コード例 #1
0
        template <bool align> SIMD_INLINE void SquaredDifferenceSum16f(const uint16_t * a, const uint16_t * b, size_t size, float * sum)
        {
            assert(size >= F);
            if (align)
                assert(Aligned(a) && Aligned(b));

            size_t partialAlignedSize = AlignLo(size, F);
            size_t fullAlignedSize = AlignLo(size, DF);
            size_t i = 0;
            float32x4_t sums[2] = { vdupq_n_f32(0), vdupq_n_f32(0) };
            if (fullAlignedSize)
            {
                for (; i < fullAlignedSize; i += DF)
                {
                    SquaredDifferenceSum16f<align>(a, b, i + F * 0, sums[0]);
                    SquaredDifferenceSum16f<align>(a, b, i + F * 1, sums[1]);
                }
                sums[0] = vaddq_f32(sums[0], sums[1]);
            }
            for (; i < partialAlignedSize; i += F)
                SquaredDifferenceSum16f<align>(a, b, i, sums[0]);
            if (partialAlignedSize != size)
            {
                float32x4_t tailMask = RightNotZero(size - partialAlignedSize);
                float32x4_t _a = vcvt_f32_f16((float16x4_t)LoadHalf<align>(a + size - F));
                float32x4_t _b = vcvt_f32_f16((float16x4_t)LoadHalf<align>(a + size - F));
                float32x4_t _d = And(vsubq_f32(_a, _b), tailMask);
                sums[0] = vaddq_f32(sums[0], vmulq_f32(_d, _d));
            }
            *sum = ExtractSum32f(sums[0]);
        }
コード例 #2
0
static void ScaleErrorSignalNEON(int extended_filter_enabled,
                                 float normal_mu,
                                 float normal_error_threshold,
                                 float x_pow[PART_LEN1],
                                 float ef[2][PART_LEN1]) {
  const float mu = extended_filter_enabled ? kExtendedMu : normal_mu;
  const float error_threshold = extended_filter_enabled ?
      kExtendedErrorThreshold : normal_error_threshold;
  const float32x4_t k1e_10f = vdupq_n_f32(1e-10f);
  const float32x4_t kMu = vmovq_n_f32(mu);
  const float32x4_t kThresh = vmovq_n_f32(error_threshold);
  int i;
  // vectorized code (four at once)
  for (i = 0; i + 3 < PART_LEN1; i += 4) {
    const float32x4_t x_pow_local = vld1q_f32(&x_pow[i]);
    const float32x4_t ef_re_base = vld1q_f32(&ef[0][i]);
    const float32x4_t ef_im_base = vld1q_f32(&ef[1][i]);
    const float32x4_t xPowPlus = vaddq_f32(x_pow_local, k1e_10f);
    float32x4_t ef_re = vdivq_f32(ef_re_base, xPowPlus);
    float32x4_t ef_im = vdivq_f32(ef_im_base, xPowPlus);
    const float32x4_t ef_re2 = vmulq_f32(ef_re, ef_re);
    const float32x4_t ef_sum2 = vmlaq_f32(ef_re2, ef_im, ef_im);
    const float32x4_t absEf = vsqrtq_f32(ef_sum2);
    const uint32x4_t bigger = vcgtq_f32(absEf, kThresh);
    const float32x4_t absEfPlus = vaddq_f32(absEf, k1e_10f);
    const float32x4_t absEfInv = vdivq_f32(kThresh, absEfPlus);
    uint32x4_t ef_re_if = vreinterpretq_u32_f32(vmulq_f32(ef_re, absEfInv));
    uint32x4_t ef_im_if = vreinterpretq_u32_f32(vmulq_f32(ef_im, absEfInv));
    uint32x4_t ef_re_u32 = vandq_u32(vmvnq_u32(bigger),
                                     vreinterpretq_u32_f32(ef_re));
    uint32x4_t ef_im_u32 = vandq_u32(vmvnq_u32(bigger),
                                     vreinterpretq_u32_f32(ef_im));
    ef_re_if = vandq_u32(bigger, ef_re_if);
    ef_im_if = vandq_u32(bigger, ef_im_if);
    ef_re_u32 = vorrq_u32(ef_re_u32, ef_re_if);
    ef_im_u32 = vorrq_u32(ef_im_u32, ef_im_if);
    ef_re = vmulq_f32(vreinterpretq_f32_u32(ef_re_u32), kMu);
    ef_im = vmulq_f32(vreinterpretq_f32_u32(ef_im_u32), kMu);
    vst1q_f32(&ef[0][i], ef_re);
    vst1q_f32(&ef[1][i], ef_im);
  }
  // scalar code for the remaining items.
  for (; i < PART_LEN1; i++) {
    float abs_ef;
    ef[0][i] /= (x_pow[i] + 1e-10f);
    ef[1][i] /= (x_pow[i] + 1e-10f);
    abs_ef = sqrtf(ef[0][i] * ef[0][i] + ef[1][i] * ef[1][i]);

    if (abs_ef > error_threshold) {
      abs_ef = error_threshold / (abs_ef + 1e-10f);
      ef[0][i] *= abs_ef;
      ef[1][i] *= abs_ef;
    }

    // Stepsize factor
    ef[0][i] *= mu;
    ef[1][i] *= mu;
  }
}
コード例 #3
0
ファイル: transform-neon.c プロジェクト: makotokato/qcms
void qcms_transform_data_rgba_out_lut_neon(qcms_transform *transform,
                                           unsigned char *src,
                                           unsigned char *dest,
                                           size_t length)
{
  size_t i;
  unsigned char alpha;
  float32_t (*mat)[4] = transform->matrix;

  const float32_t *igtbl_r = (float32_t*)transform->input_gamma_table_r;
  const float32_t *igtbl_g = (float32_t*)transform->input_gamma_table_g;
  const float32_t *igtbl_b = (float32_t*)transform->input_gamma_table_b;

  const uint8_t *otdata_r = &transform->output_table_r->data[0];
  const uint8_t *otdata_g = &transform->output_table_g->data[0];
  const uint8_t *otdata_b = &transform->output_table_b->data[0];

  const float32x4_t mat0 = vld1q_f32(mat[0]);
  const float32x4_t mat1 = vld1q_f32(mat[1]);
  const float32x4_t mat2 = vld1q_f32(mat[2]);

  const float32x4_t max   = vld1q_dup_f32(&clampMaxValue);
  const float32x4_t min   = vld1q_dup_f32(&zero);
  const float32x4_t scale = vld1q_dup_f32(&floatScale);

  float32x4_t vec_r, vec_g, vec_b;
  int32x4_t result;

  /* CYA */
  if (!length)
    return;

  for (i = 0; i < length; i++) {
    /* setup for transforming the pixel */
    vec_r = vld1q_dup_f32(&igtbl_r[*src++]);
    vec_g = vld1q_dup_f32(&igtbl_g[*src++]);
    vec_b = vld1q_dup_f32(&igtbl_b[*src++]);
    alpha = *src++;

    /* gamma * matrix */
    vec_r = vmulq_f32(vec_r, mat0);
    vec_g = vmulq_f32(vec_g, mat1);
    vec_b = vmulq_f32(vec_b, mat2);

    /* crunch, crunch, crunch */
    vec_r = vaddq_f32(vec_r, vaddq_f32(vec_g, vec_b));
    vec_r = vmaxq_f32(min, vec_r);
    vec_r = vminq_f32(max, vec_r);
    result = vcvtq_s32_f32(vmulq_f32(vec_r, scale));

    /* use calc'd indices to output RGB values */
    *dest++ = otdata_r[vgetq_lane_s32(result, 0)];
    *dest++ = otdata_g[vgetq_lane_s32(result, 1)];
    *dest++ = otdata_b[vgetq_lane_s32(result, 2)];
    *dest++ = alpha;
  }
}
コード例 #4
0
static inline void neon_make_rgb(float32x4_t macropixel, float32x4_t *rgba0p,
				 float32x4_t  *rgba1p)
{
  const float32x4_t  u_coeff = {0.0, -0.34455,  1.7790, 0.0 };
  const float32x4_t  v_coeff = {1.4075, -0.7169, 0.0, 0.0 };
  float32x4_t  y0_vec, y1_vec, u_vec, v_vec,  uv_vec;
  float32x2_t y0_u, y1_v;
  const float32_t alpha = 255.0;

  
  /* macropixel is [Y0, U, Y1, V].   */

  /* since vdupq_lane_f32 will only take two element vectors we */
  /* need to pick macropixel apart to build vectors of the components.  */
  /* so make y0_u be the first half of macropixel [Y0, U] and  */
  /* y1_v be the second half [Y1, V]. */
 
  y0_u =  vget_low_f32(macropixel);
  y1_v =  vget_high_f32(macropixel);

  /* now copy Y0 to all elements of y0_vec, then overwrite element 3  */
  /* with alpha.   */
  y0_vec = vdupq_lane_f32(y0_u, 0);
  y0_vec =  vsetq_lane_f32(alpha, y0_vec, 3);

  /* make u_vec be [U, U, U, U]. we'll do that using  */
  /* vdupq_lane_f32 and selecting U (element 1) from y0_u  */
  
  u_vec  = vdupq_lane_f32(y0_u, 1);

  /* now copy Y1 to all elements of y1_vec, then overwrite element 3  */
  /* with alpha.   */
  
  y1_vec  = vdupq_lane_f32(y1_v, 0);
  y1_vec =  vsetq_lane_f32(alpha, y1_vec, 3);

  /* make v_vec be [V, V, V, V]. we'll do that using  */
  /* vdupq_lane_f32 and selecting V (element 1) from y1_v  */
  
  v_vec = vdupq_lane_f32(y1_v, 1);

