close()
# plot the scalability
f = "result_datas/sypr_thread_diff.json"
with open(f, 'r') as j:
results = json.load(j)
print(results)
time_result = {}
x_range = [1, 2, 4, 8, 16]
for r in results:
time = r['time']
time = [float(x) for x in time]
if (not "EIGEN SINGLE THREAD" in r['method_name']):
time_result[r['method_name']] = time
mkl_speedup = []
ours_speedup = []
for i in range(5):
mkl_speedup.append(
time_result["MKL SINGLE THREAD"][i]/time_result["MKL MULTI THREAD"][i])
ours_speedup.append(
time_result["OURS SINGLE THREAD"][i]/time_result["OURS MULTI THREAD"][i])
plt.plot(x_range, mkl_speedup, label="MKL", color="#009688", linewidth=2)
plt.plot(x_range, ours_speedup, label="Ours", color="#FFC107", linewidth=2)
plt.legend(fontsize=20)
plt.yticks(list(range(0, 17, 2)), fontsize=20)
# plt.yticks(np.arange(0, max_y, gap))
ax = plt.axes()
# ax.set_xscale('log', basex=2)
ax.xaxis.set_minor_locator(ticker.FixedLocator([]))
ax.xaxis.set_major_locator(ticker.FixedLocator([1, 2, 4, 8, 16]))
ax.xaxis.set_major_formatter(
ticker.FuncFormatter(lambda y, _: '{:g}'.format(y)))
ax.spines['top'].set_visible(False)
ax.spines['right'].set_visible(False)
plt.savefig("test_result_graphs/spyr_thread_diff.pdf", bbox_inches='tight',
pad_inches=0, dpi=200)
plt.close()
f = "result_datas/sypr_5_thread_diff.json"
with open(f, 'r') as j:
results = json.load(j)
print(results)
time_result = {}
x_range = [1, 2, 4, 8, 16]
for r in results:
time = r['time']
time = [float(x) for x in time]
if (not "EIGEN SINGLE THREAD" in r['method_name']):
time_result[r['method_name']] = time
mkl_speedup = []
ours_speedup = []
for i in range(5):
mkl_speedup.append(
time_result["MKL SINGLE THREAD"][i]/time_result["MKL MULTI THREAD"][i])
ours_speedup.append(
time_result["OURS SINGLE THREAD"][i]/time_result["OURS MULTI THREAD"][i])
plt.plot(x_range, mkl_speedup, label="MKL", color="#009688", linewidth=2)
plt.plot(x_range, ours_speedup, label="Ours", color="#FFC107", linewidth=2)
plt.legend(fontsize=20)
plt.yticks(list(range(0, 17, 2)), fontsize=20)
# plt.yticks(np.arange(0, max_y, gap))
ax = plt.axes()
# ax.set_xscale('log', basex=2)
ax.xaxis.set_minor_locator(ticker.FixedLocator([]))
ax.xaxis.set_major_locator(ticker.FixedLocator([1, 2, 4, 8, 16]))
ax.xaxis.set_major_formatter(
ticker.FuncFormatter(lambda y, _: '{:g}'.format(y)))
ax.spines['top'].set_visible(False)
ax.spines['right'].set_visible(False)
plt.savefig("test_result_graphs/spyr_5_thread_diff.pdf", bbox_inches='tight',
pad_inches=0, dpi=200)
plt.close()
f = "result_datas/pipe_thread_diff.json"
with open(f, 'r') as j:
results = json.load(j)
print(results)
time_result = {}
x_range = [1, 2, 4, 8, 16]
for r in results:
time = r['time']
time = [float(x) for x in time]
if (not "EIGEN SINGLE THREAD" in r['method_name']):
time_result[r['method_name']] = time
mkl_speedup = []
ours_speedup = []
for i in range(5):
mkl_speedup.append(
time_result["MKL SINGLE THREAD"][i]/time_result["MKL MULTI THREAD"][i])
ours_speedup.append(
time_result["OURS SINGLE THREAD"][i]/time_result["OURS MULTI THREAD"][i])
plt.plot(x_range, mkl_speedup, label="MKL", color="#009688", linewidth=2)
plt.plot(x_range, ours_speedup, label="Ours", color="#FFC107", linewidth=2)
plt.legend(fontsize=20)
plt.yticks(list(range(0, 17, 2)), fontsize=20)
# plt.yticks(np.arange(0, max_y, gap))
ax = plt.axes()
# ax.set_xscale('log', basex=2)
ax.xaxis.set_minor_locator(ticker.FixedLocator([]))
ax.xaxis.set_major_locator(ticker.FixedLocator([1, 2, 4, 8, 16]))
ax.xaxis.set_major_formatter(
ticker.FuncFormatter(lambda y, _: '{:g}'.format(y)))
