/* f32x4 mm mul */
void mw_neon_mm_mul_f32x4(float * A, int Row, int T, float * B, int Col, float * C)
{
int i, k, j;
float32x4_t neon_b, neon_c;
float32x4_t neon_a0, neon_a1, neon_a2, neon_a3;
float32x4_t neon_b0, neon_b1, neon_b2, neon_b3;
for (i = 0; i < Row; i+=4)
{
for (k = 0; k < Col; k+=1)
{
neon_c = vmovq_n_f32(0);
for (j = 0; j < T; j+=4)
{
int j_T = j * T + i;
int k_Row = k * Row;
neon_a0 = vld1q_f32(A + j_T);
j_T+=Row;
neon_a1 = vld1q_f32(A + j_T);
j_T+=Row;
neon_a2 = vld1q_f32(A + j_T);
j_T+=Row;
neon_a3 = vld1q_f32(A + j_T);
neon_b = vld1q_f32(B + k_Row + j);
neon_b0 = vdupq_n_f32(vgetq_lane_f32(neon_b, 0));
neon_b1 = vdupq_n_f32(vgetq_lane_f32(neon_b, 1));
neon_b2 = vdupq_n_f32(vgetq_lane_f32(neon_b, 2));
neon_b3 = vdupq_n_f32(vgetq_lane_f32(neon_b, 3));
neon_c = vaddq_f32(vmulq_f32(neon_a0, neon_b0), neon_c);
neon_c = vaddq_f32(vmulq_f32(neon_a1, neon_b1), neon_c);
neon_c = vaddq_f32(vmulq_f32(neon_a2, neon_b2), neon_c);
neon_c = vaddq_f32(vmulq_f32(neon_a3, neon_b3), neon_c);
vst1q_lane_f32(C + k_Row + i, neon_c, 0);
vst1q_lane_f32(C + k_Row + i + 1, neon_c, 1);
vst1q_lane_f32(C + k_Row + i + 2, neon_c, 2);
vst1q_lane_f32(C + k_Row + i + 3, neon_c, 3);
}
}
}
}
void test_vgetQ_lanef32 (void)
{
float32_t out_float32_t;
float32x4_t arg0_float32x4_t;
out_float32_t = vgetq_lane_f32 (arg0_float32x4_t, 1);
}
void
test_square_root_v4sf ()
{
const float32_t pool[] = {4.0f, 9.0f, 16.0f, 25.0f};
float32x4_t val;
float32x4_t res;
val = vld1q_f32 (pool);
res = vsqrtq_f32 (val);
if (vgetq_lane_f32 (res, 0) != 2.0f)
abort ();
if (vgetq_lane_f32 (res, 1) != 3.0f)
abort ();
if (vgetq_lane_f32 (res, 2) != 4.0f)
abort ();
if (vgetq_lane_f32 (res, 3) != 5.0f)
abort ();
}
/* f32x4 mv mul */
void mw_neon_mv_mul_f32x4(float * A, int Row, int T, float * B, float * C)
{
int i = 0;
int k = 0;
float32x4_t neon_b, neon_c;
float32x4_t neon_a0, neon_a1, neon_a2, neon_a3;
float32x4_t neon_b0, neon_b1, neon_b2, neon_b3;
for (i = 0; i < Row; i+=4)
{
neon_c = vmovq_n_f32(0);
for (k = 0; k < T; k+=4)
{
int j = k * T + i;
neon_a0 = vld1q_f32(A + j);
neon_a1 = vld1q_f32(A + j + Row);
neon_a2 = vld1q_f32(A + j + 2 * Row);
neon_a3 = vld1q_f32(A + j + 3 * Row);
neon_b = vld1q_f32(B + k);
neon_b0 = vdupq_n_f32(vgetq_lane_f32(neon_b, 0));
neon_b1 = vdupq_n_f32(vgetq_lane_f32(neon_b, 1));
neon_b2 = vdupq_n_f32(vgetq_lane_f32(neon_b, 2));
neon_b3 = vdupq_n_f32(vgetq_lane_f32(neon_b, 3));
neon_c = vaddq_f32(vmulq_f32(neon_a0, neon_b0), neon_c);
neon_c = vaddq_f32(vmulq_f32(neon_a1, neon_b1), neon_c);
neon_c = vaddq_f32(vmulq_f32(neon_a2, neon_b2), neon_c);
neon_c = vaddq_f32(vmulq_f32(neon_a3, neon_b3), neon_c);
}
vst1q_f32(C + i, neon_c);
}
}
// CHECK-LABEL: test_vgetq_lane_f32:
float32_t test_vgetq_lane_f32(float32x4_t v) {
return vgetq_lane_f32(v, 0);
// CHECK-NEXT: ret
}
// __INLINE
void arm_cmplx_mult_cmplx_f32_dot(
float32_t * pSrcA,
float32_t * pSrcB,
float32_t * pDst,
uint32_t numSamples)
{
float32_t a, b, c, d; /* Temporary variables to store real and imaginary values */
float32x4_t A1, A2; /* Temporary variables to store real and imaginary values of source buffer A */
float32x4_t B1, B2; /* Temporary variables to store real and imaginary values of source buffer B */
float32x4_t C1, C2, C3, C4; /* Temporary variables to store multiplication output */
float32x4x2_t out1, out2, out3, out4; /* Temporary variables to stroe output result */
float32x4x2_t acc1, acc2, acc3, acc4; /* Accumulators */
float sum_real, sum_img; /* */
uint32_t blkCnt; /* loop counters */
/* Clear accumulators VDUP.32 q0,r0
Vector Duplicate duplicates a scalar into every element of the destination vector.