  /* now multiply u_vec * u_coeff and v_vec by v_coeff.  */
  u_vec =  vmulq_f32(u_vec, u_coeff);
  v_vec =  vmulq_f32(v_vec, v_coeff);

  /* add u_vec and v_vec to form uv_vec. use that to build  */
  /*  rgba0 and  rgba1 by adding y0_vec, y1_vec*/
  
  uv_vec = vaddq_f32(u_vec, v_vec);
  *rgba0p =  vaddq_f32(y0_vec, uv_vec);
  *rgba1p =  vaddq_f32(y1_vec, uv_vec);
  
  
}
コード例 #5
0
ファイル: mw_neon.c プロジェクト: Daniel-Hwang/eeg
/* 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);

			}
		}
	}
}
コード例 #6
0
ファイル: aec_rdft_neon.c プロジェクト: dreaflove/webrtc-lib
static void cft1st_128_neon(float* a) {
  const float32x4_t vec_swap_sign = vld1q_f32((float32_t*)k_swap_sign);
  int j, k2;

  for (k2 = 0, j = 0; j < 128; j += 16, k2 += 4) {
    float32x4_t a00v = vld1q_f32(&a[j + 0]);
    float32x4_t a04v = vld1q_f32(&a[j + 4]);
    float32x4_t a08v = vld1q_f32(&a[j + 8]);
    float32x4_t a12v = vld1q_f32(&a[j + 12]);
    float32x4_t a01v = vcombine_f32(vget_low_f32(a00v), vget_low_f32(a08v));
    float32x4_t a23v = vcombine_f32(vget_high_f32(a00v), vget_high_f32(a08v));
    float32x4_t a45v = vcombine_f32(vget_low_f32(a04v), vget_low_f32(a12v));
    float32x4_t a67v = vcombine_f32(vget_high_f32(a04v), vget_high_f32(a12v));
    const float32x4_t wk1rv = vld1q_f32(&rdft_wk1r[k2]);
    const float32x4_t wk1iv = vld1q_f32(&rdft_wk1i[k2]);
    const float32x4_t wk2rv = vld1q_f32(&rdft_wk2r[k2]);
    const float32x4_t wk2iv = vld1q_f32(&rdft_wk2i[k2]);
    const float32x4_t wk3rv = vld1q_f32(&rdft_wk3r[k2]);
    const float32x4_t wk3iv = vld1q_f32(&rdft_wk3i[k2]);
    float32x4_t x0v = vaddq_f32(a01v, a23v);
    const float32x4_t x1v = vsubq_f32(a01v, a23v);
    const float32x4_t x2v = vaddq_f32(a45v, a67v);
    const float32x4_t x3v = vsubq_f32(a45v, a67v);
    const float32x4_t x3w = vrev64q_f32(x3v);
    float32x4_t x0w;
    a01v = vaddq_f32(x0v, x2v);
    x0v = vsubq_f32(x0v, x2v);
    x0w = vrev64q_f32(x0v);
    a45v = vmulq_f32(wk2rv, x0v);
    a45v = vmlaq_f32(a45v, wk2iv, x0w);
    x0v = vmlaq_f32(x1v, x3w, vec_swap_sign);
    x0w = vrev64q_f32(x0v);
    a23v = vmulq_f32(wk1rv, x0v);
    a23v = vmlaq_f32(a23v, wk1iv, x0w);
    x0v = vmlsq_f32(x1v, x3w, vec_swap_sign);
    x0w = vrev64q_f32(x0v);
    a67v = vmulq_f32(wk3rv, x0v);
    a67v = vmlaq_f32(a67v, wk3iv, x0w);
    a00v = vcombine_f32(vget_low_f32(a01v), vget_low_f32(a23v));
    a04v = vcombine_f32(vget_low_f32(a45v), vget_low_f32(a67v));
    a08v = vcombine_f32(vget_high_f32(a01v), vget_high_f32(a23v));
    a12v = vcombine_f32(vget_high_f32(a45v), vget_high_f32(a67v));
    vst1q_f32(&a[j + 0], a00v);
    vst1q_f32(&a[j + 4], a04v);
    vst1q_f32(&a[j + 8], a08v);
    vst1q_f32(&a[j + 12], a12v);
  }
}
コード例 #7
0
static void test_fma() {
    for(int i=0; i<1020 * 4; i++) {
        data_f[i] = i;
    }
    float32x4_t c0_02 = vdupq_n_f32(0.02f);
    float32x4_t c0_04 = vdupq_n_f32(0.04f);
    float32x4_t c0_05 = vdupq_n_f32(0.05f);
    float32x4_t c0_10 = vdupq_n_f32(0.1f);
    float32x4_t c0_20 = vdupq_n_f32(0.2f);
    float32x4_t c1_00 = vdupq_n_f32(1.0f);

    startTime();

    // Do ~1 billion ops
    for (int ct=0; ct < (1000 * (1000 / 80)); ct++) {
        for (int i=0; i < 1000; i++) {
            float32x4_t t;
            t = vmulq_f32(vld1q_f32((float32_t *)&data_f[i]), c0_02);
            t = vmlaq_f32(t, vld1q_f32((float32_t *)&data_f[i+4]), c0_04);
            t = vmlaq_f32(t, vld1q_f32((float32_t *)&data_f[i+8]), c0_05);
            t = vmlaq_f32(t, vld1q_f32((float32_t *)&data_f[i+12]), c0_10);
            t = vmlaq_f32(t, vld1q_f32((float32_t *)&data_f[i+16]), c0_20);
            t = vmlaq_f32(t, vld1q_f32((float32_t *)&data_f[i+20]), c0_20);
            t = vmlaq_f32(t, vld1q_f32((float32_t *)&data_f[i+24]), c0_10);
            t = vmlaq_f32(t, vld1q_f32((float32_t *)&data_f[i+28]), c0_05);
            t = vmlaq_f32(t, vld1q_f32((float32_t *)&data_f[i+32]), c0_04);
            t = vmlaq_f32(t, vld1q_f32((float32_t *)&data_f[i+36]), c0_02);
            t = vaddq_f32(t, c1_00);
            vst1q_f32((float32_t *)&data_f[i], t);
        }
    }

    endTime("neon fma", 1e9);
}
コード例 #8
0
static inline float32x4_t floor_neon(float32x4_t a)
{
#if __ARM_ARCH >= 8
   return vrndqm_f32(a);
#else
   const float32x4_t round32 = vdupq_n_f32(12582912.0f);
   const float32x4_t vhalf = vdupq_n_f32(0.5f);

   float32x4_t rounded = vsubq_f32(vaddq_f32(a, round32), round32);
   uint32x4_t mask = vceqq_f32(a, rounded);

   float32x4_t floored = vsubq_f32(vaddq_f32(vsubq_f32(a, vhalf), round32), round32);
   return vreinterpretq_f32_u32(vorrq_u32(vandq_u32(vreinterpretq_u32_f32(a), mask),
            vbicq_u32(vreinterpretq_u32_f32(floored), mask)));
#endif
}
コード例 #9
0
ファイル: OgreMathlibNEON.cpp プロジェクト: amerkoleci/mogre
    //-----------------------------------------------------------------------------------
    void MathlibNEON::SinCos4( ArrayReal x, ArrayReal &outSin, ArrayReal &outCos )
    {
        // TODO: Improve accuracy by mapping to the range [-pi/4, pi/4] and swap
        // between cos & sin depending on which quadrant it fell:
        // Quadrant | sin     |  cos
        // n = 0 ->  sin( x ),  cos( x )
        // n = 1 ->  cos( x ), -sin( x )
        // n = 2 -> -sin( x ), -cos( x )
        // n = 3 -> -sin( x ),  sin( x )
        // See ARGUMENT REDUCTION FOR HUGE ARGUMENTS:
        // Good to the Last Bit
        // K. C. Ng and themembers of the FP group of SunPro
        // http://www.derekroconnor.net/Software/Ng--ArgReduction.pdf

        // -- Perhaps we can leave this to GSoC students? --

        // Map arbitrary angle x to the range [-pi; +pi] without using division.
        // Code taken from MSDN's HLSL trick. Architectures with fused mad (i.e. NEON)
        // can replace the add, the sub, & the two muls for two mad
        ArrayReal integralPart;
        x = vaddq_f32( vmulq_f32( x, ONE_DIV_2PI ), HALF );
        x = Modf4( x, integralPart );
        x = vsubq_f32( vmulq_f32( x, TWO_PI ), PI );

        sincos_ps( x, &outSin, &outCos );
    }
コード例 #10
0
ファイル: intrin_neon.hpp プロジェクト: 165-goethals/opencv
inline v_int32x4 v_round(const v_float32x4& a)
{
    static const int32x4_t v_sign = vdupq_n_s32(1 << 31),
        v_05 = vreinterpretq_s32_f32(vdupq_n_f32(0.5f));

    int32x4_t v_addition = vorrq_s32(v_05, vandq_s32(v_sign, vreinterpretq_s32_f32(a.val)));
    return v_int32x4(vcvtq_s32_f32(vaddq_f32(a.val, vreinterpretq_f32_s32(v_addition))));
}
コード例 #11
0
static void FilterFarNEON(
    int num_partitions,
    int x_fft_buf_block_pos,
    float x_fft_buf[2][kExtendedNumPartitions * PART_LEN1],
    float h_fft_buf[2][kExtendedNumPartitions * PART_LEN1],
    float y_fft[2][PART_LEN1]) {
  int i;
  for (i = 0; i < num_partitions; i++) {
    int j;
    int xPos = (i + x_fft_buf_block_pos) * PART_LEN1;
    int pos = i * PART_LEN1;
    // Check for wrap
    if (i + x_fft_buf_block_pos >= num_partitions) {
      xPos -= num_partitions * PART_LEN1;
    }