ax.spines['top'].set_visible(False)
ax.spines['right'].set_visible(False)
plt.savefig("test_result_graphs/pipe_thread_diff.pdf", bbox_inches='tight',
pad_inches=0, dpi=200)
plt.close()
f = "result_datas/pipe_5_thread_diff.json"
with open(f, 'r') as j:
results = json.load(j)
print(results)
time_result = {}
x_range = [1, 2, 4, 8, 16]
for r in results:
time = r['time']
time = [float(x) for x in time]
if (not "EIGEN SINGLE THREAD" in r['method_name']):
time_result[r['method_name']] = time
mkl_speedup = []
ours_speedup = []
for i in range(5):
mkl_speedup.append(
time_result["MKL SINGLE THREAD"][i]/time_result["MKL MULTI THREAD"][i])
ours_speedup.append(
time_result["OURS SINGLE THREAD"][i]/time_result["OURS MULTI THREAD"][i])
plt.plot(x_range, mkl_speedup, label="MKL", color="#009688", linewidth=2)
plt.plot(x_range, ours_speedup, label="Ours", color="#FFC107", linewidth=2)
plt.legend(fontsize=20)
plt.yticks(list(range(0, 17, 2)), fontsize=20)
# plt.yticks(np.arange(0, max_y, gap))
ax = plt.axes()
# ax.set_xscale('log', basex=2)
ax.xaxis.set_minor_locator(ticker.FixedLocator([]))
ax.xaxis.set_major_locator(ticker.FixedLocator([1, 2, 4, 8, 16]))
ax.xaxis.set_major_formatter(
ticker.FuncFormatter(lambda y, _: '{:g}'.format(y)))
ax.spines['top'].set_visible(False)
ax.spines['right'].set_visible(False)
plt.savefig("test_result_graphs/pipe_5_thread_diff.pdf", bbox_inches='tight',
pad_inches=0, dpi=200)
plt.close()
f = "result_datas/syrk_thread_diff.json"
with open(f, 'r') as j:
results = json.load(j)
print(results)
time_result = {}
x_range = [1, 2, 4, 8, 16]
for r in results:
time = r['time']
time = [float(x) for x in time]
if (not "EIGEN SINGLE THREAD" in r['method_name']):
time_result[r['method_name']] = time
mkl_speedup = []
ours_speedup = []
for i in range(5):
mkl_speedup.append(
time_result["MKL SINGLE THREAD"][i]/time_result["MKL MULTI THREAD"][i])
ours_speedup.append(
time_result["OURS SINGLE THREAD"][i]/time_result["OURS MULTI THREAD"][i])
plt.plot(x_range, mkl_speedup, label="MKL", color="#009688", linewidth=2)
plt.plot(x_range, ours_speedup, label="Ours", color="#FFC107", linewidth=2)
plt.legend(fontsize=20)
plt.yticks(list(range(0, 17, 2)), fontsize=20)
# plt.yticks(np.arange(0, max_y, gap))
ax = plt.axes()
# ax.set_xscale('log', basex=2)
ax.xaxis.set_minor_locator(ticker.FixedLocator([]))
ax.xaxis.set_major_locator(ticker.FixedLocator([1, 2, 4, 8, 16]))
ax.xaxis.set_major_formatter(
ticker.FuncFormatter(lambda y, _: '{:g}'.format(y)))
ax.spines['top'].set_visible(False)
ax.spines['right'].set_visible(False)
plt.savefig("test_result_graphs/syrk_thread_diff.pdf", bbox_inches='tight',
pad_inches=0, dpi=200)
plt.close()
f = "result_datas/syrk_5_thread_diff.json"
with open(f, 'r') as j:
results = json.load(j)
print(results)
time_result = {}
x_range = [1, 2, 4, 8, 16]
for r in results:
time = r['time']
time = [float(x) for x in time]
if (not "EIGEN SINGLE THREAD" in r['method_name']):
time_result[r['method_name']] = time
mkl_speedup = []
ours_speedup = []
for i in range(5):
mkl_speedup.append(
time_result["MKL SINGLE THREAD"][i]/time_result["MKL MULTI THREAD"][i])
ours_speedup.append(
time_result["OURS SINGLE THREAD"][i]/time_result["OURS MULTI THREAD"][i])
plt.plot(x_range, mkl_speedup, label="MKL", color="#009688", linewidth=2)
plt.plot(x_range, ours_speedup, label="Ours", color="#FFC107", linewidth=2)
plt.legend(fontsize=20)
plt.yticks(list(range(0, 17, 2)), fontsize=20)
# plt.yticks(np.arange(0, max_y, gap))
ax = plt.axes()
# ax.set_xscale('log', basex=2)
ax.xaxis.set_minor_locator(ticker.FixedLocator([]))