*/
acc1.val[0] = vdupq_n_f32(0.0f);
acc1.val[1] = vdupq_n_f32(0.0f);
acc2.val[0] = vdupq_n_f32(0.0f);
acc2.val[1] = vdupq_n_f32(0.0f);
acc3.val[0] = vdupq_n_f32(0.0f);
acc3.val[1] = vdupq_n_f32(0.0f);
acc4.val[0] = vdupq_n_f32(0.0f);
acc4.val[1] = vdupq_n_f32(0.0f);
/* Loop over blockSize number of values */
blkCnt = numSamples >> 4u;
while(blkCnt > 0u)
{
/* A1, A2, B1, B2 each has two complex data. */
/******************************************************/
/* Step 1: Load data A1, A2, B1, B2 for group a:*/
/* read 2 complex values at a time from source A buffer
float32x4_t vld1q_f32(__transfersize(4) float32_t const * ptr);
VLD1.32 {d0, d1}, [r0]
*/
A1 = vld1q_f32(pSrcA);
/* increment source A buffer by 4 */
pSrcA += 4u;
/* read 2 complex values at a time from source A buffer */
A2 = vld1q_f32(pSrcA);
/* increment source A buffer by 4 */
pSrcA += 4u;
/* read 2 complex values at a time from source B buffer */
B1 = vld1q_f32(pSrcB);
/* increment source B buffer by 4 */
pSrcB += 4u;
/* read 2 complex values at a time from source B buffer */
B2 = vld1q_f32(pSrcB);
/* increment source B buffer by 4 */
pSrcB += 4u;
/******************************************************/
/* Step 2: Unzip data Out1, Out2 for group a:*/
/* unzip real and imag values
A1: reala0, imga0, reala1, imga1
A2: realb0, imgb0, realb1, imgb1
out1.val0: reala0, reala1, realb0, realb1;
out1.val1: imga0, imga1, imgb0, imgb1
vuzpq_f32:
float32x4x2_t vuzpq_f32 (float32x4_t, float32x4_t)
Form of expected instruction(s): vuzp.32 q0, q1
Vector Unzip de-interleaves the elements of two vectors.