    // vectorized code (four at once)
    for (j = 0; j + 3 < PART_LEN1; j += 4) {
      const float32x4_t x_fft_buf_re = vld1q_f32(&x_fft_buf[0][xPos + j]);
      const float32x4_t x_fft_buf_im = vld1q_f32(&x_fft_buf[1][xPos + j]);
      const float32x4_t h_fft_buf_re = vld1q_f32(&h_fft_buf[0][pos + j]);
      const float32x4_t h_fft_buf_im = vld1q_f32(&h_fft_buf[1][pos + j]);
      const float32x4_t y_fft_re = vld1q_f32(&y_fft[0][j]);
      const float32x4_t y_fft_im = vld1q_f32(&y_fft[1][j]);
      const float32x4_t a = vmulq_f32(x_fft_buf_re, h_fft_buf_re);
      const float32x4_t e = vmlsq_f32(a, x_fft_buf_im, h_fft_buf_im);
      const float32x4_t c = vmulq_f32(x_fft_buf_re, h_fft_buf_im);
      const float32x4_t f = vmlaq_f32(c, x_fft_buf_im, h_fft_buf_re);
      const float32x4_t g = vaddq_f32(y_fft_re, e);
      const float32x4_t h = vaddq_f32(y_fft_im, f);
      vst1q_f32(&y_fft[0][j], g);
      vst1q_f32(&y_fft[1][j], h);
    }
    // scalar code for the remaining items.
    for (; j < PART_LEN1; j++) {
      y_fft[0][j] += MulRe(x_fft_buf[0][xPos + j],
                           x_fft_buf[1][xPos + j],
                           h_fft_buf[0][pos + j],
                           h_fft_buf[1][pos + j]);
      y_fft[1][j] += MulIm(x_fft_buf[0][xPos + j],
                           x_fft_buf[1][xPos + j],
                           h_fft_buf[0][pos + j],
                           h_fft_buf[1][pos + j]);
    }
  }
}
コード例 #12
0
ファイル: base.hpp プロジェクト: AdLantis/opencv
inline int32x4_t cv_vrndq_s32_f32(float32x4_t v)
{
    static int32x4_t v_sign = vdupq_n_s32(1 << 31),
        v_05 = vreinterpretq_s32_f32(vdupq_n_f32(0.5f));

    int32x4_t v_addition = vorrq_s32(v_05, vandq_s32(v_sign, vreinterpretq_s32_f32(v)));
    return vcvtq_s32_f32(vaddq_f32(v, vreinterpretq_f32_s32(v_addition)));
}
コード例 #13
0
/* Performs one rotation/translation */
static void 
neon_coord_4(
    float32x4_t a_4, 
    float32x4_t b_4,
    float32x4_t x_4, 
    float32x4_t y_4,
    float32x4_t pos_4f, 
    float32x4_t point5_4, 
    int * result)
{
    float32x4_t tmp1 = vmulq_f32(a_4, x_4);
    float32x4_t tmp2 = vmulq_f32(b_4, y_4);
    tmp2 = vaddq_f32(tmp1, tmp2);
    tmp2 = vaddq_f32(tmp2, pos_4f);
    tmp2 = vaddq_f32(tmp2, point5_4);
    int32x4_t c_4 = vcvtq_s32_f32(tmp2);
    vst1q_s32(result, c_4);
}
コード例 #14
0
ファイル: SimdNeonHog.cpp プロジェクト: 4144/Simd
        template <bool align> SIMD_INLINE void HogDirectionHistograms(const float32x4_t & dx, const float32x4_t & dy, Buffer & buffer, size_t col)
        {
            float32x4_t bestDot = vdupq_n_f32(0);
            int32x4_t bestIndex = vdupq_n_s32(0);
            for(int i = 0; i < buffer.size; ++i)
            {
                float32x4_t dot = vaddq_f32(vmulq_f32(dx, buffer.cos[i]), vmulq_f32(dy, buffer.sin[i]));
                uint32x4_t mask = vcgtq_f32(dot, bestDot);
                bestDot = vmaxq_f32(dot, bestDot);
                bestIndex = vbslq_s32(mask, buffer.pos[i], bestIndex);

                dot = vnegq_f32(dot);
                mask = vcgtq_f32(dot, bestDot);
                bestDot = vmaxq_f32(dot, bestDot);
                bestIndex = vbslq_s32(mask, buffer.neg[i], bestIndex);
            }
            Store<align>(buffer.index + col, bestIndex);
            Store<align>(buffer.value + col, Sqrt<SIMD_NEON_RCP_ITER>(vaddq_f32(vmulq_f32(dx, dx), vmulq_f32(dy, dy))));
        }
コード例 #15
0
 template <bool align> SIMD_INLINE void SquaredDifferenceKahanSum32f(const float * a, const float * b, size_t offset, float32x4_t & sum, float32x4_t & correction)
 {
     float32x4_t _a = Load<align>(a + offset);
     float32x4_t _b = Load<align>(b + offset);
     float32x4_t _d = vsubq_f32(_a, _b);
     float32x4_t term = vmlaq_f32(correction, _d, _d);
     float32x4_t temp = vaddq_f32(sum, term);
     correction = vsubq_f32(vmulq_f32(temp, sum), term);
     sum = temp;
 }
コード例 #16
0
ファイル: aec_core_neon.c プロジェクト: RyanLee27/pjproject
static void FilterFarNEON(AecCore* aec, float yf[2][PART_LEN1]) {
  int i;
  const int num_partitions = aec->num_partitions;
  for (i = 0; i < num_partitions; i++) {
    int j;
    int xPos = (i + aec->xfBufBlockPos) * PART_LEN1;
    int pos = i * PART_LEN1;
    // Check for wrap
    if (i + aec->xfBufBlockPos >= num_partitions) {
      xPos -= num_partitions * PART_LEN1;
    }

    // vectorized code (four at once)
    for (j = 0; j + 3 < PART_LEN1; j += 4) {
      const float32x4_t xfBuf_re = vld1q_f32(&aec->xfBuf[0][xPos + j]);
      const float32x4_t xfBuf_im = vld1q_f32(&aec->xfBuf[1][xPos + j]);
      const float32x4_t wfBuf_re = vld1q_f32(&aec->wfBuf[0][pos + j]);
      const float32x4_t wfBuf_im = vld1q_f32(&aec->wfBuf[1][pos + j]);
      const float32x4_t yf_re = vld1q_f32(&yf[0][j]);
      const float32x4_t yf_im = vld1q_f32(&yf[1][j]);
      const float32x4_t a = vmulq_f32(xfBuf_re, wfBuf_re);
      const float32x4_t e = vmlsq_f32(a, xfBuf_im, wfBuf_im);
      const float32x4_t c = vmulq_f32(xfBuf_re, wfBuf_im);
      const float32x4_t f = vmlaq_f32(c, xfBuf_im, wfBuf_re);
      const float32x4_t g = vaddq_f32(yf_re, e);
      const float32x4_t h = vaddq_f32(yf_im, f);
      vst1q_f32(&yf[0][j], g);
      vst1q_f32(&yf[1][j], h);
    }
    // scalar code for the remaining items.
    for (; j < PART_LEN1; j++) {
      yf[0][j] += MulRe(aec->xfBuf[0][xPos + j],
                        aec->xfBuf[1][xPos + j],
                        aec->wfBuf[0][pos + j],
                        aec->wfBuf[1][pos + j]);
      yf[1][j] += MulIm(aec->xfBuf[0][xPos + j],
                        aec->xfBuf[1][xPos + j],
                        aec->wfBuf[0][pos + j],
                        aec->wfBuf[1][pos + j]);
    }
  }
}
コード例 #17
0
ファイル: OgreMathlibNEON.cpp プロジェクト: amerkoleci/mogre
    //-----------------------------------------------------------------------------------
    ArrayReal MathlibNEON::Cos4( ArrayReal x )
    {
        // Map arbitrary angle x to the range [-pi; +pi] without using division.
        // Code taken from MSDN's HLSL trick. Architectures with fused mad (i.e. NEON)
        // can replace the add, the sub, & the two muls for two mad
        ArrayReal integralPart;
        x = vaddq_f32( vmulq_f32( x, ONE_DIV_2PI ), HALF );
        x = Modf4( x, integralPart );
        x = vsubq_f32( vmulq_f32( x, TWO_PI ), PI );

        return cos_ps( x );
    }
コード例 #18
0
void dotProd_neon(const float *data, const float *weights, float *vals, const int n, const int len, const float *istd) {
    for (int i = 0; i < n; i += 4) {
        float32x4_t accum0 = { 0.0f, 0.0f, 0.0f, 0.0f };
        float32x4_t accum1 = accum0;
        float32x4_t accum2 = accum0;
        float32x4_t accum3 = accum0;

        for (int j = 0; j < len; j += 4) {
            float32x4_t d0 = vld1q_f32(data + j);
            float32x4_t d1 = d0;
            float32x4_t d2 = d0;
            float32x4_t d3 = d0;

            float32x4_t w0 = vld1q_f32(weights);
            float32x4_t w1 = vld1q_f32(weights + 4);
            float32x4_t w2 = vld1q_f32(weights + 8);
            float32x4_t w3 = vld1q_f32(weights + 12);

            accum0 = vaddq_f32(accum0, vmulq_f32(d0, w0));
            accum1 = vaddq_f32(accum1, vmulq_f32(d1, w1));
            accum2 = vaddq_f32(accum2, vmulq_f32(d2, w2));
            accum3 = vaddq_f32(accum3, vmulq_f32(d3, w3));

