这是一段关于循环的代码，我已经尝试用
双重指针版本：
注：该段内容涉及IT技术。
std::vector<double> 和普通的 double* 来编写。在遍历1000万个元素时，std::vector 的版本始终比 double* 的版本快约80％; 对于几乎任何 N 值，vector 的速度都明显更快。查看 GCC STL 源代码，我没有看到 std::vector 执行任何比 double* 更高级的操作（例如，使用普通的 new[] 进行分配，operator [] 进行偏移解引用）。 本问题 也提到了这一点。你有什么想法吗？Compiler: GCC 4.6.1
Example compile line: g++ -Ofast -march=native -DNDEBUG \
-ftree-vectorizer-verbose=2 -o vector.bin \
vector.cpp -lrt
OS: CentOS 5
CPU: Opteron 8431
RAM: 128 GB
如果我使用icpc 11.1或在Xeon上运行，结果在质量上是相同的。此外，向量化转储显示只有std::vector构造函数中的填充操作被向量化了。
向量版本：
#include <vector>
#include <iostream>
#include <boost/lexical_cast.hpp>
#include "util.h"
#include "rkck_params.h"
using namespace std;
int main( int argc, char* argv[] )
{
const size_t N = boost::lexical_cast<size_t>( argv[ 1 ] );
vector<double> y_old( N );
vector<double> y_new( N );
vector<double> y_err( N );
vector<double> k0( N );
vector<double> k1( N );
vector<double> k2( N );
vector<double> k3( N );
vector<double> k4( N );
vector<double> k5( N );
const double h = 0.5;
const timespec start = clock_tick();
for ( size_t i = 0 ; i < N ; ++i )
{
y_new[ i ] = y_old[ i ]
+ h
*(
rkck::c[ 0 ]*k0[ i ]
+ rkck::c[ 2 ]*k2[ i ]
+ rkck::c[ 3 ]*k3[ i ]
+ rkck::c[ 5 ]*k5[ i ]
);
y_err[ i ] = h
*(
rkck::cdiff[ 0 ]*k0[ i ]
+ rkck::cdiff[ 2 ]*k2[ i ]
+ rkck::cdiff[ 3 ]*k3[ i ]
+ rkck::cdiff[ 4 ]*k4[ i ]
+ rkck::cdiff[ 5 ]*k5[ i ]
);
}
const timespec stop = clock_tick();
const double total_time = seconds( start, stop );
// Output
cout << "vector\t" << N << "\t" << total_time << endl;
return 0;
}
双重指针版本：
注：该段内容涉及IT技术。
#include <iostream>
#include <boost/lexical_cast.hpp>
#include "util.h"
#include "rkck_params.h"
using namespace std;
int main( int argc, char* argv[] )
{
const size_t N = boost::lexical_cast<size_t>( argv[ 1 ] );
double* y_old = new double[ N ];
double* y_new = new double[ N ];
double* y_err = new double[ N ];
double* k0 = new double[ N ];
double* k1 = new double[ N ];
double* k2 = new double[ N ];
double* k3 = new double[ N ];
double* k4 = new double[ N ];
double* k5 = new double[ N ];
const double h = 0.5;
const timespec start = clock_tick();
for ( size_t i = 0 ; i < N ; ++i )
{
y_new[ i ]
= y_old[ i ]
+ h
*(
rkck::c[ 0 ]*k0[ i ]
+ rkck::c[ 2 ]*k2[ i ]
+ rkck::c[ 3 ]*k3[ i ]
+ rkck::c[ 5 ]*k5[ i ]
);
y_err[ i ]
= h
*(
rkck::cdiff[ 0 ]*k0[ i ]
+ rkck::cdiff[ 2 ]*k2[ i ]
+ rkck::cdiff[ 3 ]*k3[ i ]
+ rkck::cdiff[ 4 ]*k4[ i ]
+ rkck::cdiff[ 5 ]*k5[ i ]
);
}
const timespec stop = clock_tick();
const double total_time = seconds( start, stop );
delete [] y_old;
delete [] y_new;
delete [] y_err;
delete [] k0;
delete [] k1;
delete [] k2;
delete [] k3;
delete [] k4;
delete [] k5;
// Output
cout << "plain\t" << N << "\t" << total_time << endl;
return 0;
}
rkck_params.h:
#ifndef RKCK_PARAMS_H
#define RKCK_PARAMS_H
namespace rkck
{
// C.f. $c_i$ in Ch. 16.2 of NR in C++, 2nd ed.
const double c[ 6 ]
= { 37.0/378.0,
0.0,
250.0/621.0,
125.0/594,
0.0,
512.0/1771.0 };
// C.f. $( c_i - c_i^* )$ in Ch. 16.2 of NR in C++, 2nd ed.
const double cdiff[ 6 ]
= { c[ 0 ] - 2825.0/27648.0,
c[ 1 ] - 0.0,
c[ 2 ] - 18575.0/48384.0,
c[ 3 ] - 13525.0/55296.0,
c[ 4 ] - 277.0/14336.0,
c[ 5 ] - 1.0/4.0 };
}
#endif
util.h:
#ifndef UTIL_H
#define UTIL_H
#include <time.h>
#include <utility>
inline timespec clock_tick()
{
timespec tick;
clock_gettime( CLOCK_REALTIME, &tick );
return tick;
}
// \cite{www.guyrutenberg.com/2007/09/22/profiling-code-using-clock_gettime}
inline double seconds( const timespec& earlier, const timespec& later )
{
double seconds_diff = -1.0;
double nano_diff = -1.0;
if ( later.tv_nsec < earlier.tv_nsec )
{
seconds_diff = later.tv_sec - earlier.tv_sec - 1;
nano_diff = ( 1.0e9 + later.tv_nsec - earlier.tv_nsec )*1.0e-9;
}
else
{
seconds_diff = later.tv_sec - earlier.tv_sec;
nano_diff = ( later.tv_nsec - earlier.tv_nsec )*1.0e-9;
}
return seconds_diff + nano_diff;
}
#endif