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from compyle.api import Elementwise, annotate, wrap, get_config
import numpy as np
from numpy import sin
import time
@annotate(i='int', doublep='x, y, a, b')
def axpb(i, x, y, a, b):
y[i] = a[i]*sin(x[i]) + b[i]
def setup(backend, openmp=False):
get_config().use_openmp = openmp
e = Elementwise(axpb, backend=backend)
return e
def data(n, backend):
x = np.linspace(0, 1, n)
y = np.zeros_like(x)
a = x*x
b = np.sqrt(x + 1)
return wrap(x, y, a, b, backend=backend)
def compare(m=20):
N = 2**np.arange(1, 25)
backends = [['cython', False], ['cython', True]]
try:
import pyopencl
backends.append(['opencl', False])
except ImportError as e:
pass
try:
import pycuda
backends.append(['cuda', False])
except ImportError as e:
pass
timing = []
for backend in backends:
e = setup(*backend)
times = []
for n in N:
args = data(n, backend[0])
t = []
for j in range(m):
start = time.time()
e(*args)
secs = time.time() - start
t.append(secs)
times.append(np.average(t))
timing.append(times)
return N, backends, np.array(timing)
def plot_timing(n, timing, backends):
from matplotlib import pyplot as plt
backends[1][0] = 'openmp'
for t, backend in zip(timing[1:], backends[1:]):
plt.semilogx(n, timing[0]/t, label='serial/' + backend[0], marker='+')
plt.grid()
plt.xlabel('N')
plt.ylabel('Speedup')
plt.legend()
plt.show()
if __name__ == '__main__':
n, backends, times = compare()
plot_timing(n, times, backends)
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