*/
out1 = vuzpq_f32(A1, A2);
out2 = vuzpq_f32(B1, B2);
/******************************************************/
/* Step 1: Load data A1, A2, B1, B2 for group b:*/
/* read 2 complex values at a time from source A buffer */
A1 = vld1q_f32(pSrcA);
/* increment source A buffer by 4 */
pSrcA += 4u;
/* read 2 complex values at a time from source A buffer */
A2 = vld1q_f32(pSrcA);
/* increment source A buffer by 4 */
pSrcA += 4u;
/* read 2 complex values at a time from source B buffer */
B1 = vld1q_f32(pSrcB);
/* increment source B buffer by 4 */
pSrcB += 4u;
/* read 2 complex values at a time from source B buffer */
B2 = vld1q_f32(pSrcB);
/* increment source B buffer by 4 */
pSrcB += 4u;
/******************************************************/
/* Step 3: Compute data C1,C2,C3,C4 for group a:*/
/* C[2 * i] = A[2 * i] * B[2 * i] - A[2 * i + 1] * B[2 * i + 1]. */
/* C[2 * i + 1] = A[2 * i] * B[2 * i + 1] + A[2 * i + 1] * B[2 * i]. */
/* vmulq_f32: VMUL.F32 q0,q0,q0
val[0]: real
val[1]: img
C1 = a.real*b.real; C2 = a.img*b.img
C3 = a.img*b.real; C4 = a.real*b.img
*/
/* multiply 4 samples at a time from A1 real input with B1 real input */
C1 = vmulq_f32(out1.val[0], out2.val[0]);
/* multiply 4 samples at a time from A1 imaginary input with B1 imaginary input */
C2 = vmulq_f32(out1.val[1], out2.val[1]);
/* multiply 4 samples at a time from A1 imaginary input with B1 real input */
C3 = vmulq_f32(out1.val[1], out2.val[0]);
/* multiply 4 samples at a time from A1 real input with B1 imaginary input */
C4 = vmulq_f32(out1.val[0], out2.val[1]);
/* real: c1-c2; img: c3+c4 */
/******************************************************/
/* Step 2: Unzip data Out2, Out3 for group b:*/
out2 = vuzpq_f32(A1, A2);
out3 = vuzpq_f32(B1, B2);
/******************************************************/
/* Step 1: Load data A1, A2 for group c:*/
/* read 2 complex values at a time from source A buffer */
A1 = vld1q_f32(pSrcA);
/* increment source A buffer by 4 */
pSrcA += 4u;
/* read 2 complex values at a time from source A buffer */
A2 = vld1q_f32(pSrcA);
/* increment source A buffer by 4 */
pSrcA += 4u;
/******************************************************/
/* Step 4: Output or accumlate data for group a:*/
/* (a+bi)*(c+di) = (ac-bd)+(ad+bc)i*/
/* real: c1-c2; img: c3+c4 */
/* subtract 4 samples at time from real result to imaginary result, got four real part */
/*
C1 = a.real*b.real; C2 = a.img*b.img
C3 = a.img*b.real; C4 = a.real*b.img
vaddq_f32:
VADD.F32 q0,q0,q0
*/
out1.val[0] = vsubq_f32(C1, C2);
acc1.val[0] = vaddq_f32(out1.val[0], acc1.val[0]); /* add by Hank */
/* add real*imaginary result with imaginary*real result 4 at a time */
out1.val[1] = vaddq_f32(C3, C4);
acc1.val[1] = vaddq_f32(out1.val[1], acc1.val[1]); /* add by Hank */
/* out1 is four complex product. */
/******************************************************/
/* Step 1: Load data B1, B2 for group c:*/
/* read 2 complex values at a time from source B buffer */
B1 = vld1q_f32(pSrcB);
/* increment source B buffer by 4 */
pSrcB += 4u;
/* read 2 complex values at a time from source B buffer */
B2 = vld1q_f32(pSrcB);
/* increment source B buffer by 4 */
pSrcB += 4u;
/******************************************************/
/* Step 3: Compute data C1,C2 for group b:*/
/* multiply 4 samples at a time from A1 real input with B1 real input */
C1 = vmulq_f32(out2.val[0], out3.val[0]);
/* multiply 4 samples at a time from A1 imaginary input with B1 imaginary input */
C2 = vmulq_f32(out2.val[1], out3.val[1]);
/******************************************************/
/* Step 5: Store data for group a:*/
/* Store 4 complex samples to destination buffer
VST2.32 {d0, d2}, [r0] */
//vst2q_f32(pDst, out1);
/* increment destination buffer by 8 */
//pDst += 8u;
/******************************************************/
/* Step 3: Compute data C3,C4 for group b:*/
/* multiply 4 samples at a time from A1 imaginary input with B1 real input */
C3 = vmulq_f32(out2.val[1], out3.val[0]);
/* multiply 4 samples at a time from A1 real input with B1 imaginary input */
C4 = vmulq_f32(out2.val[0], out3.val[1]);
/******************************************************/
/* Step 2: Unzip data Out1, Out2 for group C:*/