            weights += 16;
        }

        float32x2_t sum0 = vpadd_f32(vget_low_f32(accum0), vget_high_f32(accum0));
        float32x2_t sum1 = vpadd_f32(vget_low_f32(accum1), vget_high_f32(accum1));
        float32x2_t sum2 = vpadd_f32(vget_low_f32(accum2), vget_high_f32(accum2));
        float32x2_t sum3 = vpadd_f32(vget_low_f32(accum3), vget_high_f32(accum3));
        sum0 = vpadd_f32(sum0, sum1);
        sum1 = vpadd_f32(sum2, sum3);
        float32x4_t sum = vcombine_f32(sum0, sum1);
        
        sum = vmulq_n_f32(sum, istd[0]);
        sum = vaddq_f32(sum, vld1q_f32(weights + n*len + i));
        vst1q_f32(vals + i, sum);
    }
}
コード例 #19
0
ファイル: bias_arm.cpp プロジェクト: superhero1991/ncnn
int Bias_arm::forward(const Mat& bottom_blob, Mat& top_blob) const
{
    int w = bottom_blob.w;
    int h = bottom_blob.h;
    int channels = bottom_blob.c;
    int size = w * h;

    top_blob.create(w, h, channels);
    if (top_blob.empty())
        return -100;

    const float* bias_ptr = bias_data;
    #pragma omp parallel for
    for (int q=0; q<channels; q++)
    {
        const float* ptr = bottom_blob.channel(q);
        float* outptr = top_blob.channel(q);

        float bias = bias_ptr[q];

#if __ARM_NEON
        int nn = size >> 2;
        int remain = size - (nn << 2);
#else
        int remain = size;
#endif // __ARM_NEON

#if __ARM_NEON
        float32x4_t _bias = vdupq_n_f32(bias);
        for (; nn>0; nn--)
        {
            float32x4_t _p = vld1q_f32(ptr);
            float32x4_t _outp = vaddq_f32(_p, _bias);
            vst1q_f32(outptr, _outp);

            ptr += 4;
            outptr += 4;
        }
#endif // __ARM_NEON

        for (; remain>0; remain--)
        {
            *outptr = *ptr + bias;

            ptr++;
            outptr++;
        }
    }

    return 0;
}
コード例 #20
0
ファイル: mw_neon.c プロジェクト: Daniel-Hwang/eeg
/* 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);
	}
}
コード例 #21
0
void dotProd_i16_neon(const float *dataf, const float *weightsf, float *vals, const int n, const int len, const float *istd) {
    const int16_t *data = (const int16_t *)dataf;
    const int16_t *weights = (const int16_t *)weightsf;
    weightsf += n * len / 2; // sizeof(float) / sizeof(int16_t)

    for (int i = 0; i < n; i += 4) {
        int32x4_t accum0 = { 0, 0, 0, 0 };
        int32x4_t accum1 = accum0;
        int32x4_t accum2 = accum0;
        int32x4_t accum3 = accum0;

        for (int j = 0; j < len; j += 8) {
            int16x4x2_t d0 = vld2_s16(data + j);

            int16x4x2_t w0 = vld2_s16(weights);
            int16x4x2_t w1 = vld2_s16(weights + 8);
            int16x4x2_t w2 = vld2_s16(weights + 16);
            int16x4x2_t w3 = vld2_s16(weights + 24);

            accum0 = vmlal_s16(accum0, d0.val[0], w0.val[0]);
            accum0 = vmlal_s16(accum0, d0.val[1], w0.val[1]);

            accum1 = vmlal_s16(accum1, d0.val[0], w1.val[0]);
            accum1 = vmlal_s16(accum1, d0.val[1], w1.val[1]);

            accum2 = vmlal_s16(accum2, d0.val[0], w2.val[0]);
            accum2 = vmlal_s16(accum2, d0.val[1], w2.val[1]);

            accum3 = vmlal_s16(accum3, d0.val[0], w3.val[0]);
            accum3 = vmlal_s16(accum3, d0.val[1], w3.val[1]);

            weights += 32;
        }

        int32x2_t sum0 = vpadd_s32(vget_low_s32(accum0), vget_high_s32(accum0));
        int32x2_t sum1 = vpadd_s32(vget_low_s32(accum1), vget_high_s32(accum1));
        int32x2_t sum2 = vpadd_s32(vget_low_s32(accum2), vget_high_s32(accum2));
        int32x2_t sum3 = vpadd_s32(vget_low_s32(accum3), vget_high_s32(accum3));
        sum0 = vpadd_s32(sum0, sum1);
        sum1 = vpadd_s32(sum2, sum3);
        int32x4_t sum = vcombine_s32(sum0, sum1);

        float32x4_t val = vcvtq_f32_s32(sum);
        val = vmulq_f32(val, vld1q_f32(weightsf + i*2));
        val = vmulq_n_f32(val, istd[0]);
        val = vaddq_f32(val, vld1q_f32(weightsf + i*2 + 4));
        vst1q_f32(vals + i, val);
    }
}
コード例 #22
0
//Kernel function: saxpy
void saxpy_vector(KernelArgs* args) {

    //Setup
    const float32x4_t MASK_FALSE = vdupq_n_f32(0.f);
    const float32x4_t MASK_TRUE = vcvtq_f32_u32(vceqq_f32(MASK_FALSE, MASK_FALSE));
    
    //Uniforms
    
    //Fuses
    
    //Literals
    
    //Stack variables
    float32x4_t scale, x, y, result, var060, var061;
    
    //Loop over input
    uint64_t index;
    for(index = 0; index < args->N; index += 4) {
    
        //Inputs
        scale = vld1q_f32(&args->scale[index]);
        x = vld1q_f32(&args->x[index]);
        y = vld1q_f32(&args->y[index]);
        
        //Begin kernel logic
        {
        
            //>>> result = scale * x + y
            var061 = vmulq_f32(scale, x);
            var060 = vaddq_f32(var061, y);
            result = vbslq_f32(vcvtq_u32_f32(MASK_TRUE), var060, result);
        
        }
        //End kernel logic
        
        //Outputs
        vst1q_f32(&args->result[index], result);
        
    }
}
コード例 #23
0
ファイル: mw_neon.c プロジェクト: Daniel-Hwang/eeg
/* f32x4 add */
void mw_neon_mm_add_f32x4(float * A, int Row, int Col, float * B, float * C)
{
	float32x4_t neon_a, neon_b, neon_c;
	int size = Row * Col;
	int i = 0;
	int k = 0;

	for (i = 4; i <= size ; i+=4)
	{
		k = i - 4;
		neon_a = vld1q_f32(A + k);
		neon_b = vld1q_f32(B + k);
		neon_c = vaddq_f32(neon_a, neon_b);
		vst1q_f32(C + k, neon_c);
	}

	k = i - 4;
    for (i = 0; i < size % 4; i++)
	{
		C[k + i] = A[k + i] + B[k + i];
	}
}
コード例 #24
0
// __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;
コード例 #25
0
ファイル: base.hpp プロジェクト: AdLantis/opencv
inline uint32x4_t cv_vrndq_u32_f32(float32x4_t v)
{
    static float32x4_t v_05 = vdupq_n_f32(0.5f);
    return vcvtq_u32_f32(vaddq_f32(v, v_05));
}
コード例 #26
0
ファイル: dotprod_cccf.neon.c プロジェクト: Clivia/liquid-dsp
// use ARM Neon extensions (unrolled loop)
// NOTE: unrolling doesn't show any appreciable performance difference
void dotprod_cccf_execute_neon4(dotprod_cccf    _q,
                                float complex * _x,
                                float complex * _y)
{
    // type cast input as floating point array
    float * x = (float*) _x;

    // double effective length
    unsigned int n = 2*_q->n;

    // first cut: ...
    float32x4_t v0,  v1,  v2,  v3;   // input vectors
    float32x4_t hi0, hi1, hi2, hi3;  // coefficients vectors (real)
    float32x4_t hq0, hq1, hq2, hq3;  // coefficients vectors (imag)
    float32x4_t ci0, ci1, ci2, ci3;  // output multiplications (v * hi)
    float32x4_t cq0, cq1, cq2, cq3;  // output multiplications (v * hq)

    // load zeros into sum registers
    float zeros[4] = {0,0,0,0};
    float32x4_t sumi = vld1q_f32(zeros);
    float32x4_t sumq = vld1q_f32(zeros);

    // r = 4*floor(n/16)
    unsigned int r = (n >> 4) << 2;

    //
    unsigned int i;
    for (i=0; i<r; i+=4) {
        // load inputs into register (unaligned)
        v0 = vld1q_f32(&x[4*i+0]);
        v1 = vld1q_f32(&x[4*i+4]);
        v2 = vld1q_f32(&x[4*i+8]);
        v3 = vld1q_f32(&x[4*i+12]);

        // load real coefficients into registers (aligned)
        hi0 = vld1q_f32(&_q->hi[4*i+0]);
        hi1 = vld1q_f32(&_q->hi[4*i+4]);
        hi2 = vld1q_f32(&_q->hi[4*i+8]);
        hi3 = vld1q_f32(&_q->hi[4*i+12]);

        // load real coefficients into registers (aligned)
        hq0 = vld1q_f32(&_q->hq[4*i+0]);
        hq1 = vld1q_f32(&_q->hq[4*i+4]);
        hq2 = vld1q_f32(&_q->hq[4*i+8]);
        hq3 = vld1q_f32(&_q->hq[4*i+12]);
        
        // compute parallel multiplications (real)
        ci0 = vmulq_f32(v0, hi0);
        ci1 = vmulq_f32(v1, hi1);
        ci2 = vmulq_f32(v2, hi2);
        ci3 = vmulq_f32(v3, hi3);

