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Code refactor: use float4 instead of intrinsics for CPU denoise filtering. 

Differential Revision: https://developer.blender.org/D2764
This commit is contained in:
Brecht Van Lommel 2017-07-19 01:54:56 +02:00
parent a24fbf3323
commit ee77c1e917
9 changed files with 71 additions and 119 deletions
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80
intern/cycles/kernel/filter/filter_features_sse.h
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@ -16,7 +16,7 @@
CCL_NAMESPACE_BEGIN
#define ccl_get_feature_sse(pass) _mm_loadu_ps(buffer + (pass)*pass_stride)
#define ccl_get_feature_sse(pass) load_float4(buffer + (pass)*pass_stride)
/* Loop over the pixels in the range [low.x, high.x) x [low.y, high.y), 4 at a time.
* pixel_buffer always points to the first of the 4 current pixel in the first pass.
@ -24,25 +24,25 @@ CCL_NAMESPACE_BEGIN
#define FOR_PIXEL_WINDOW_SSE pixel_buffer = buffer + (low.y - rect.y)*buffer_w + (low.x - rect.x); \
for(pixel.y = low.y; pixel.y < high.y; pixel.y++) { \
__m128 y4 = _mm_set1_ps(pixel.y); \
float4 y4 = make_float4(pixel.y); \
for(pixel.x = low.x; pixel.x < high.x; pixel.x += 4, pixel_buffer += 4) { \
__m128 x4 = _mm_add_ps(_mm_set1_ps(pixel.x), _mm_set_ps(3.0f, 2.0f, 1.0f, 0.0f)); \
__m128 active_pixels = _mm_cmplt_ps(x4, _mm_set1_ps(high.x));
float4 x4 = make_float4(pixel.x) + make_float4(0.0f, 1.0f, 2.0f, 3.0f); \
int4 active_pixels = x4 < make_float4(high.x);
#define END_FOR_PIXEL_WINDOW_SSE } \
pixel_buffer += buffer_w - (pixel.x - low.x); \
}
ccl_device_inline void filter_get_features_sse(__m128 x, __m128 y,
__m128 active_pixels,
ccl_device_inline void filter_get_features_sse(float4 x, float4 y,
int4 active_pixels,
const float *ccl_restrict buffer,
__m128 *features,
const __m128 *ccl_restrict mean,
float4 *features,
const float4 *ccl_restrict mean,
int pass_stride)
{
features[0] = x;
features[1] = y;
features[2] = _mm_fabs_ps(ccl_get_feature_sse(0));
features[2] = fabs(ccl_get_feature_sse(0));
features[3] = ccl_get_feature_sse(1);
features[4] = ccl_get_feature_sse(2);
features[5] = ccl_get_feature_sse(3);
@ -52,53 +52,41 @@ ccl_device_inline void filter_get_features_sse(__m128 x, __m128 y,
features[9] = ccl_get_feature_sse(7);
if(mean) {
for(int i = 0; i < DENOISE_FEATURES; i++)
features[i] = _mm_sub_ps(features[i], mean[i]);
features[i] = features[i] - mean[i];
}
for(int i = 0; i < DENOISE_FEATURES; i++)
features[i] = _mm_mask_ps(features[i], active_pixels);
features[i] = mask(active_pixels, features[i]);
}
ccl_device_inline void filter_get_feature_scales_sse(__m128 x, __m128 y,
__m128 active_pixels,
ccl_device_inline void filter_get_feature_scales_sse(float4 x, float4 y,
int4 active_pixels,
const float *ccl_restrict buffer,
__m128 *scales,
const __m128 *ccl_restrict mean,
float4 *scales,
const float4 *ccl_restrict mean,
int pass_stride)
{
scales[0] = _mm_mask_ps(_mm_fabs_ps(_mm_sub_ps(x, mean[0])), active_pixels);
scales[1] = _mm_mask_ps(_mm_fabs_ps(_mm_sub_ps(y, mean[1])), active_pixels);
scales[2] = _mm_mask_ps(_mm_fabs_ps(_mm_sub_ps(_mm_fabs_ps(ccl_get_feature_sse(0)), mean[2])), active_pixels);
__m128 diff, scale;
diff = _mm_sub_ps(ccl_get_feature_sse(1), mean[3]);
scale = _mm_mul_ps(diff, diff);
diff = _mm_sub_ps(ccl_get_feature_sse(2), mean[4]);
scale = _mm_add_ps(scale, _mm_mul_ps(diff, diff));
diff = _mm_sub_ps(ccl_get_feature_sse(3), mean[5]);
scale = _mm_add_ps(scale, _mm_mul_ps(diff, diff));
scales[3] = _mm_mask_ps(scale, active_pixels);
scales[4] = _mm_mask_ps(_mm_fabs_ps(_mm_sub_ps(ccl_get_feature_sse(4), mean[6])), active_pixels);
diff = _mm_sub_ps(ccl_get_feature_sse(5), mean[7]);
scale = _mm_mul_ps(diff, diff);
diff = _mm_sub_ps(ccl_get_feature_sse(6), mean[8]);
scale = _mm_add_ps(scale, _mm_mul_ps(diff, diff));
diff = _mm_sub_ps(ccl_get_feature_sse(7), mean[9]);
scale = _mm_add_ps(scale, _mm_mul_ps(diff, diff));
scales[5] = _mm_mask_ps(scale, active_pixels);
scales[0] = fabs(x - mean[0]);
scales[1] = fabs(y - mean[1]);
scales[2] = fabs(fabs(ccl_get_feature_sse(0)) - mean[2]);
scales[3] = sqr(ccl_get_feature_sse(1) - mean[3]) +
sqr(ccl_get_feature_sse(2) - mean[4]) +
sqr(ccl_get_feature_sse(3) - mean[5]);
scales[4] = fabs(ccl_get_feature_sse(4) - mean[6]);
scales[5] = sqr(ccl_get_feature_sse(5) - mean[7]) +
sqr(ccl_get_feature_sse(6) - mean[8]) +
sqr(ccl_get_feature_sse(7) - mean[9]);
for(int i = 0; i < 6; i++)
scales[i] = mask(active_pixels, scales[i]);
}
ccl_device_inline void filter_calculate_scale_sse(__m128 *scale)
ccl_device_inline void filter_calculate_scale_sse(float4 *scale)
{
scale[0] = _mm_div_ps(_mm_set1_ps(1.0f), _mm_max_ps(_mm_hmax_ps(scale[0]), _mm_set1_ps(0.01f)));
scale[1] = _mm_div_ps(_mm_set1_ps(1.0f), _mm_max_ps(_mm_hmax_ps(scale[1]), _mm_set1_ps(0.01f)));
scale[2] = _mm_div_ps(_mm_set1_ps(1.0f), _mm_max_ps(_mm_hmax_ps(scale[2]), _mm_set1_ps(0.01f)));
scale[6] = _mm_div_ps(_mm_set1_ps(1.0f), _mm_max_ps(_mm_hmax_ps(scale[4]), _mm_set1_ps(0.01f)));
scale[7] = scale[8] = scale[9] = _mm_div_ps(_mm_set1_ps(1.0f), _mm_max_ps(_mm_hmax_ps(_mm_sqrt_ps(scale[5])), _mm_set1_ps(0.01f)));
scale[3] = scale[4] = scale[5] = _mm_div_ps(_mm_set1_ps(1.0f), _mm_max_ps(_mm_hmax_ps(_mm_sqrt_ps(scale[3])), _mm_set1_ps(0.01f)));
scale[0] = rcp(max(reduce_max(scale[0]), make_float4(0.01f)));
scale[1] = rcp(max(reduce_max(scale[1]), make_float4(0.01f)));
scale[2] = rcp(max(reduce_max(scale[2]), make_float4(0.01f)));
scale[6] = rcp(max(reduce_max(scale[4]), make_float4(0.01f)));
scale[7] = scale[8] = scale[9] = rcp(max(reduce_max(sqrt(scale[5])), make_float4(0.01f)));
scale[3] = scale[4] = scale[5] = rcp(max(reduce_max(sqrt(scale[3])), make_float4(0.01f)));
}

