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import numpy as np
import time
import md_simple
import md_nnps
from compyle.config import get_config
def solve(n, backend, solver_algo, tf=0.5, dt=0.02, use_count_sort=False):
solver = solver_algo(n, backend=backend.replace("_omp", ""))
start = time.time()
solver.solve(tf, dt)
end = time.time()
print("Time taken for backend = %s, N = %i is %g secs" %
(backend, n, (end - start)))
return end - start
def compare(backends, n_list, solver_algo, niter=3):
t_list = {b: [] for b in backends}
speedups = {b: [] for b in backends}
for n in n_list:
print("Running for N = %i" % n)
for backend in backends:
if "omp" in backend:
get_config().use_openmp = True
t = 1e9
for it in range(niter):
t = min(t, solve(n, backend, solver_algo))
t_list[backend].append(t)
if "omp" in backend:
get_config().use_openmp = False
if 'cython' in backends:
for backend in backends:
for i, n in enumerate(n_list):
speedups[backend].append(
t_list["cython"][i] / t_list[backend][i])
else:
speedups = None
return speedups, t_list
def compare_implementations(backend, n_list, niter=3):
import matplotlib.pyplot as plt
sp, nnps_tlist = compare([backend], n_list,
md_nnps.MDSolver, niter=niter)
sp, simple_tlist = compare([backend], n_list,
md_simple.MDSolver, niter=niter)
speedup = [simple_tlist[backend][i] / nnps_tlist[backend][i]
for i in range(len(n_list))]
plt.loglog(n_list, nnps_tlist[backend], 'x-', label="Linear")
plt.loglog(n_list, simple_tlist[backend], 'x-', label="Simple")
plt.xlabel("Number of particles")
plt.ylabel("Time (secs)")
plt.legend()
plt.grid(True)
plt.savefig("time_comp_impl.png", dpi=300)
plt.clf()
plt.loglog(n_list, speedup, 'x-')
plt.xlabel("Number of particles")
plt.ylabel("Speedup")
plt.grid(True)
plt.savefig("speedup_comp_impl.png", dpi=300)
def plot(n_list, speedups, t_list, label):
backend_label_map = {'cython': 'Cython', 'cython_omp': 'OpenMP',
'opencl': 'OpenCL', 'cuda': 'CUDA'}
import matplotlib.pyplot as plt
plt.figure()
if speedups:
for backend, arr in speedups.items():
if backend == "cython":
continue
plt.semilogx(n_list, arr, 'x-', label=backend_label_map[backend])
plt.xlabel("Number of particles")
plt.ylabel("Speedup")
plt.legend()
plt.grid(True)
plt.savefig("%s_speedup_%s.png" %
(label, "_".join(speedups.keys())), dpi=300)
plt.clf()
for backend, arr in t_list.items():
plt.loglog(n_list, arr, 'x-', label=backend_label_map[backend])
plt.xlabel("Number of particles")
plt.ylabel("Time (secs)")
plt.legend()
plt.grid(True)
plt.savefig("%s_time_%s.png" % (label, "_".join(t_list.keys())), dpi=300)
if __name__ == "__main__":
from argparse import ArgumentParser
p = ArgumentParser()
p.add_argument(
'-c', '--comparison', action='store', dest='comp', default='gpu_comp',
choices=['gpu_comp', 'omp_comp', 'comp_algo'],
help='Choose the comparison.'
)
p.add_argument(
'--nnps', action='store', dest='nnps', default='linear',
choices=['linear', 'simple'],
help='Choose algorithm.'
)
p.add_argument(
'--use-double', action='store_true', dest='use_double',
default=False, help='Use double precision on the GPU.'
)
o = p.parse_args()
get_config().use_double = o.use_double
solver_algo = (md_nnps.MDNNPSSolver if o.nnps == 'linear'
else md_simple.MDSolver)
n_list = [10000 * (2 ** i) for i in range(10)] if o.nnps == 'linear' else \
[500 * (2 ** i) for i in range(8)]
if o.comp == "gpu_comp":
backends = ["opencl", "cuda", "cython"]
print("Running for", n_list)
speedups, t_list = compare(backends, n_list, solver_algo)
plot(n_list, speedups, t_list, o.nnps)
elif o.comp == "omp_comp":
backends = ["cython_omp", "cython"]
print("Running for", n_list)
speedups, t_list = compare(backends, n_list, solver_algo)
plot(n_list, speedups, t_list, o.nnps)
elif o.comp == "comp_algo":
backend = "cython"
n_list = [500, 1000, 2000, 4000, 8000, 16000, 32000]
print("Running for", n_list)
compare_implementations(backend, n_list)
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