        // compute parallel multiplications (imag)
        cq0 = vmulq_f32(v0, hq0);
        cq1 = vmulq_f32(v1, hq1);
        cq2 = vmulq_f32(v2, hq2);
        cq3 = vmulq_f32(v3, hq3);

        // accumulate
        sumi = vaddq_f32(sumi, ci0);    sumq = vaddq_f32(sumq, cq0);
        sumi = vaddq_f32(sumi, ci1);    sumq = vaddq_f32(sumq, cq1);
        sumi = vaddq_f32(sumi, ci2);    sumq = vaddq_f32(sumq, cq2);
        sumi = vaddq_f32(sumi, ci3);    sumq = vaddq_f32(sumq, cq3);
    }

    // unload
    float wi[4];
    float wq[4];
    vst1q_f32(wi, sumi);
    vst1q_f32(wq, sumq);

    // fold down (add/sub)
    float complex total = 
        ((wi[0] - wq[1]) + (wi[2] - wq[3])) +
        ((wi[1] + wq[0]) + (wi[3] + wq[2])) * _Complex_I;

    // cleanup (note: n _must_ be even)
    // TODO : clean this method up
    for (i=2*r; i<_q->n; i++) {
        total += _x[i] * ( _q->hi[2*i] + _q->hq[2*i]*_Complex_I );
    }

    // set return value
    *_y = total;
}
コード例 #27
0
ファイル: dotprod_cccf.neon.c プロジェクト: Clivia/liquid-dsp
// use ARM Neon extensions
//
// (a + jb)(c + jd) = (ac - bd) + j(ad + bc)
//
// mm_x  = { x[0].real, x[0].imag, x[1].real, x[1].imag }
// mm_hi = { h[0].real, h[0].real, h[1].real, h[1].real }
// mm_hq = { h[0].imag, h[0].imag, h[1].imag, h[1].imag }
//
// mm_y0 = mm_x * mm_hi
//       = { x[0].real * h[0].real,
//           x[0].imag * h[0].real,
//           x[1].real * h[1].real,
//           x[1].imag * h[1].real };
//
// mm_y1 = mm_x * mm_hq
//       = { x[0].real * h[0].imag,
//           x[0].imag * h[0].imag,
//           x[1].real * h[1].imag,
//           x[1].imag * h[1].imag };
//
void dotprod_cccf_execute_neon(dotprod_cccf    _q,
                               float complex * _x,
                               float complex * _y)
{
    // type cast input as floating point array
    float * x = (float*) _x;

    // double effective length
    unsigned int n = 2*_q->n;

    // temporary buffers
    float32x4_t v;   // input vector
    float32x4_t hi;  // coefficients vector (real)
    float32x4_t hq;  // coefficients vector (imag)
    float32x4_t ci;  // output multiplication (v * hi)
    float32x4_t cq;  // output multiplication (v * hq)

    // output accumulators
    float zeros[4] = {0,0,0,0};
    float32x4_t sumi = vld1q_f32(zeros);
    float32x4_t sumq = vld1q_f32(zeros);

    // t = 4*(floor(_n/4))
    unsigned int t = (n >> 2) << 2;

    //
    unsigned int i;
    for (i=0; i<t; i+=4) {
        // load inputs into register (unaligned)
        // {x[0].real, x[0].imag, x[1].real, x[1].imag}
        v = vld1q_f32(&x[i]);

        // load coefficients into register (aligned)
        // {hi[0].real, hi[0].imag, hi[1].real, hi[1].imag}
        // {hq[0].real, hq[0].imag, hq[1].real, hq[1].imag}
        hi = vld1q_f32(&_q->hi[i]);
        hq = vld1q_f32(&_q->hq[i]);

        // compute parallel multiplications
        ci = vmulq_f32(v, hi);
        cq = vmulq_f32(v, hq);

        // parallel addition
        sumi = vaddq_f32(sumi, ci);
        sumq = vaddq_f32(sumq, cq);
    }

    // unload and combine
    float wi[4];
    float wq[4];
    vst1q_f32(wi, sumi);
    vst1q_f32(wq, sumq);

    // fold down (add/sub)
    float complex total = 
        ((wi[0] - wq[1]) + (wi[2] - wq[3])) +
        ((wi[1] + wq[0]) + (wi[3] + wq[2])) * _Complex_I;

    // cleanup
    for (i=t/2; i<_q->n; i++)
        total += _x[i] * ( _q->hi[2*i] + _q->hq[2*i]*_Complex_I );

    // set return value
    *_y = total;
}
コード例 #28
0
int main (int argc, char **argv) {
  int c = 0;
  int i = 0;
  int j = 0;
  uint num_loops = 0;
  bool interrupt_flag = false;
  uint number_samples = 0;
  uint decim_rate = 0;
  uint fft_size = 0;
  float threshold = 0.0;
  double gain = 0.0;
  int threshold_exceeded = 0;
  float threshold_exceeded_mag = 0.0;
  int threshold_exceeded_index = 0;
  uint32_t start_decision;
  uint32_t stop_decision;
  uint32_t start_sensing;
  uint32_t stop_sensing;
  uint32_t start_overhead;
  uint32_t stop_overhead;
  uint32_t start_dma;
  uint32_t stop_dma;
  float dma_time[30];
  float sensing_time[30];
  float decision_time[30];
  float32x4_t floats_real;
  float32x4_t floats_imag;
  float32x4_t floats_real_sqr;
  float32x4_t floats_imag_sqr;
  float32x4_t floats_add;
  float32x4_t floats_sqroot;
  float32x4_t thresholds;
  uint32x4_t compares;
  uint32_t decisions[4096];
  fftwf_complex *in1;
  fftwf_complex out[8192];  // Must be 2x max FFT size
  fftwf_plan p1;
  struct crash_plblock *usrp_intf_tx;
  struct crash_plblock *usrp_intf_rx;

  // Parse command line arguments
  while (1) {
    static struct option long_options[] = {
      /* These options don't set a flag.
         We distinguish them by their indices. */
      {"interrupt",   no_argument,       0, 'i'},
      {"loop prog",   no_argument,       0, 'l'},
      {"decim",       required_argument, 0, 'd'},
      {"fft size",    required_argument, 0, 'k'},
      {"threshold",   required_argument, 0, 't'},
      {0, 0, 0, 0}
    };
    /* getopt_long stores the option index here. */
    int option_index = 0;
    // 'n' is the short option, ':' means it requires an argument
    c = getopt_long (argc, argv, "ild:k:t:",
                     long_options, &option_index);
    /* Detect the end of the options. */
    if (c == -1) break;

    switch (c) {
      case 'i':
        interrupt_flag = true;
        break;
      case 'l':
        loop_prog = 1;
        break;
      case 'd':
        decim_rate = atoi(optarg);
        break;
      case 'k':
        fft_size = (uint)ceil(log2((double)atoi(optarg)));
        break;
      case 't':
        threshold = atof(optarg);
        break;
      case '?':
        /* getopt_long already printed an error message. */
        break;
      default:
        abort ();
    }
  }
  /* Print any remaining command line arguments (not options). */
  if (optind < argc)
  {
    printf ("Invalid options:\n");
    while (optind < argc) {
      printf ("\t%s\n", argv[optind++]);
    }
    return -1;
  }

  if (decim_rate == 0) {
    printf("INFO: Decimation rate not specified, defaulting to 1\n");
    decim_rate = 1;
  }

  if (decim_rate > 2047) {
    printf("ERROR: Decimation rate too high\n");
    return -1;
  }

  if (fft_size == 0) {
    printf("INFO: FFT size not specified, defaulting to 256\n");
    fft_size = 8;
  }

  // FFT size cannot be greater than 4096 or less than 64
  if (fft_size > 13 || fft_size < 6) {
    printf("ERROR: FFT size cannot be greater than 4096 or less than 64\n");
    return -1;
  }

  if (threshold == 0.0) {
    printf("INFO: Threshold not set, default to 1.0\n");
    threshold = 1.0;
  }

  number_samples = (uint)pow(2.0,(double)fft_size);

  // Set Ctrl-C handler
  signal(SIGINT, ctrl_c);

  // Set this process to be real time
  //struct sched_param param;
  //param.sched_priority = 99;
  //if (sched_setscheduler(0, SCHED_FIFO, & param) != 0) {
  //    perror("sched_setscheduler");
  //    exit(EXIT_FAILURE);
  //}


  usrp_intf_tx = crash_open(USRP_INTF_PLBLOCK_ID,WRITE);
  if (usrp_intf_tx == 0) {
    printf("ERROR: Failed to allocate usrp_intf_tx plblock\n");
    return -1;
  }

  usrp_intf_rx = crash_open(USRP_INTF_PLBLOCK_ID,READ);
  if (usrp_intf_rx == 0) {
    crash_close(usrp_intf_rx);
    printf("ERROR: Failed to allocate usrp_intf_rx plblock\n");
    return -1;
  }

  in1 = (fftw_complex *)(usrp_intf_rx->dma_buff);

  start_overhead = crash_read_reg(usrp_intf_tx->regs,DMA_DEBUG_CNT);
  stop_overhead = crash_read_reg(usrp_intf_tx->regs,DMA_DEBUG_CNT);
  printf("Overhead (us): %f\n",(1e6/150e6)*(stop_overhead - start_overhead));

  do {
    // Set threshold for NEON instruction
    thresholds[0] = threshold;
    thresholds[1] = threshold;
    thresholds[2] = threshold;
    thresholds[3] = threshold;

    // Setup FFTW3
    p1 = fftwf_plan_dft_1d(fft_size, in1, out, FFTW_FORWARD, FFTW_ESTIMATE);