18
intern/cycles/kernel/filter/filter_nlm_cpu.h
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@ -50,10 +50,8 @@ ccl_device_inline void kernel_filter_nlm_blur(const float *ccl_restrict differen
int w,
int f)
{
#ifdef __KERNEL_SSE3__
int aligned_lowx = (rect.x & ~(3));
int aligned_highx = ((rect.z + 3) & ~(3));
#endif
int aligned_lowx = rect.x / 4;
int aligned_highx = (rect.z + 3) / 4;
for(int y = rect.y; y < rect.w; y++) {
const int low = max(rect.y, y-f);
const int high = min(rect.w, y+f+1);
@ -61,15 +59,11 @@ ccl_device_inline void kernel_filter_nlm_blur(const float *ccl_restrict differen
out_image[y*w+x] = 0.0f;
}
for(int y1 = low; y1 < high; y1++) {
#ifdef __KERNEL_SSE3__
for(int x = aligned_lowx; x < aligned_highx; x+=4) {
_mm_store_ps(out_image + y*w+x, _mm_add_ps(_mm_load_ps(out_image + y*w+x), _mm_load_ps(difference_image + y1*w+x)));
float4* out_image4 = (float4*)(out_image + y*w);
float4* difference_image4 = (float4*)(difference_image + y1*w);
for(int x = aligned_lowx; x < aligned_highx; x++) {
out_image4[x] += difference_image4[x];
}
#else
for(int x = rect.x; x < rect.z; x++) {
out_image[y*w+x] += difference_image[y1*w+x];
}
#endif
}
for(int x = rect.x; x < rect.z; x++) {
out_image[y*w+x] *= 1.0f/(high - low);

