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numpy_matmul_benchmark.py
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numpy_matmul_benchmark.py
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import time
import sys
import numpy as np
class Timing():
def __init__(self, name):
self._name = name
self._last_start_time = 0
self.ct = 0
self.cumulative_time = 0
self.min_time = sys.float_info.max
def start(self):
self._last_start_time = time.time()
def finish(self):
end_time = time.time()
elapsed_time = end_time - self._last_start_time
self.cumulative_time += elapsed_time
self.ct += 1
if elapsed_time < self.min_time:
self.min_time = elapsed_time
def __str__(self):
return '{}: avg {} min {}'.format(self._name,
self.cumulative_time/self.ct, self.min_time)
def benchmark(dim, iterations):
t = Timing('initialize ones')
for _ in range(iterations):
t.start()
a = np.ones((dim,dim))
t.finish()
print t
t = Timing('initialize random')
for _ in range(iterations):
t.start()
b = np.random.rand(dim,dim)
t.finish()
print t
t = Timing('add')
for _ in range(iterations):
t.start()
c = np.add(a, b)
t.finish()
print t
t = Timing('mul')
for _ in range(iterations):
t.start()
d = np.dot(a, c)
t.finish()
print t
if __name__ == '__main__':
benchmark(2500, 10)