    // Global Reset to get us to a clean slate
    crash_reset(usrp_intf_tx);

    if (interrupt_flag == true) {
      crash_set_bit(usrp_intf_tx->regs,DMA_MM2S_INTERRUPT);
    }
    // Wait for USRP DDR interface to finish calibrating (due to reset). This is necessary
    // as the next steps recalibrate the interface and are ignored if issued while it is
    // currently calibrating.
    while(!crash_get_bit(usrp_intf_tx->regs,USRP_RX_CAL_COMPLETE));
    while(!crash_get_bit(usrp_intf_tx->regs,USRP_TX_CAL_COMPLETE));

    // Set RX phase
    crash_write_reg(usrp_intf_tx->regs,USRP_RX_PHASE_INIT,RX_PHASE_CAL);
    crash_set_bit(usrp_intf_tx->regs,USRP_RX_RESET_CAL);
    //printf("RX PHASE INIT: %d\n",crash_read_reg(usrp_intf_tx->regs,USRP_RX_PHASE_INIT));
    while(!crash_get_bit(usrp_intf_tx->regs,USRP_RX_CAL_COMPLETE));

    // Set TX phase
    crash_write_reg(usrp_intf_tx->regs,USRP_TX_PHASE_INIT,TX_PHASE_CAL);
    crash_set_bit(usrp_intf_tx->regs,USRP_TX_RESET_CAL);
    //printf("TX PHASE INIT: %d\n",crash_read_reg(usrp_intf_tx->regs,USRP_TX_PHASE_INIT));
    while(!crash_get_bit(usrp_intf_tx->regs,USRP_TX_CAL_COMPLETE));

    // Set USRP TX / RX Modes
    while(crash_get_bit(usrp_intf_tx->regs,USRP_UART_BUSY));
    crash_write_reg(usrp_intf_tx->regs,USRP_USRP_MODE_CTRL,CMD_TX_MODE + TX_DAC_RAW_MODE);
    while(crash_get_bit(usrp_intf_tx->regs,USRP_UART_BUSY));
    while(crash_get_bit(usrp_intf_tx->regs,USRP_UART_BUSY));
    crash_write_reg(usrp_intf_tx->regs,USRP_USRP_MODE_CTRL,CMD_RX_MODE + RX_ADC_DSP_MODE);
    while(crash_get_bit(usrp_intf_tx->regs,USRP_UART_BUSY));

    // Setup RX path
    crash_set_bit(usrp_intf_tx->regs, USRP_RX_FIFO_BYPASS);                       // Bypass RX FIFO so stale data in the FIFO does not cause latency
    crash_write_reg(usrp_intf_tx->regs, USRP_AXIS_MASTER_TDEST, DMA_PLBLOCK_ID);  // Set tdest to spec_sense
    crash_write_reg(usrp_intf_tx->regs, USRP_RX_PACKET_SIZE, number_samples);     // Set packet size
    crash_clear_bit(usrp_intf_tx->regs, USRP_RX_FIX2FLOAT_BYPASS);                // Do not bypass fix2float
    if (decim_rate == 1) {
      crash_set_bit(usrp_intf_tx->regs, USRP_RX_CIC_BYPASS);                      // Bypass CIC Filter
      crash_set_bit(usrp_intf_tx->regs, USRP_RX_HB_BYPASS);                       // Bypass HB Filter
      crash_write_reg(usrp_intf_tx->regs, USRP_RX_GAIN, 1);                       // Set gain = 1
    } else if (decim_rate == 2) {
      crash_set_bit(usrp_intf_tx->regs, USRP_RX_CIC_BYPASS);                      // Bypass CIC Filter
      crash_clear_bit(usrp_intf_tx->regs, USRP_RX_HB_BYPASS);                     // Enable HB Filter
      crash_write_reg(usrp_intf_tx->regs, USRP_RX_GAIN, 1);                       // Set gain = 1
    // Even, use both CIC and Halfband filters
    } else if ((decim_rate % 2) == 0) {
      crash_clear_bit(usrp_intf_tx->regs, USRP_RX_CIC_BYPASS);                    // Enable CIC Filter
      crash_write_reg(usrp_intf_tx->regs, USRP_RX_CIC_DECIM, decim_rate/2);       // Set CIC decimation rate (div by 2 as we are using HB filter)
      crash_clear_bit(usrp_intf_tx->regs, USRP_RX_HB_BYPASS);                     // Enable HB Filter
      // Offset CIC bit growth. A 32-bit multiplier in the receive chain allows us
      // to scale the CIC output.
      gain = 26.0-3.0*log2(decim_rate/2);
      gain = (gain > 1.0) ? (ceil(pow(2.0,gain))) : (1.0);                        // Do not allow gain to be set to 0
      crash_write_reg(usrp_intf_tx->regs, USRP_RX_GAIN, (uint32_t)gain);          // Set gain
    // Odd, use only CIC filter
    } else {
      crash_clear_bit(usrp_intf_tx->regs, USRP_RX_CIC_BYPASS);                    // Enable CIC Filter
      crash_write_reg(usrp_intf_tx->regs, USRP_RX_CIC_DECIM, decim_rate);         // Set CIC decimation rate
      crash_set_bit(usrp_intf_tx->regs, USRP_RX_HB_BYPASS);                       // Bypass HB Filter
      //
      gain = 26.0-3.0*log2(decim_rate);
      gain = (gain > 1.0) ? (ceil(pow(2.0,gain))) : (1.0);                        // Do not allow gain to be set to 0
      crash_write_reg(usrp_intf_tx->regs, USRP_RX_GAIN, (uint32_t)gain);          // Set gain
    }

    // Setup TX path
    crash_clear_bit(usrp_intf_tx->regs, USRP_TX_FIX2FLOAT_BYPASS);                // Do not bypass fix2float
    crash_set_bit(usrp_intf_tx->regs, USRP_TX_CIC_BYPASS);                        // Bypass CIC Filter
    crash_set_bit(usrp_intf_tx->regs, USRP_TX_HB_BYPASS);                         // Bypass HB Filter
    crash_write_reg(usrp_intf_tx->regs, USRP_TX_GAIN, 1);                         // Set gain = 1

    // Create a CW signal to transmit
    float *tx_sample = (float*)(usrp_intf_tx->dma_buff);
    for (i = 0; i < 4095; i++) {
      tx_sample[2*i+1] = 0;
      tx_sample[2*i] = 0.5;
    }
    tx_sample[2*4095+1] = 0;
    tx_sample[2*4095] = 0;

    // Load waveform into TX FIFO so it can immediately trigger
    crash_write(usrp_intf_tx, USRP_INTF_PLBLOCK_ID, number_samples);

    crash_set_bit(usrp_intf_tx->regs,USRP_RX_ENABLE);                             // Enable RX

    // First, loop until threshold is exceeded
    j = 0;
    while (threshold_exceeded == 0) {
      crash_read(usrp_intf_rx, USRP_INTF_PLBLOCK_ID, number_samples);
      // Run FFT
      fftwf_execute(p1);
      for (i = 0; i < number_samples/4; i++) {
        // Calculate sqrt(I^2 + Q^2)
        floats_real[0] = out[4*i][0];
        floats_real[1] = out[4*i+1][0];
        floats_real[2] = out[4*i+2][0];
        floats_real[3] = out[4*i+3][0];
        floats_real_sqr = vmulq_f32(floats_real, floats_real);
        floats_imag[0] = out[4*i][1];
        floats_imag[1] = out[4*i+1][1];
        floats_imag[2] = out[4*i+2][1];
        floats_imag[3] = out[4*i+3][1];
        floats_imag_sqr = vmulq_f32(floats_imag, floats_imag);
        floats_add = vaddq_f32(floats_real_sqr,floats_imag_sqr);
        floats_sqroot[0] = sqrt(floats_add[0]);
        floats_sqroot[1] = sqrt(floats_add[1]);
        floats_sqroot[2] = sqrt(floats_add[2]);
        floats_sqroot[3] = sqrt(floats_add[3]);
        compares = vcageq_f32(floats_sqroot,thresholds);
        if (compares[0] == -1) {
          // Do not break loop
          threshold_exceeded = 1;
          // Save threshold data
          threshold_exceeded_mag = floats_sqroot[0];
          threshold_exceeded_index = 4*i;
          break;
        } else if (compares[1] == -1) {
          // Do not break loop
          threshold_exceeded = 1;
          // Save threshold data
          threshold_exceeded_mag = floats_sqroot[1];
          threshold_exceeded_index = 4*i+1;
          break;
        } else if (compares[2] == -1) {
          // Do not break loop
          threshold_exceeded = 1;
          // Save threshold data
          threshold_exceeded_mag = floats_sqroot[2];
          threshold_exceeded_index = 4*i+2;
          break;
        } else if (compares[3] == -1) {
          // Do not break loop
          threshold_exceeded = 1;
          // Save threshold data
          threshold_exceeded_mag = floats_sqroot[3];
          threshold_exceeded_index = 4*i+3;
          break;
        }
      }
      if (j > 10) {
        printf("TIMEOUT: Threshold never exceeded\n");
        goto cleanup;
      }
      j++;
      sleep(1);
    }