out3 = vuzpq_f32(A1, A2);
out4 = vuzpq_f32(B1, B2);
/******************************************************/
/* Step 1: Load data A1, A2, B1, B2 for group d:*/
/* read 4 complex values from source A buffer */
A1 = vld1q_f32(pSrcA);
pSrcA += 4u;
A2 = vld1q_f32(pSrcA);
pSrcA += 4u;
/* read 4 complex values from source B buffer */
B1 = vld1q_f32(pSrcB);
pSrcB += 4u;
B2 = vld1q_f32(pSrcB);
pSrcB += 4u;
/******************************************************/
/* Step 4: Output or accumlate data for group b:*/
/* subtract 4 samples at time from real result to imaginary result */
out2.val[0] = vsubq_f32(C1, C2);
/* add real*imaginary result with imaginary*real result 4 at a time */
out2.val[1] = vaddq_f32(C3, C4);
acc2.val[0] = vaddq_f32(out2.val[0], acc2.val[0]); /* add by Hank */
acc2.val[1] = vaddq_f32(out2.val[1], acc2.val[1]); /* add by Hank */
/******************************************************/
/* Step 3: Compute data C1,C2,C3,C4 for group c:*/
/* multiply 4 samples at a time from A3 real input with B3 real input */
C1 = vmulq_f32(out3.val[0], out4.val[0]);
/* multiply 4 samples at a time from A3 imaginary input with B3 imaginary input */
C2 = vmulq_f32(out3.val[1], out4.val[1]);
/* multiply 4 samples at a time from A3 imaginary input with B3 real input */
C3 = vmulq_f32(out3.val[1], out4.val[0]);
/* multiply 4 samples at a time from A3 real input with B3 imaginary input */
C4 = vmulq_f32(out3.val[0], out4.val[1]);
/******************************************************/
/* Step 2: Unzip data Out1, Out2 for group D:*/
out1 = vuzpq_f32(A1, A2);
out4 = vuzpq_f32(B1, B2);
/******************************************************/
/* Step 5: Store data for group b:*/
/* Store 4 complex samples to destination buffer */
//vst2q_f32(pDst, out2);
/* increment destination buffer by 8 */
//pDst += 8u;
/******************************************************/
/* Step 4: Output or accumlate data for group c:*/
/* subtract 4 samples at time from real result to imaginary result */
out3.val[0] = vsubq_f32(C1, C2);
/* add real*imaginary result with imaginary*real result 4 at a time */
out3.val[1] = vaddq_f32(C3, C4);
acc3.val[0] = vaddq_f32(out3.val[0], acc3.val[0]); /* add by Hank */
acc3.val[1] = vaddq_f32(out3.val[1], acc3.val[1]); /* add by Hank */
/******************************************************/
/* Step 3: Compute data C1,C2,C3,C4 for group d:*/
/* multiply 4 samples at a time from A1 real input with B1 real input */
C1 = vmulq_f32(out1.val[0], out4.val[0]);
/* multiply 4 samples at a time from A1 imaginary input with B1 imaginary input */
C2 = vmulq_f32(out1.val[1], out4.val[1]);
/* multiply 4 samples at a time from A1 imaginary input with B1 real input */
C3 = vmulq_f32(out1.val[1], out4.val[0]);
/* multiply 4 samples at a time from A1 real input with B1 imaginary input */
C4 = vmulq_f32(out1.val[0], out4.val[1]);
/******************************************************/
/* Step 5: Store data for group c:*/
/* Store 4 complex samples to destination buffer */
//vst2q_f32(pDst, out3);
/******************************************************/
/* Step 4: Output or accumlate data for group d:*/
/* subtract 4 samples at time from real result to imaginary result */
out4.val[0] = vsubq_f32(C1, C2);
/* increment destination buffer by 8 */
//pDst += 8u;
/******************************************************/
/* Step 4: Output or accumlate data for group d:*/
/* add real*imaginary result with imaginary*real result 4 at a time */
out4.val[1] = vaddq_f32(C3, C4);
acc4.val[0] = vaddq_f32(out4.val[0], acc4.val[0]); /* add by Hank */
acc4.val[1] = vaddq_f32(out4.val[1], acc4.val[1]); /* add by Hank */
/* zip real and imag values */
//out4 = vzipq_f32(out4.val[0], out4.val[1]);
/******************************************************/
/* Step 5: Store data for group d:*/
/* Store 4 complex samples to destination buffer */
//vst1q_f32(pDst, out4.val[0]);
//pDst += 4u;
//vst1q_f32(pDst, out4.val[1]);
//pDst += 4u;
/* Decrement the numSamples loop counter */
blkCnt--;
}
blkCnt = numSamples & 15u;
blkCnt = blkCnt >> 2u;
/* If the blockSize is not a multiple of 16, compute remaining output samples.
