【发布时间】:2017-11-14 18:47:56
【问题描述】:
我正在使用 Cython 版本 0.27.3 为一个简单的素性测试模块编译以下源代码,该模块包含相同算法的 python 和 cython 实现。当我将 threads 参数设置为不同的值时,尽管 GIL 已发布,但我没有看到性能提升。有什么东西阻止它并行运行吗?
有问题的函数是 cdef void _getprimes,它接受 memoryview 切片作为参数,并且应该在该切片中将所有非素数值设置为 0。
primes.pyx
#cython: boundscheck=False, wraparound=False, nonecheck=False
cimport cython
from cpython cimport array
from cython.parallel cimport parallel, prange
from libc.math cimport sqrt, ceil
from libc.stdlib cimport malloc, free
from libc.stdio cimport printf
import math
# =====================
# Python implementation
# =====================
def pyisprime(n):
"""Python implementation"""
if n < 2 or n & 1 == 0:
if n == 2:
return True
return False
for i in range(2, int(math.sqrt(n)) + 1):
if n % i == 0:
return False
return True
def pygetprimes(nums):
return [num for num in nums if pyisprime(num)]
# =====================
# Cython implementation
# =====================
cdef int _isprime(unsigned long long n) nogil:
"""Cython implementation of a simple primality check"""
cdef unsigned long long upper
cdef unsigned long long i = 3
cdef int prime = 1
if n < 2 or n & 1 == 0:
if n == 2:
return 1
return 0
upper = <unsigned long long>ceil(sqrt(<double>n))
while i <= upper:
if n % i == 0:
prime = 0
break
i += 1
return prime
def isprime(unsigned long long n):
"""Wrapper for _isprime"""
cdef int result
with nogil:
result = _isprime(n)
return result
cdef void _getprimes(unsigned long long[:] nums, int threads) nogil:
cdef unsigned long num
cdef int i = 0
with parallel(num_threads=threads):
for i in prange(nums.shape[0], schedule="dynamic"):
if _isprime(nums[i]) == 0:
nums[i] = 0
def getprimes(nums, int threads = 1):
"""Wrapper for _getprimes"""
cdef unsigned long long num
cdef unsigned long long[:] primes = array.array("Q", nums)
with nogil:
_getprimes(primes, threads)
return [num for num in primes if num != 0]
setup.py
#!/usr/bin/env python3
from distutils.core import setup
from Cython.Build import cythonize
setup(
name="primes",
ext_modules=cythonize('primes.pyx'),
)
test.py
#!/usr/bin/env python3
import functools
import random
import time
import primes
def timed(func):
def wrapped(*args, **kwargs):
start = time.time()
val = func(*args, **kwargs)
end = time.time()
print(func.__name__, end - start)
return val
return functools.wraps(func)(wrapped)
def main():
nums = [random.randint(0, 0xffffff) for _ in range(500000)]
pyfoo = timed(primes.pygetprimes)
cyfoo = timed(primes.getprimes)
x = pyfoo(nums)
y = cyfoo(nums, 1)
z = cyfoo(nums, 4)
assert x == y == z
if __name__ == "__main__":
main()
当我运行cyfoo 时,我预计将线程数从 1 增加到 4 会显示某种类型的速度提升,但事实并非如此:
[aarcher@Arch]: ~/Programming/Cython/build/lib.linux-x86_64-3.6>$ ./test.py
pygetprimes 5.11554741859436
getprimes 1.1129701137542725
getprimes 1.1306445598602295
【问题讨论】:
-
我相信您需要为 OpenMP 启用编译器标志,以便并行语句实际执行任何操作。见这里:cython.readthedocs.io/en/latest/src/userguide/…
-
非常简单!如果您继续并将其作为答案,我会接受。
标签: python multithreading performance cython