    // Second, perform specturm sensing and the spectrum decision
    while (threshold_exceeded == 1) {
      threshold_exceeded = 0;
      crash_read(usrp_intf_rx, USRP_INTF_PLBLOCK_ID, number_samples);
      // Run FFT
      fftwf_execute(p1);
      for (i = 0; i < number_samples/4; i++) {
        // Calculate sqrt(I^2 + Q^2)
        floats_real[0] = out[4*i][0];
        floats_real[1] = out[4*i+1][0];
        floats_real[2] = out[4*i+2][0];
        floats_real[3] = out[4*i+3][0];
        floats_real_sqr = vmulq_f32(floats_real, floats_real);
        floats_imag[0] = out[4*i][1];
        floats_imag[1] = out[4*i+1][1];
        floats_imag[2] = out[4*i+2][1];
        floats_imag[3] = out[4*i+3][1];
        floats_imag_sqr = vmulq_f32(floats_imag, floats_imag);
        floats_add = vaddq_f32(floats_real_sqr,floats_imag_sqr);
        floats_sqroot[0] = sqrt(floats_add[0]);
        floats_sqroot[1] = sqrt(floats_add[1]);
        floats_sqroot[2] = sqrt(floats_add[2]);
        floats_sqroot[3] = sqrt(floats_add[3]);
        compares = vcageq_f32(floats_sqroot,thresholds);
        // Was the threshold exceeded?
        if (compares[0] == -1 || compares[1] == -1 || compares[2] == -1 || compares[3] == -1) {
          // Do not break loop
          threshold_exceeded = 1;
          break;
        }
      }
      if (threshold_exceeded == 0) {
        // Enable TX
        crash_set_bit(usrp_intf_tx->regs,USRP_TX_ENABLE);
      }
    }

    // Calculate how long the DMA and the thresholding took by using a counter in the FPGA
    // running at 150 MHz.
    start_dma = crash_read_reg(usrp_intf_tx->regs,DMA_DEBUG_CNT);
    crash_read(usrp_intf_rx, USRP_INTF_PLBLOCK_ID, number_samples);
    stop_dma = crash_read_reg(usrp_intf_tx->regs,DMA_DEBUG_CNT);

    // Set a huge threshold so we have to examine every bin
    thresholds[0] = 1000000000.0;
    thresholds[1] = 1000000000.0;
    thresholds[2] = 1000000000.0;
    thresholds[3] = 1000000000.0;
    start_sensing = crash_read_reg(usrp_intf_tx->regs,DMA_DEBUG_CNT);
    fftwf_execute(p1);
    for (i = 0; i < number_samples/4; i++) {
      floats_real[0] = out[4*i][0];
      floats_real[1] = out[4*i+1][0];
      floats_real[2] = out[4*i+2][0];
      floats_real[3] = out[4*i+3][0];
      floats_real_sqr = vmulq_f32(floats_real, floats_real);
      floats_imag[0] = out[4*i][1];
      floats_imag[1] = out[4*i+1][1];
      floats_imag[2] = out[4*i+2][1];
      floats_imag[3] = out[4*i+3][1];
      floats_imag_sqr = vmulq_f32(floats_imag, floats_imag);
      floats_add = vaddq_f32(floats_real_sqr,floats_imag_sqr);
      floats_sqroot[0] = sqrt(floats_add[0]);
      floats_sqroot[1] = sqrt(floats_add[1]);
      floats_sqroot[2] = sqrt(floats_add[2]);
      floats_sqroot[3] = sqrt(floats_add[3]);
      compares = vcageq_f32(floats_sqroot,thresholds);
      decisions[4*i] = compares[0];
      decisions[4*i+1] = compares[1];
      decisions[4*i+2] = compares[2];
      decisions[4*i+3] = compares[3];
    }
    stop_sensing = crash_read_reg(usrp_intf_tx->regs,DMA_DEBUG_CNT);

    start_decision = crash_read_reg(usrp_intf_tx->regs,DMA_DEBUG_CNT);
    for (i = 0; i < number_samples; i++) {
        if (decisions[i] == -1) {
        printf("This shouldn't happen\n");
      }
    }
    stop_decision = crash_read_reg(usrp_intf_tx->regs,DMA_DEBUG_CNT);

    // Print threshold information
    printf("Threshold:\t\t\t%f\n",threshold);
    printf("Threshold Exceeded Index:\t%d\n",threshold_exceeded_index);
    printf("Threshold Exceeded Mag:\t\t%f\n",threshold_exceeded_mag);
    printf("DMA Time (us): %f\n",(1e6/150e6)*(stop_dma - start_dma));
    printf("Sensing Time (us): %f\n",(1e6/150e6)*(stop_sensing - start_sensing));
    printf("Decision Time (us): %f\n",(1e6/150e6)*(stop_decision - start_decision));

    // Keep track of times so we can report an average at the end
    if (num_loops < 30) {
      dma_time[num_loops] = (1e6/150e6)*(stop_dma - start_dma);
      sensing_time[num_loops] = (1e6/150e6)*(stop_sensing - start_sensing);
      decision_time[num_loops] = (1e6/150e6)*(stop_decision - start_decision);
    }
    num_loops++;

    if (loop_prog == 1) {
      printf("Ctrl-C to end program after this loop\n");
    }

    // Force printf to flush since. We are at a real-time priority, so it cannot unless we force it.
    fflush(stdout);
    //if (nanosleep(&ask_sleep,&act_sleep) < 0) {
    //    perror("nanosleep");
    //    exit(EXIT_FAILURE);
    //}

cleanup:
    crash_clear_bit(usrp_intf_tx->regs,USRP_RX_ENABLE);                           // Disable RX
    crash_clear_bit(usrp_intf_tx->regs,USRP_TX_ENABLE);                           // Disable TX
    threshold_exceeded = 0;
    threshold_exceeded_mag = 0.0;
    threshold_exceeded_index = 0;
    fftwf_destroy_plan(p1);
    sleep(1);
  } while (loop_prog == 1);

  float dma_time_avg = 0.0;
  float sensing_time_avg = 0.0;
  float decision_time_avg = 0.0;
  if (num_loops > 30) {
    for (i = 0; i < 30; i++) {
      dma_time_avg += dma_time[i];
      sensing_time_avg += sensing_time[i];
      decision_time_avg += decision_time[i];
    }
    dma_time_avg = dma_time_avg/30;
    sensing_time_avg = sensing_time_avg/30;
    decision_time_avg = decision_time_avg/30;
  } else {
    for (i = 0; i < num_loops; i++) {
      dma_time_avg += dma_time[i];
      sensing_time_avg += sensing_time[i];
      decision_time_avg += decision_time[i];
    }
    dma_time_avg = dma_time_avg/num_loops;
    sensing_time_avg = sensing_time_avg/num_loops;
    decision_time_avg = decision_time_avg/num_loops;
  }
  printf("Number of loops: %d\n",num_loops);
  printf("Average DMA time (us): %f\n",dma_time_avg);
  printf("Average Sensing time (us): %f\n",sensing_time_avg);
  printf("Average Decision time (us): %f\n",decision_time_avg);

  crash_close(usrp_intf_tx);
  crash_close(usrp_intf_rx);
  return 0;
}
コード例 #29
0
ファイル: SignalBiquad.c プロジェクト: pingdynasty/heavy
void __hv_biquad_f_win32(SignalBiquad *o, hv_bInf_t *_bIn, hv_bInf_t *_bX0, hv_bInf_t *_bX1, hv_bInf_t *_bX2, hv_bInf_t *_bY1, hv_bInf_t *_bY2, hv_bOutf_t bOut) {
  hv_bInf_t bIn = *_bIn;
  hv_bInf_t bX0 = *_bX0;
  hv_bInf_t bX1 = *_bX1;
  hv_bInf_t bX2 = *_bX2;
  hv_bInf_t bY1 = *_bY1;
  hv_bInf_t bY2 = *_bY2;
#else
void __hv_biquad_f(SignalBiquad *o, hv_bInf_t bIn, hv_bInf_t bX0, hv_bInf_t bX1, hv_bInf_t bX2, hv_bInf_t bY1, hv_bInf_t bY2, hv_bOutf_t bOut) {
#endif
#if HV_SIMD_AVX
  __m256 a = _mm256_mul_ps(bIn, bX0);
  __m256 b = _mm256_mul_ps(o->xm1, bX1);
  __m256 c = _mm256_mul_ps(o->xm2, bX2);
  __m256 d = _mm256_add_ps(a, b);
  __m256 e = _mm256_add_ps(c, d); // bIn*bX0 + o->x1*bX1 + o->x2*bX2
  float y0 = e[0] - o->ym1*bY1[0] - o->ym2*bY2[0];
  float y1 = e[1] - y0*bY1[1] - o->ym1*bY2[1];
  float y2 = e[2] - y1*bY1[2] - y0*bY2[2];
  float y3 = e[3] - y2*bY1[3] - y1*bY2[3];
  float y4 = e[4] - y3*bY1[4] - y2*bY2[4];
  float y5 = e[5] - y4*bY1[5] - y3*bY2[5];
  float y6 = e[6] - y5*bY1[6] - y4*bY2[6];
  float y7 = e[7] - y6*bY1[7] - y5*bY2[7];

  o->xm2 = o->xm1;
  o->xm1 = bIn;
  o->ym1 = y7;
  o->ym2 = y6;

  *bOut = _mm256_set_ps(y7, y6, y5, y4, y3, y2, y1, y0);
#elif HV_SIMD_SSE
  __m128 a = _mm_mul_ps(bIn, bX0);
  __m128 b = _mm_mul_ps(o->xm1, bX1);
  __m128 c = _mm_mul_ps(o->xm2, bX2);
  __m128 d = _mm_add_ps(a, b);
  __m128 e = _mm_add_ps(c, d);

  const float *const bbe = (float *) &e;
  const float *const bbY1 = (float *) &bY1;
  const float *const bbY2 = (float *) &bY2;

  float y0 = bbe[0] - o->ym1*bbY1[0] - o->ym2*bbY2[0];
  float y1 = bbe[1] - y0*bbY1[1] - o->ym1*bbY2[1];
  float y2 = bbe[2] - y1*bbY1[2] - y0*bbY2[2];
  float y3 = bbe[3] - y2*bbY1[3] - y1*bbY2[3];

  o->xm2 = o->xm1;
  o->xm1 = bIn;
  o->ym1 = y3;
  o->ym2 = y2;