** Compute multiple of 4 samples at a time in second loop.
** and remaining 1 to 3 samples in third loop. */
while(blkCnt > 0u)
{
/* Step 1: Load data A1, A2, B1, B2 */
/* read 4 complex values at a time from source A buffer */
A1 = vld1q_f32(pSrcA);
/* increment source A buffer by 8 */
pSrcA += 4u;
A2 = vld1q_f32(pSrcA);
pSrcA += 4u;
/* read 4 complex values at a time from source B buffer */
B1 = vld1q_f32(pSrcB);
/* increment source B buffer by 8 */
pSrcB += 4u;
B2 = vld1q_f32(pSrcB);
pSrcB += 4u;
/* Step 2: Unzip data Out1, Out2 */
/* Unzip data */
out1 = vuzpq_f32(A1, A2);
out2 = vuzpq_f32(B1, B2);
/* Step 3: Compute data C1,C2,C3,C4 */
/* C[2 * i] = A[2 * i] * B[2 * i] - A[2 * i + 1] * B[2 * i + 1]. */
/* C[2 * i + 1] = A[2 * i] * B[2 * i + 1] + A[2 * i + 1] * B[2 * i]. */
/* multiply 4 samples at a time from A1 real input with B1 real input */
C1 = vmulq_f32(out1.val[0], out2.val[0]);
/* multiply 4 samples at a time from A1 imaginary input with B1 imaginary input */
C2 = vmulq_f32(out1.val[1], out2.val[1]);
/* multiply 4 samples at a time from A1 imaginary input with B1 real input */
C3 = vmulq_f32(out1.val[1], out2.val[0]);
/* multiply 4 samples at a time from A1 real input with B1 imaginary input */
C4 = vmulq_f32(out1.val[0], out2.val[1]);
/* Step 4: Output or accumlate data for group d:*/
/* subtract 4 samples at time from real result to imaginary result */
out1.val[0] = vsubq_f32(C1, C2);
/* add real*imaginary result with imaginary*real result 4 at a time */
out1.val[1] = vaddq_f32(C3, C4);
acc1.val[0] = vaddq_f32(out1.val[0], acc1.val[0]); /* add by Hank */
acc1.val[1] = vaddq_f32(out1.val[1], acc1.val[1]); /* add by Hank */
//out1 = vzipq_f32(out1.val[0], out1.val[1]);
/* Step 5: Store data */
/* Store 4 complex samples to destination buffer */
//vst1q_f32(pDst, out1.val[0]);
//pDst += 4u;
//vst1q_f32(pDst, out1.val[1]);
//pDst += 4u;
/* Decrement the numSamples loop counter */
blkCnt--;
}
blkCnt = numSamples & 3u;
/* If the blockSize is not a multiple of 4, compute any remaining output samples here.
** No intrinsics is used. */
sum_real =0;
sum_img =0;
while(blkCnt > 0u)
{
/* C[2 * i] = A[2 * i] * B[2 * i] - A[2 * i + 1] * B[2 * i + 1]. */
/* C[2 * i + 1] = A[2 * i] * B[2 * i + 1] + A[2 * i + 1] * B[2 * i]. */
a = *pSrcA++;
b = *pSrcA++;
c = *pSrcB++;
d = *pSrcB++;
/* store the result in the destination buffer. */
sum_real += ((a * c) - (b * d));
sum_img += ((a * d) + (b * c));
/* Decrement the numSamples loop counter */
blkCnt--;
}
/* add 4 accumulators */
acc1.val[0] = vaddq_f32(acc1.val[0], acc2.val[0]);
acc1.val[1] = vaddq_f32(acc1.val[1], acc2.val[1]);
acc2.val[0] = vaddq_f32(acc3.val[0], acc4.val[0]);
acc2.val[1] = vaddq_f32(acc3.val[1], acc4.val[1]);
acc1.val[0] = vaddq_f32(acc1.val[0], acc2.val[0]);
acc1.val[1] = vaddq_f32(acc1.val[1], acc2.val[1]);
sum_real += vgetq_lane_f32(acc1.val[0], 0) + vgetq_lane_f32(acc1.val[0], 1)
+ vgetq_lane_f32(acc1.val[0], 2) + vgetq_lane_f32(acc1.val[0], 3);
sum_img += vgetq_lane_f32(acc1.val[1], 0) + vgetq_lane_f32(acc1.val[1], 1)
+ vgetq_lane_f32(acc1.val[1], 2) + vgetq_lane_f32(acc1.val[1], 3);
*pDst++=sum_real;
*pDst++=sum_img;
/* useful when debuggin.. */
void print4(float32x4_t v) {
/* float *p = (float*)&v; */ /* Commented out to avoid compiler warning of unused variable */
