Reputation: 5575
I was wondering how I could turn this C code into C++ for memory alignment.
float *pResult = (float*) _aligned_malloc(length * sizeof(float), 16);
I did look here and then I tried this
float *pResult = (float*) __attribute__((aligned(16)));
and this
float *pResult = __attribute__((aligned(16)));
but both gave similar errors.
error: expected primary-expression before '__attribute__'|
error: expected ',' or ';' before '__attribute__'|
Complete code
#include "stdafx.h"
#include <xmmintrin.h> // Need this for SSE compiler intrinsics
#include <math.h> // Needed for sqrt in CPU-only version
#include "stdio.h"
int main(int argc, char* argv[])
{
printf("Starting calculation...\n");
const int length = 64000;
// We will be calculating Y = Sin(x) / x, for x = 1->64000
// If you do not properly align your data for SSE instructions, you may take a huge performance hit.
float *pResult = (float*) __attribute__((aligned(16))); // align to 16-byte for SSE
__m128 x;
__m128 xDelta = _mm_set1_ps(4.0f); // Set the xDelta to (4,4,4,4)
__m128 *pResultSSE = (__m128*) pResult;
const int SSELength = length / 4;
for (int stress = 0; stress < 100000; stress++) // lots of stress loops so we can easily use a stopwatch
{
#define TIME_SSE // Define this if you want to run with SSE
#ifdef TIME_SSE
x = _mm_set_ps(4.0f, 3.0f, 2.0f, 1.0f); // Set the initial values of x to (4,3,2,1)
for (int i=0; i < SSELength; i++)
{
__m128 xSqrt = _mm_sqrt_ps(x);
// Note! Division is slow. It's actually faster to take the reciprocal of a number and multiply
// Also note that Division is more accurate than taking the reciprocal and multiplying
#define USE_DIVISION_METHOD
#ifdef USE_FAST_METHOD
__m128 xRecip = _mm_rcp_ps(x);
pResultSSE[i] = _mm_mul_ps(xRecip, xSqrt);
#endif //USE_FAST_METHOD
#ifdef USE_DIVISION_METHOD
pResultSSE[i] = _mm_div_ps(xSqrt, x);
#endif // USE_DIVISION_METHOD
// NOTE! Sometimes, the order in which things are done in SSE may seem reversed.
// When the command above executes, the four floating elements are actually flipped around
// We have already compensated for that flipping by setting the initial x vector to (4,3,2,1) instead of (1,2,3,4)
x = _mm_add_ps(x, xDelta); // Advance x to the next set of numbers
}
#endif // TIME_SSE
#ifndef TIME_SSE
float xFloat = 1.0f;
for (int i=0 ; i < length; i++)
{
pResult[i] = sqrt(xFloat) / xFloat; // Even though division is slow, there are no intrinsic functions like there are in SSE
xFloat += 1.0f;
}
#endif // !TIME_SSE
}
// To prove that the program actually worked
for (int i=0; i < 20; i++)
{
printf("Result[%d] = %f\n", i, pResult[i]);
}
// Results for my particular system
// 23.75 seconds for SSE with reciprocal/multiplication method
// 38.5 seconds for SSE with division method
// 301.5 seconds for CPU
return 0;
}
Upvotes: 4
Views: 4225
Reputation: 217850
with C++11, you may use something like:
struct aligned_float
{
alignas(16) float f[4];
};
static_assert(sizeof(aligned_float) == 4 * sizeof(float), "padding issue");
int main()
{
const int length = 64000;
std::vector<aligned_float> pResult(length / sizeof(aligned_float));
return 0;
}
Upvotes: 3
Reputation: 137477
See here:
http://www.gnu.org/software/libc/manual/html_node/Aligned-Memory-Blocks.html
Glibc provides aligned_alloc().
Upvotes: 1
Reputation: 137477
The aligned attributes only apply to how things are compiled/linked. It has no runtime effect.
The only portable way I know to solve this, is to have a wrapper that actually allocates more than is necessary, and masks off the lower bits to ensure that what it returs meets a ssufficient alignment.
Upvotes: 1