16
intern/cycles/kernel/filter/filter_transform_sse.h
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@ -24,7 +24,7 @@ ccl_device void kernel_filter_construct_transform(const float *ccl_restrict buff
{
int buffer_w = align_up(rect.z - rect.x, 4);
__m128 features[DENOISE_FEATURES];
float4 features[DENOISE_FEATURES];
const float *ccl_restrict pixel_buffer;
int2 pixel;
@ -34,19 +34,19 @@ ccl_device void kernel_filter_construct_transform(const float *ccl_restrict buff
min(rect.w, y + radius + 1));
int num_pixels = (high.y - low.y) * (high.x - low.x);
__m128 feature_means[DENOISE_FEATURES];
float4 feature_means[DENOISE_FEATURES];
math_vector_zero_sse(feature_means, DENOISE_FEATURES);
FOR_PIXEL_WINDOW_SSE {
filter_get_features_sse(x4, y4, active_pixels, pixel_buffer, features, NULL, pass_stride);
math_vector_add_sse(feature_means, DENOISE_FEATURES, features);
} END_FOR_PIXEL_WINDOW_SSE
__m128 pixel_scale = _mm_set1_ps(1.0f / num_pixels);
float4 pixel_scale = make_float4(1.0f / num_pixels);
for(int i = 0; i < DENOISE_FEATURES; i++) {
feature_means[i] = _mm_mul_ps(_mm_hsum_ps(feature_means[i]), pixel_scale);
feature_means[i] = reduce_add(feature_means[i]) * pixel_scale;
}
__m128 feature_scale[DENOISE_FEATURES];
float4 feature_scale[DENOISE_FEATURES];
math_vector_zero_sse(feature_scale, DENOISE_FEATURES);
FOR_PIXEL_WINDOW_SSE {
filter_get_feature_scales_sse(x4, y4, active_pixels, pixel_buffer, features, feature_means, pass_stride);
@ -55,12 +55,12 @@ ccl_device void kernel_filter_construct_transform(const float *ccl_restrict buff
filter_calculate_scale_sse(feature_scale);
__m128 feature_matrix_sse[DENOISE_FEATURES*DENOISE_FEATURES];
float4 feature_matrix_sse[DENOISE_FEATURES*DENOISE_FEATURES];
math_matrix_zero_sse(feature_matrix_sse, DENOISE_FEATURES);
FOR_PIXEL_WINDOW_SSE {
filter_get_features_sse(x4, y4, active_pixels, pixel_buffer, features, feature_means, pass_stride);
math_vector_mul_sse(features, DENOISE_FEATURES, feature_scale);
math_matrix_add_gramian_sse(feature_matrix_sse, DENOISE_FEATURES, features, _mm_set1_ps(1.0f));
math_matrix_add_gramian_sse(feature_matrix_sse, DENOISE_FEATURES, features, make_float4(1.0f));
} END_FOR_PIXEL_WINDOW_SSE
float feature_matrix[DENOISE_FEATURES*DENOISE_FEATURES];
@ -98,7 +98,7 @@ ccl_device void kernel_filter_construct_transform(const float *ccl_restrict buff
/* Bake the feature scaling into the transformation matrix. */
for(int i = 0; i < DENOISE_FEATURES; i++) {
math_vector_scale(transform + i*DENOISE_FEATURES, _mm_cvtss_f32(feature_scale[i]), *rank);
math_vector_scale(transform + i*DENOISE_FEATURES, feature_scale[i][0], *rank);
}
}

