Recently, I've started to use Ubuntu 16.04 with g++ 5.3.1 and checked that my program runs 3 times slower.
Before that I've used Ubuntu 14.04, g++ 4.8.4.
I built it with the same commands: CFLAGS = -std=c++11 -Wall -O3.
My program contains cycles, filled with math calls (sin, cos, exp). You can find it here.
I've tried to compile with different optimization flags (O0, O1, O2, O3, Ofast), but in all cases the problem is reproduced (with Ofast both variants run faster, but the first runs 3 times slower still).
In my program I use libtinyxml-dev, libgslcblas. But they have the same versions in both cases and don't take any significant part in the program (according to code and callgrind profiling) in terms of performance.
I've performed profiling, but it doesn't give me any idea about why it happens.
Kcachegrind comparison (left is slower).
I've only noticed that now the program uses libm-2.23 compared to libm-2.19 with Ubuntu 14.04.
My processor is i7-5820, Haswell.
I have no idea why it becomes slower. Do you have any ideas?
P.S. Below you can find the most time consuming function:
void InclinedSum::prepare3D()
{
double buf1, buf2;
double sum_prev1 = 0.0, sum_prev2 = 0.0;
int break_idx1, break_idx2;
int arr_idx;
for(int seg_idx = 0; seg_idx < props->K; seg_idx++)
{
const Point& r = well->segs[seg_idx].r_bhp;
for(int k = 0; k < props->K; k++)
{
arr_idx = seg_idx * props->K + k;
F[arr_idx] = 0.0;
break_idx2 = 0;
for(int m = 1; m <= props->M; m++)
{
break_idx1 = 0;
for(int l = 1; l <= props->L; l++)
{
buf1 = ((cos(M_PI * (double)(m) * well->segs[k].r1.x / props->sizes.x - M_PI * (double)(l) * well->segs[k].r1.z / props->sizes.z) -
cos(M_PI * (double)(m) * well->segs[k].r2.x / props->sizes.x - M_PI * (double)(l) * well->segs[k].r2.z / props->sizes.z)) /
( M_PI * (double)(m) * tan(props->alpha) / props->sizes.x + M_PI * (double)(l) / props->sizes.z ) +
(cos(M_PI * (double)(m) * well->segs[k].r1.x / props->sizes.x + M_PI * (double)(l) * well->segs[k].r1.z / props->sizes.z) -
cos(M_PI * (double)(m) * well->segs[k].r2.x / props->sizes.x + M_PI * (double)(l) * well->segs[k].r2.z / props->sizes.z)) /
( M_PI * (double)(m) * tan(props->alpha) / props->sizes.x - M_PI * (double)(l) / props->sizes.z )
) / 2.0;
buf2 = sqrt((double)(m) * (double)(m) / props->sizes.x / props->sizes.x + (double)(l) * (double)(l) / props->sizes.z / props->sizes.z);
for(int i = -props->I; i <= props->I; i++)
{
F[arr_idx] += buf1 / well->segs[k].length / buf2 *
( exp(-M_PI * buf2 * fabs(r.y - props->r1.y + 2.0 * (double)(i) * props->sizes.y)) -
exp(-M_PI * buf2 * fabs(r.y + props->r1.y + 2.0 * (double)(i) * props->sizes.y)) ) *
sin(M_PI * (double)(m) * r.x / props->sizes.x) *
cos(M_PI * (double)(l) * r.z / props->sizes.z);
}
if( fabs(F[arr_idx] - sum_prev1) > F[arr_idx] * EQUALITY_TOLERANCE )
{
sum_prev1 = F[arr_idx];
break_idx1 = 0;
} else
break_idx1++;
if(break_idx1 > 1)
{
//std::cout << "l=" << l << std::endl;
break;
}
}
if( fabs(F[arr_idx] - sum_prev2) > F[arr_idx] * EQUALITY_TOLERANCE )
{
sum_prev2 = F[arr_idx];
break_idx2 = 0;
} else
break_idx2++;
if(break_idx2 > 1)
{
std::cout << "m=" << m << std::endl;
break;
}
}
}
}
}
Further investigation. I wrote the following simple program:
#include <cmath>
#include <iostream>
#include <chrono>
#define CYCLE_NUM 1E+7
using namespace std;
using namespace std::chrono;
int main()
{
double sum = 0.0;
auto t1 = high_resolution_clock::now();
for(int i = 1; i < CYCLE_NUM; i++)
{
sum += sin((double)(i)) / (double)(i);
}
auto t2 = high_resolution_clock::now();
microseconds::rep t = duration_cast<microseconds>(t2-t1).count();
cout << "sum = " << sum << endl;
cout << "time = " << (double)(t) / 1.E+6 << endl;
return 0;
}
I am really wondering why this simple sample program is 2.5 faster under g++ 4.8.4 libc-2.19 (libm-2.19) than under g++ 5.3.1 libc-2.23 (libm-2.23).
The compile command was:
g++ -std=c++11 -O3 main.cpp -o sum
Using other optimization flags don't change the ratio.
How can I understand who, gcc or libc, slow down the program?
