# 在Python中运行C扩展比普通C更快

Python扩展,发现在
Python中执行C函数要比从C main执行C代码快2倍.

>普通C计算代码(简单3用于矩阵 – 矩阵乘法)
> Plain C main函数调用mmult()函数
> Python扩展包装器来调用mmult()函数
>所有时间都完全在C代码中发生

Python扩展 – 36us

–mmult.cpp ———-

``````#include "mmult.h"

void mmult(int32_t a[1024],int32_t b[1024],int32_t c[1024]) {

struct timeval t1, t2;
gettimeofday(&t1, NULL);

for(int i=0; i<32; i=i+1) {
for(int j=0; j<32; j=j+1) {
int32_t result=0;
for(int k=0; k<32; k=k+1) {
result+=a[i*32+k]*b[k*32+j];
}
c[i*32+j] = result;
}
}

gettimeofday(&t2, NULL);

double elapsedTime = (t2.tv_usec - t1.tv_usec) + (t2.tv_sec - t1.tv_sec)*1000000;
printf("elapsed time: %fus\n",elapsedTime);

}
``````

–mmult.h ——-

``````#include <stdint.h>

void mmult(int32_t a[1024],int32_t b[1024],int32_t c[1024]);
``````

–main.cpp ——

``````#include <stdio.h>
#include <stdlib.h>
#include <sys/time.h>
#include "mmult.h"

int main() {
int* a = (int*)malloc(sizeof(int)*1024);
int* b = (int*)malloc(sizeof(int)*1024);
int* c = (int*)malloc(sizeof(int)*1024);

for(int i=0; i<1024; i++) {
a[i]=i+1;
b[i]=i+1;
c[i]=0;
}

struct timeval t1, t2;
gettimeofday(&t1, NULL);
mmult(a,b,c);
gettimeofday(&t2, NULL);

double elapsedTime = (t2.tv_usec - t1.tv_usec) + (t2.tv_sec - t1.tv_sec)*1000000;
printf("elapsed time: %fus\n",elapsedTime);
free(a);
free(b);
free(c);

return 0;
}
``````

``````gcc -o main main.cpp mmult.cpp -O3
``````

–wrapper.cpp —–

``````#include <Python.h>
#include <numpy/arrayobject.h>
#include "mmult.h"

static PyObject* mmult_wrapper(PyObject* self, PyObject* args) {
int32_t* a;
PyArrayObject* a_obj = NULL;
int32_t* b;
PyArrayObject* b_obj = NULL;
int32_t* c;
PyArrayObject* c_obj = NULL;

int res = PyArg_ParseTuple(args, "OOO", &a_obj, &b_obj, &c_obj);

if (!res)
return NULL;

a = (int32_t*) PyArray_DATA(a_obj);
b = (int32_t*) PyArray_DATA(b_obj);
c = (int32_t*) PyArray_DATA(c_obj);

/* call function */
mmult(a,b,c);

Py_RETURN_NONE;
}

/*  define functions in module */
static PyMethodDef TheMethods[] = {
{"mmult_wrapper", mmult_wrapper, METH_VARARGS, "your c function"},
{NULL, NULL, 0, NULL}
};

static struct PyModuleDef cModPyDem = {
"mmult", "Some documentation",
-1,
TheMethods
};

PyMODINIT_FUNC
PyInit_c_module(void) {
PyObject* retval = PyModule_Create(&cModPyDem);
import_array();
return retval;
}
``````

–setup.py —–

``````import os
import numpy
from distutils.core import setup, Extension
cur = os.path.dirname(os.path.realpath(__file__))
c_module = Extension("c_module", sources=["wrapper.cpp","mmult.cpp"],include_dirs=[cur,numpy.get_include()])
setup(ext_modules=[c_module])
``````

–code.py —–

``````import c_module
import time
import numpy as np
if __name__ == "__main__":
a = np.ndarray((32,32),dtype='int32',buffer=np.linspace(1,1024,1024,dtype='int32').reshape(32,32))
b = np.ndarray((32,32),dtype='int32',buffer=np.linspace(1,1024,1024,dtype='int32').reshape(32,32))
c = np.ndarray((32,32),dtype='int32',buffer=np.zeros((32,32),dtype='int32'))

c_module.mmult_wrapper(a,b,c)
``````

``````python3.6 setup_sw.py build_ext --inplace
``````

UPDATE

Python扩展 – 27us

CPU cache效果(或
context switches
paging)可能支配计算时间(并改变它以使该时间无意义).

(我猜你在Linux / x86-64上)