1
intern/cycles/kernel/kernels/cpu/filter_sse2.cpp
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@ -25,6 +25,7 @@
#else
/* SSE optimization disabled for now on 32 bit, see bug #36316 */
# if !(defined(__GNUC__) && (defined(i386) || defined(_M_IX86)))
# define __KERNEL_SSE__
# define __KERNEL_SSE2__
# endif
#endif /* WITH_CYCLES_OPTIMIZED_KERNEL_SSE2 */

1
intern/cycles/kernel/kernels/cpu/filter_sse3.cpp
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@ -25,6 +25,7 @@
#else
/* SSE optimization disabled for now on 32 bit, see bug #36316 */
# if !(defined(__GNUC__) && (defined(i386) || defined(_M_IX86)))
# define __KERNEL_SSE__
# define __KERNEL_SSE2__
# define __KERNEL_SSE3__
# define __KERNEL_SSSE3__

1
intern/cycles/kernel/kernels/cpu/filter_sse41.cpp
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@ -25,6 +25,7 @@
#else
/* SSE optimization disabled for now on 32 bit, see bug #36316 */
# if !(defined(__GNUC__) && (defined(i386) || defined(_M_IX86)))
# define __KERNEL_SSE__
# define __KERNEL_SSE2__
# define __KERNEL_SSE3__
# define __KERNEL_SSSE3__

12
intern/cycles/util/util_math_float4.h
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@ -52,7 +52,6 @@ ccl_device_inline float4 sqrt(const float4& a);
ccl_device_inline float4 sqr(const float4& a);
ccl_device_inline float4 cross(const float4& a, const float4& b);
ccl_device_inline bool is_zero(const float4& a);
ccl_device_inline float reduce_add(const float4& a);
ccl_device_inline float average(const float4& a);
ccl_device_inline float len(const float4& a);
ccl_device_inline float4 normalize(const float4& a);
@ -85,6 +84,7 @@ ccl_device_inline float4 select(const int4& mask,
const float4& b);
ccl_device_inline float4 reduce_min(const float4& a);
ccl_device_inline float4 reduce_max(const float4& a);
ccl_device_inline float4 reduce_add(const float4& a);
#endif /* !__KERNEL_GPU__ */
/*******************************************************************************
@ -275,24 +275,24 @@ ccl_device_inline bool is_zero(const float4& a)
#endif
}
ccl_device_inline float reduce_add(const float4& a)
ccl_device_inline float4 reduce_add(const float4& a)
{
#ifdef __KERNEL_SSE__
# ifdef __KERNEL_SSE3__
float4 h(_mm_hadd_ps(a.m128, a.m128));
return _mm_cvtss_f32(_mm_hadd_ps(h.m128, h.m128));
return float4( _mm_hadd_ps(h.m128, h.m128));
# else
float4 h(shuffle<1,0,3,2>(a) + a);
return _mm_cvtss_f32(shuffle<2,3,0,1>(h) + h);
return shuffle<2,3,0,1>(h) + h;
# endif
#else
return ((a.x + a.y) + (a.z + a.w));
return make_float4(((a.x + a.y) + (a.z + a.w)));
#endif
}
ccl_device_inline float average(const float4& a)
{
return reduce_add(a) * 0.25f;
return reduce_add(a)[0] * 0.25f;
}
ccl_device_inline float len(const float4& a)

