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dnn: prefer to use v_fma() instead of v_c += v_a * v_b

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pull/19015/head
Alexander Alekhin 4 years ago
parent 12a36b5a94
commit 00f36a3149
2 changed files with 32 additions and 27 deletions
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  1. 45
      modules/dnn/src/layers/convolution_layer.cpp
  2. 14
      modules/dnn/src/layers/fully_connected_layer.cpp

45
modules/dnn/src/layers/convolution_layer.cpp
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@ -1370,15 +1370,15 @@ public:
v_float32x4 r2 = v_load_aligned(rptr + vsz_a*2);
v_float32x4 r3 = v_load_aligned(rptr + vsz_a*3);
vs00 += w0*r0;
vs01 += w0*r1;
vs02 += w0*r2;
vs03 += w0*r3;
vs10 += w1*r0;
vs11 += w1*r1;
vs12 += w1*r2;
vs13 += w1*r3;
vs00 = v_fma(w0, r0, vs00);
vs01 = v_fma(w0, r1, vs01);
vs02 = v_fma(w0, r2, vs02);
vs03 = v_fma(w0, r3, vs03);
vs10 = v_fma(w1, r0, vs10);
vs11 = v_fma(w1, r1, vs11);
vs12 = v_fma(w1, r2, vs12);
vs13 = v_fma(w1, r3, vs13);
}
s0 += v_reduce_sum4(vs00, vs01, vs02, vs03);
s1 += v_reduce_sum4(vs10, vs11, vs12, vs13);
@ -2035,20 +2035,21 @@ public:
for( ; n <= nmax - 4; n += 4 )
{
v_float32x4 d0 = v_load(dst0 + n);
v_float32x4 d1 = v_load(dst1 + n);
v_float32x4 b0 = v_load(bptr0 + n);
v_float32x4 b1 = v_load(bptr1 + n);
v_float32x4 b2 = v_load(bptr2 + n);
v_float32x4 b3 = v_load(bptr3 + n);
v_float32x4 d0 = v_load(dst0 + n);
v_float32x4 d1 = v_load(dst1 + n);
d0 += b0*a00;
d1 += b0*a01;
d0 += b1*a10;
d1 += b1*a11;
d0 += b2*a20;
d1 += b2*a21;
d0 += b3*a30;
d1 += b3*a31;
// TODO try to improve pipeline width
d0 = v_fma(b0, a00, d0);
d1 = v_fma(b0, a01, d1);
d0 = v_fma(b1, a10, d0);
d1 = v_fma(b1, a11, d1);
d0 = v_fma(b2, a20, d0);
d1 = v_fma(b2, a21, d1);
d0 = v_fma(b3, a30, d0);
d1 = v_fma(b3, a31, d1);
v_store(dst0 + n, d0);
v_store(dst1 + n, d1);
}
@ -2056,8 +2057,10 @@ public:
for( ; n < nmax; n++ )
{
float b0 = bptr0[n], b1 = bptr1[n];
float b2 = bptr2[n], b3 = bptr3[n];
float b0 = bptr0[n];
float b1 = bptr1[n];
float b2 = bptr2[n];
float b3 = bptr3[n];
float d0 = dst0[n] + alpha00*b0 + alpha10*b1 + alpha20*b2 + alpha30*b3;
float d1 = dst1[n] + alpha01*b0 + alpha11*b1 + alpha21*b2 + alpha31*b3;
dst0[n] = d0;

14
modules/dnn/src/layers/fully_connected_layer.cpp
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@ -241,16 +241,18 @@ public:
#if CV_SIMD128
for( ; i <= nw - 4; i += 4, wptr += 4*wstep )
{
v_float32x4 vs0 = v_setall_f32(0.f), vs1 = v_setall_f32(0.f);
v_float32x4 vs2 = v_setall_f32(0.f), vs3 = v_setall_f32(0.f);
v_float32x4 vs0 = v_setall_f32(0.f);
v_float32x4 vs1 = v_setall_f32(0.f);
v_float32x4 vs2 = v_setall_f32(0.f);
v_float32x4 vs3 = v_setall_f32(0.f);
for( k = 0; k < vecsize; k += 4 )
{
v_float32x4 v = v_load_aligned(sptr + k);
vs0 += v*v_load_aligned(wptr + k);
vs1 += v*v_load_aligned(wptr + wstep + k);
vs2 += v*v_load_aligned(wptr + wstep*2 + k);
vs3 += v*v_load_aligned(wptr + wstep*3 + k);
vs0 = v_fma(v, v_load_aligned(wptr + k), vs0);
vs1 = v_fma(v, v_load_aligned(wptr + wstep + k), vs1);
vs2 = v_fma(v, v_load_aligned(wptr + wstep*2 + k), vs2);
vs3 = v_fma(v, v_load_aligned(wptr + wstep*3 + k), vs3);
}
v_float32x4 s = v_reduce_sum4(vs0, vs1, vs2, vs3);

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