  *bOut = _mm_set_ps(y3, y2, y1, y0);
#elif HV_SIMD_NEON
  float32x4_t a = vmulq_f32(bIn, bX0);
  float32x4_t b = vmulq_f32(o->xm1, bX1);
  float32x4_t c = vmulq_f32(o->xm2, bX2);
  float32x4_t d = vaddq_f32(a, b);
  float32x4_t e = vaddq_f32(c, d);
  float y0 = e[0] - o->ym1*bY1[0] - o->ym2*bY2[0];
  float y1 = e[1] - y0*bY1[1] - o->ym1*bY2[1];
  float y2 = e[2] - y1*bY1[2] - y0*bY2[2];
  float y3 = e[3] - y2*bY1[3] - y1*bY2[3];

  o->xm2 = o->xm1;
  o->xm1 = bIn;
  o->ym1 = y3;
  o->ym2 = y2;

  *bOut = (float32x4_t) {y0, y1, y2, y3};
#else
  const float y = bIn*bX0 + o->xm1*bX1 + o->xm2*bX2 - o->ym1*bY1 - o->ym2*bY2;
  o->xm2 = o->xm1; o->xm1 = bIn;
  o->ym2 = o->ym1; o->ym1 = y;
  *bOut = y;
#endif
}
コード例 #30
0
ファイル: aec_rdft_neon.c プロジェクト: dreaflove/webrtc-lib
static void cftmdl_128_neon(float* a) {
  int j;
  const int l = 8;
  const float32x4_t vec_swap_sign = vld1q_f32((float32_t*)k_swap_sign);
  float32x4_t wk1rv = vld1q_f32(cftmdl_wk1r);

  for (j = 0; j < l; j += 2) {
    const float32x2_t a_00 = vld1_f32(&a[j + 0]);
    const float32x2_t a_08 = vld1_f32(&a[j + 8]);
    const float32x2_t a_32 = vld1_f32(&a[j + 32]);
    const float32x2_t a_40 = vld1_f32(&a[j + 40]);
    const float32x4_t a_00_32 = vcombine_f32(a_00, a_32);
    const float32x4_t a_08_40 = vcombine_f32(a_08, a_40);
    const float32x4_t x0r0_0i0_0r1_x0i1 = vaddq_f32(a_00_32, a_08_40);
    const float32x4_t x1r0_1i0_1r1_x1i1 = vsubq_f32(a_00_32, a_08_40);
    const float32x2_t a_16 = vld1_f32(&a[j + 16]);
    const float32x2_t a_24 = vld1_f32(&a[j + 24]);
    const float32x2_t a_48 = vld1_f32(&a[j + 48]);
    const float32x2_t a_56 = vld1_f32(&a[j + 56]);
    const float32x4_t a_16_48 = vcombine_f32(a_16, a_48);
    const float32x4_t a_24_56 = vcombine_f32(a_24, a_56);
    const float32x4_t x2r0_2i0_2r1_x2i1 = vaddq_f32(a_16_48, a_24_56);
    const float32x4_t x3r0_3i0_3r1_x3i1 = vsubq_f32(a_16_48, a_24_56);
    const float32x4_t xx0 = vaddq_f32(x0r0_0i0_0r1_x0i1, x2r0_2i0_2r1_x2i1);
    const float32x4_t xx1 = vsubq_f32(x0r0_0i0_0r1_x0i1, x2r0_2i0_2r1_x2i1);
    const float32x4_t x3i0_3r0_3i1_x3r1 = vrev64q_f32(x3r0_3i0_3r1_x3i1);
    const float32x4_t x1_x3_add =
        vmlaq_f32(x1r0_1i0_1r1_x1i1, vec_swap_sign, x3i0_3r0_3i1_x3r1);
    const float32x4_t x1_x3_sub =
        vmlsq_f32(x1r0_1i0_1r1_x1i1, vec_swap_sign, x3i0_3r0_3i1_x3r1);
    const float32x2_t yy0_a = vdup_lane_f32(vget_high_f32(x1_x3_add), 0);
    const float32x2_t yy0_s = vdup_lane_f32(vget_high_f32(x1_x3_sub), 0);
    const float32x4_t yy0_as = vcombine_f32(yy0_a, yy0_s);
    const float32x2_t yy1_a = vdup_lane_f32(vget_high_f32(x1_x3_add), 1);
    const float32x2_t yy1_s = vdup_lane_f32(vget_high_f32(x1_x3_sub), 1);
    const float32x4_t yy1_as = vcombine_f32(yy1_a, yy1_s);
    const float32x4_t yy0 = vmlaq_f32(yy0_as, vec_swap_sign, yy1_as);
    const float32x4_t yy4 = vmulq_f32(wk1rv, yy0);
    const float32x4_t xx1_rev = vrev64q_f32(xx1);
    const float32x4_t yy4_rev = vrev64q_f32(yy4);

    vst1_f32(&a[j + 0], vget_low_f32(xx0));
    vst1_f32(&a[j + 32], vget_high_f32(xx0));
    vst1_f32(&a[j + 16], vget_low_f32(xx1));
    vst1_f32(&a[j + 48], vget_high_f32(xx1_rev));

    a[j + 48] = -a[j + 48];

    vst1_f32(&a[j + 8], vget_low_f32(x1_x3_add));
    vst1_f32(&a[j + 24], vget_low_f32(x1_x3_sub));
    vst1_f32(&a[j + 40], vget_low_f32(yy4));
    vst1_f32(&a[j + 56], vget_high_f32(yy4_rev));
  }

  {
    const int k = 64;
    const int k1 = 2;
    const int k2 = 2 * k1;
    const float32x4_t wk2rv = vld1q_f32(&rdft_wk2r[k2 + 0]);
    const float32x4_t wk2iv = vld1q_f32(&rdft_wk2i[k2 + 0]);
    const float32x4_t wk1iv = vld1q_f32(&rdft_wk1i[k2 + 0]);
    const float32x4_t wk3rv = vld1q_f32(&rdft_wk3r[k2 + 0]);
    const float32x4_t wk3iv = vld1q_f32(&rdft_wk3i[k2 + 0]);
    wk1rv = vld1q_f32(&rdft_wk1r[k2 + 0]);
    for (j = k; j < l + k; j += 2) {
      const float32x2_t a_00 = vld1_f32(&a[j + 0]);
      const float32x2_t a_08 = vld1_f32(&a[j + 8]);
      const float32x2_t a_32 = vld1_f32(&a[j + 32]);
      const float32x2_t a_40 = vld1_f32(&a[j + 40]);
      const float32x4_t a_00_32 = vcombine_f32(a_00, a_32);
      const float32x4_t a_08_40 = vcombine_f32(a_08, a_40);
      const float32x4_t x0r0_0i0_0r1_x0i1 = vaddq_f32(a_00_32, a_08_40);
      const float32x4_t x1r0_1i0_1r1_x1i1 = vsubq_f32(a_00_32, a_08_40);
      const float32x2_t a_16 = vld1_f32(&a[j + 16]);
      const float32x2_t a_24 = vld1_f32(&a[j + 24]);
      const float32x2_t a_48 = vld1_f32(&a[j + 48]);
      const float32x2_t a_56 = vld1_f32(&a[j + 56]);
      const float32x4_t a_16_48 = vcombine_f32(a_16, a_48);
      const float32x4_t a_24_56 = vcombine_f32(a_24, a_56);
      const float32x4_t x2r0_2i0_2r1_x2i1 = vaddq_f32(a_16_48, a_24_56);
      const float32x4_t x3r0_3i0_3r1_x3i1 = vsubq_f32(a_16_48, a_24_56);
      const float32x4_t xx = vaddq_f32(x0r0_0i0_0r1_x0i1, x2r0_2i0_2r1_x2i1);
      const float32x4_t xx1 = vsubq_f32(x0r0_0i0_0r1_x0i1, x2r0_2i0_2r1_x2i1);
      const float32x4_t x3i0_3r0_3i1_x3r1 = vrev64q_f32(x3r0_3i0_3r1_x3i1);
      const float32x4_t x1_x3_add =
          vmlaq_f32(x1r0_1i0_1r1_x1i1, vec_swap_sign, x3i0_3r0_3i1_x3r1);
      const float32x4_t x1_x3_sub =
          vmlsq_f32(x1r0_1i0_1r1_x1i1, vec_swap_sign, x3i0_3r0_3i1_x3r1);
      float32x4_t xx4 = vmulq_f32(wk2rv, xx1);
      float32x4_t xx12 = vmulq_f32(wk1rv, x1_x3_add);
      float32x4_t xx22 = vmulq_f32(wk3rv, x1_x3_sub);
      xx4 = vmlaq_f32(xx4, wk2iv, vrev64q_f32(xx1));
      xx12 = vmlaq_f32(xx12, wk1iv, vrev64q_f32(x1_x3_add));
      xx22 = vmlaq_f32(xx22, wk3iv, vrev64q_f32(x1_x3_sub));

      vst1_f32(&a[j + 0], vget_low_f32(xx));
      vst1_f32(&a[j + 32], vget_high_f32(xx));
      vst1_f32(&a[j + 16], vget_low_f32(xx4));
      vst1_f32(&a[j + 48], vget_high_f32(xx4));
      vst1_f32(&a[j + 8], vget_low_f32(xx12));
      vst1_f32(&a[j + 40], vget_high_f32(xx12));
      vst1_f32(&a[j + 24], vget_low_f32(xx22));
      vst1_f32(&a[j + 56], vget_high_f32(xx22));
    }
  }
}