28
intern/cycles/util/util_math_matrix.h
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@ -339,59 +339,59 @@ ccl_device void math_matrix_jacobi_eigendecomposition(float *A, ccl_global float
}
#ifdef __KERNEL_SSE3__
ccl_device_inline void math_vector_zero_sse(__m128 *A, int n)
ccl_device_inline void math_vector_zero_sse(float4 *A, int n)
{
for(int i = 0; i < n; i++) {
A[i] = _mm_setzero_ps();
A[i] = make_float4(0.0f);
}
}
ccl_device_inline void math_matrix_zero_sse(__m128 *A, int n)
ccl_device_inline void math_matrix_zero_sse(float4 *A, int n)
{
for(int row = 0; row < n; row++) {
for(int col = 0; col <= row; col++) {
MAT(A, n, row, col) = _mm_setzero_ps();
MAT(A, n, row, col) = make_float4(0.0f);
}
}
}
/* Add Gramian matrix of v to A.
* The Gramian matrix of v is v^T*v, so element (i,j) is v[i]*v[j]. */
ccl_device_inline void math_matrix_add_gramian_sse(__m128 *A, int n, const __m128 *ccl_restrict v, __m128 weight)
ccl_device_inline void math_matrix_add_gramian_sse(float4 *A, int n, const float4 *ccl_restrict v, float4 weight)
{
for(int row = 0; row < n; row++) {
for(int col = 0; col <= row; col++) {
MAT(A, n, row, col) = _mm_add_ps(MAT(A, n, row, col), _mm_mul_ps(_mm_mul_ps(v[row], v[col]), weight));
MAT(A, n, row, col) = MAT(A, n, row, col) + v[row] * v[col] * weight;
}
}
}
ccl_device_inline void math_vector_add_sse(__m128 *V, int n, const __m128 *ccl_restrict a)
ccl_device_inline void math_vector_add_sse(float4 *V, int n, const float4 *ccl_restrict a)
{
for(int i = 0; i < n; i++) {
V[i] = _mm_add_ps(V[i], a[i]);
V[i] += a[i];
}
}
ccl_device_inline void math_vector_mul_sse(__m128 *V, int n, const __m128 *ccl_restrict a)
ccl_device_inline void math_vector_mul_sse(float4 *V, int n, const float4 *ccl_restrict a)
{
for(int i = 0; i < n; i++) {
V[i] = _mm_mul_ps(V[i], a[i]);
V[i] *= a[i];
}
}
ccl_device_inline void math_vector_max_sse(__m128 *a, const __m128 *ccl_restrict b, int n)
ccl_device_inline void math_vector_max_sse(float4 *a, const float4 *ccl_restrict b, int n)
{
for(int i = 0; i < n; i++) {
a[i] = _mm_max_ps(a[i], b[i]);
a[i] = max(a[i], b[i]);
}
}
ccl_device_inline void math_matrix_hsum(float *A, int n, const __m128 *ccl_restrict B)
ccl_device_inline void math_matrix_hsum(float *A, int n, const float4 *ccl_restrict B)
{
for(int row = 0; row < n; row++) {
for(int col = 0; col <= row; col++) {
MAT(A, n, row, col) = _mm_hsum_ss(MAT(B, n, row, col));
MAT(A, n, row, col) = reduce_add(MAT(B, n, row, col))[0];
}
}
}

33
intern/cycles/util/util_simd.h
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@ -417,39 +417,6 @@ __forceinline __m128 _mm_round_ps( __m128 value, const int flags )
#endif /* !(defined(__SSE4_1__) || defined(__SSE4_2__)) */
#undef _mm_fabs_ps
#define _mm_fabs_ps(x) _mm_and_ps(x, _mm_castsi128_ps(_mm_set1_epi32(0x7fffffff)))
/* Return a __m128 with every element set to the largest element of v. */
ccl_device_inline __m128 _mm_hmax_ps(__m128 v)
{
/* v[0, 1, 2, 3] => [0, 1, 0, 1] and [2, 3, 2, 3] => v[max(0, 2), max(1, 3), max(0, 2), max(1, 3)] */
v = _mm_max_ps(_mm_movehl_ps(v, v), _mm_movelh_ps(v, v));
/* v[max(0, 2), max(1, 3), max(0, 2), max(1, 3)] => [4 times max(1, 3)] and [4 times max(0, 2)] => v[4 times max(0, 1, 2, 3)] */
v = _mm_max_ps(_mm_movehdup_ps(v), _mm_moveldup_ps(v));
return v;
}
/* Return the sum of the four elements of x. */
ccl_device_inline float _mm_hsum_ss(__m128 x)
{
__m128 a = _mm_movehdup_ps(x);
__m128 b = _mm_add_ps(x, a);
return _mm_cvtss_f32(_mm_add_ss(_mm_movehl_ps(a, b), b));
}
/* Return a __m128 with every element set to the sum of the four elements of x. */
ccl_device_inline __m128 _mm_hsum_ps(__m128 x)
{
x = _mm_hadd_ps(x, x);
x = _mm_hadd_ps(x, x);
return x;
}
/* Replace elements of x with zero where mask isn't set. */
#undef _mm_mask_ps
#define _mm_mask_ps(x, mask) _mm_blendv_ps(_mm_setzero_ps(), x, mask)
#else /* __KERNEL_SSE2__ */
/* This section is for utility functions which operates on non-register data