printf("[%13.8g, %13.8g, %13.8g, %13.8g]", vgetq_lane_f32(v,0), vgetq_lane_f32(v, 1), vgetq_lane_f32(v, 2), vgetq_lane_f32(v, 3));
}
float32_t test_vgetq_lane_f32(float32x4_t a) {
// CHECK-LABEL: test_vgetq_lane_f32:
// CHECK-NEXT: mov s0, v0[3]
// CHECK-NEXT: ret
return vgetq_lane_f32(a, 3);
}
/* useful when debuggin.. */
void print4(float32x4_t v) {
float *p = (float*)&v;
printf("[%13.8g, %13.8g, %13.8g, %13.8g]", vgetq_lane_f32(v,0), vgetq_lane_f32(v, 1), vgetq_lane_f32(v, 2), vgetq_lane_f32(v, 3));
}
/*******************************************************************************
* PROCEDURE: gaussian_smooth
* PURPOSE: Blur an image with a gaussian filter.
* NAME: Mike Heath
* DATE: 2/15/96
*******************************************************************************/
short int* gaussian_smooth(unsigned char *image, int rows, int cols, float sigma)
{
int r, c, rr, cc, /* Counter variables. */
windowsize, /* Dimension of the gaussian kernel. */
center; /* Half of the windowsize. */
float *tempim,*tempim1, /* Buffer for separable filter gaussian smoothing. */
*kernel, /* A one dimensional gaussian kernel. */
dot, /* Dot product summing variable. */
sum; /* Sum of the kernel weights variable. */
/****************************************************************************
* Create a 1-dimensional gaussian smoothing kernel.
****************************************************************************/
if(VERBOSE) printf(" Computing the gaussian smoothing kernel.\n");
make_gaussian_kernel(sigma, &kernel, &windowsize);
center = windowsize / 2;
/****************************************************************************
* Allocate a temporary buffer image and the smoothed image.
****************************************************************************/
if((tempim = (float *) malloc(rows*cols* sizeof(float))) == NULL)
{
fprintf(stderr, "Error allocating the buffer image.\n");
exit(1);
}
short int* smoothedim;
if(((smoothedim) = (short int *) malloc(rows*cols*sizeof(short int))) == NULL)
{
fprintf(stderr, "Error allocating the smoothed image.\n");
exit(1);
}
startTimer(&totalTime);
//Neon impelementation of gaussian smooth starts here
/****************************************************************************
* Blur in the x - direction.
****************************************************************************/
int loop;
int floop;
//Modification of input image for neon implementation
//For Filter 1
float * new_image;
//For Filter 2
float *new_image_col;
//kernel is changed to 17 from 15 for neon (two 0s at the beginning and the end)
float new_kernel[17];
//Generating now kernel filter
for (floop = 0 ; floop < 17 ; floop++)
{
if(floop == 0 || floop == 16 )
new_kernel[floop] = 0 ;
else
new_kernel [floop] = kernel[floop -1];
}
//For filter 1, new cols number for neon
unsigned int new_cols;
new_cols=cols+16;
unsigned int i, k;
unsigned int a;
unsigned int m;
unsigned int n, j;
//Malloc of new image used by neon
new_image = (float*)malloc(new_cols*rows*sizeof(float));
for( i =0; i<rows; i++){
memset(&new_image[i*new_cols],0,8*sizeof(float));
for( k=0; k<cols;k++){
new_image[i*new_cols+8+k] = (float)image[i*cols+k];
}
memset(&new_image[i*new_cols+8+cols],0,8*sizeof(float));
}
// Neon handles four piexel at a time
float32x4_t neon_input;