ax.xaxis.set_major_locator(ticker.FixedLocator([1, 2, 4, 8, 16]))
ax.xaxis.set_major_formatter(
ticker.FuncFormatter(lambda y, _: '{:g}'.format(y)))
ax.spines['top'].set_visible(False)
ax.spines['right'].set_visible(False)
plt.savefig("test_result_graphs/syrk_5_thread_diff.pdf", bbox_inches='tight',
pad_inches=0, dpi=200)
plt.close()
file_list = ["const", "const_2", "const_abc"]
file_list_15 = [x+"_15" for x in file_list]
file_list += file_list_15
file_list_full = ["result_datas/"+x+".json" for x in file_list]
x_range = [3, 4, 5]
x_range = [10**x for x in x_range]
for k in range(len(file_list_full)):
f = file_list_full[k]
with open(f, 'r') as j:
results = json.load(j)
print(results)
time_result = {}
pre_comp_time = []
for r in results:
time = r['time']
time = [float(x) for x in time]
time_result[r['method_name']] = time
if (r['method_name'] == "OURS MULTI THREAD"):
pre_comp_time = r["pre_comp"]
pre_comp_time = [float(x)/1000 for x in pre_comp_time]
multi_thread_factor = []
single_thread_factor = []
eigen_single_thread_factor = []
for i in range(3):
multi_thread_factor.append(
time_result["MKL MULTI THREAD"][i]/time_result["OURS MULTI THREAD"][i])
plt.plot(x_range, multi_thread_factor,
linewidth=3, label="Eight Threads Speedup", color="#1B9CFC")
if ("MKL SINGLE THREAD" in time_result):
for i in range(3):
single_thread_factor.append(
time_result["MKL SINGLE THREAD"][i]/time_result["OURS SINGLE THREAD"][i])
eigen_single_thread_factor.append(
time_result["EIGEN SINGLE THREAD"][i]/time_result["OURS SINGLE THREAD"][i])
plt.plot(x_range, single_thread_factor,
linewidth=3, label="Single Thread Speedup", color="#55E6C1")
plt.legend(fontsize=20)
# if "_15" in f:
# plt.yticks(list(range(0, 45, 5)))
# else:
plt.yticks(list(range(0, 5)))
# plt.subplots_adjust(top=1, bottom=0, right=1, left=0,
# hspace=0, wspace=0)
ax = plt.axes()
ax.set_xscale('log')
# ax.xaxis.set_major_locator(ticker.FixedLocator(x_range))
ax.xaxis.set_minor_locator(ticker.FixedLocator([]))
ax.spines['top'].set_visible(False)
ax.spines['right'].set_visible(False)
save_plot_name = "test_result_graphs/" + \
(file_list[k].split('.')[0]) + ".pdf"
print(save_plot_name)
plt.savefig(save_plot_name, bbox_inches='tight',
pad_inches=0, dpi=200)
plt.close()
# plot the eigen difference
plt.plot(x_range, eigen_single_thread_factor,
linewidth=3, label="Single Thread Speedup Over Eigen", color="#d63031")
plt.yticks(list(range(0, 30, 5)))
# plt.legend()
import math
localMax = math.ceil(max(eigen_single_thread_factor))
localMin = math.floor(min(eigen_single_thread_factor))
plt.yticks(range(localMin, localMax+1,
math.ceil((localMax + 1 - localMin)/5)))
ax = plt.axes()
ax.set_xscale('log')
ax.xaxis.set_minor_locator(ticker.FixedLocator([]))
ax.yaxis.set_major_locator(ticker.FixedLocator(list(range(0, 30, 5))))
ax.spines['top'].set_visible(False)
ax.spines['right'].set_visible(False)
save_plot_name = "test_result_graphs/" + \
(file_list[k].split('.')[0]) + "_eigen.pdf"
print(save_plot_name)
plt.savefig(save_plot_name, bbox_inches='tight',
pad_inches=0, dpi=200)
plt.close()
plt.plot(x_range, pre_comp_time,
linewidth=3, label="Pre Computation Time", color="#b8e994")
# plt.legend()
ax = plt.axes()
ax.set_xscale('log')
ax.xaxis.set_minor_locator(ticker.FixedLocator([]))
ax.yaxis.set_major_formatter(ticker.FormatStrFormatter('%.0e'))
ax.spines['top'].set_visible(False)
ax.spines['right'].set_visible(False)
save_plot_name = "test_result_graphs/" + \
(file_list[k].split('.')[0]) + "_pre_comp.pdf"
print(save_plot_name)
plt.savefig(save_plot_name, bbox_inches='tight',
pad_inches=0, dpi=200)
plt.close()