float32x4_t neon_filter;
float32x4_t temp_sum;
float32x2_t tempUpper;
float32x2_t tempLower;
float32_t zero = 0;
float32_t temp_output;
float Basekernel = 0.0f;
float kernelSum;
//When using the new filter, we always assume the image has more than 9 pixels in a row
//Base sum for the filter
for( a=8; a<=16; a++){
Basekernel += new_kernel[a];
}
//Filter 1, filtering row by row
for(m=0; m<rows; m++){
for( n=0; n<cols; n++){
temp_sum = vdupq_n_f32(0);
if(n==0){
kernelSum = Basekernel;
}
else if(n <=8){
kernelSum += new_kernel[8-n];
}
else if(n>=cols-8){
kernelSum -=new_kernel[cols-n+8];
}
//For each pixel, filtering is performed four times
for( j=0; j<4; j++)
{
int kk=0;
if(j>=2)
{
kk=1;
}
neon_input = vld1q_f32(&new_image[m*new_cols+n+j*4+kk]);
neon_filter = vld1q_f32(&new_kernel[j*4+kk]);
temp_sum = vmlaq_f32(temp_sum,neon_input,neon_filter);
}
unsigned int t;
for( t=0; t<=3; t++){
temp_output += vgetq_lane_f32(temp_sum,t );
}
temp_output += new_image[m*new_cols+n+8] * new_kernel[8];
temp_output /= kernelSum;
tempim[m*cols+n] = temp_output;
temp_output=0;
}
}
for(r=0; r<rows; r++)
{
for(c=0; c<cols; c++)
{
dot = 0.0;
sum = 0.0;
for(cc=(-center); cc<=center; cc++)
{
if(((c+cc) >= 0) && ((c+cc) < cols))
{
dot += (float)image[r*cols+(c+cc)] * kernel[center+cc];
sum += kernel[center+cc];
}
}
tempim1[r*cols+c] = dot/sum;
}
}
/****************************************************************************
* Blur in the y - direction.
****************************************************************************/
unsigned int new_rows;
new_rows=rows+16;
new_image_col = (float*)malloc(new_rows*cols*sizeof(float));
if(VERBOSE) printf(" Bluring the image in the Y-direction.\n");
for( i =0; i<cols; i++){//actually nember of new rows are the number of columns here
memset(&new_image_col[i*new_rows],0,8*sizeof(float));
for( k=0; k<rows;k++){
new_image_col[i*new_rows+8+k] = tempim[k*cols+i];
//new_image_col[i*new_rows+8+k] = imagetest1[k*cols+i];
}
memset(&new_image_col[i*new_rows+8+rows],0,8*sizeof(float));
}
Basekernel = 0.0;
for( a=8; a<=16; a++){
Basekernel += new_kernel[a];
}
for(m=0; m<cols; m++){// it was rows at br
for( n=0; n<rows; n++){
temp_sum = vdupq_n_f32(0);
if(n==0){
kernelSum = Basekernel;
}
else if(n <=8){
kernelSum += new_kernel[8-n];
}
else if(n>=rows-8){
kernelSum -=new_kernel[rows-n+8];
}
for( j=0; j<4; j++)
{
int kk=0;
if(j>=2)
{
kk=1;
}
neon_input = vld1q_f32(&new_image_col[m*new_rows+n+j*4+kk]);
neon_filter = vld1q_f32(&new_kernel[j*4+kk]);
temp_sum = vmlaq_f32(temp_sum,neon_input,neon_filter);
}
unsigned int t;
for( t=0; t<=3; t++){
temp_output += vgetq_lane_f32(temp_sum,t );
}
temp_output += new_image_col[m*new_rows+n+8] * new_kernel[8];
temp_output = (temp_output * BOOSTBLURFACTOR) / kernelSum + 0.5;
smoothedim[n*cols+m] = (short int )temp_output;
temp_output=0;
}
}
stopTimer(&totalTime);
printTimer(&totalTime);
free(tempim);
free(kernel);
return smoothedim;
}
// CHECK-LABEL: define float @test_vgetq_lane_f32(<4 x float> %a) #0 {
// CHECK: [[TMP0:%.*]] = bitcast <4 x float> %a to <16 x i8>
// CHECK: [[TMP1:%.*]] = bitcast <16 x i8> [[TMP0]] to <4 x float>
// CHECK: [[VGETQ_LANE:%.*]] = extractelement <4 x float> [[TMP1]], i32 3
// CHECK: ret float [[VGETQ_LANE]]
float32_t test_vgetq_lane_f32(float32x4_t a) {
return vgetq_lane_f32(a, 3);
}
