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| 1 // Copyright 2013 The Chromium Authors. All rights reserved. | |
| 2 // Use of this source code is governed by a BSD-style license that can be | |
| 3 // found in the LICENSE file. | |
| 4 | |
| 5 #include "media/base/vector_math_testing.h" | |
| 6 | |
| 7 #include <algorithm> | |
| 8 | |
| 9 #include <xmmintrin.h> // NOLINT | |
| 10 | |
| 11 namespace media { | |
| 12 namespace vector_math { | |
| 13 | |
| 14 void FMUL_SSE(const float src[], float scale, int len, float dest[]) { | |
| 15 const int rem = len % 4; | |
| 16 const int last_index = len - rem; | |
| 17 __m128 m_scale = _mm_set_ps1(scale); | |
| 18 for (int i = 0; i < last_index; i += 4) | |
| 19 _mm_store_ps(dest + i, _mm_mul_ps(_mm_load_ps(src + i), m_scale)); | |
| 20 | |
| 21 // Handle any remaining values that wouldn't fit in an SSE pass. | |
| 22 for (int i = last_index; i < len; ++i) | |
| 23 dest[i] = src[i] * scale; | |
| 24 } | |
| 25 | |
| 26 void FMAC_SSE(const float src[], float scale, int len, float dest[]) { | |
| 27 const int rem = len % 4; | |
| 28 const int last_index = len - rem; | |
| 29 __m128 m_scale = _mm_set_ps1(scale); | |
| 30 for (int i = 0; i < last_index; i += 4) { | |
| 31 _mm_store_ps(dest + i, _mm_add_ps(_mm_load_ps(dest + i), | |
| 32 _mm_mul_ps(_mm_load_ps(src + i), m_scale))); | |
| 33 } | |
| 34 | |
| 35 // Handle any remaining values that wouldn't fit in an SSE pass. | |
| 36 for (int i = last_index; i < len; ++i) | |
| 37 dest[i] += src[i] * scale; | |
| 38 } | |
| 39 | |
| 40 // Convenience macro to extract float 0 through 3 from the vector |a|. This is | |
| 41 // needed because compilers other than clang don't support access via | |
| 42 // operator[](). | |
| 43 #define EXTRACT_FLOAT(a, i) \ | |
| 44 (i == 0 ? \ | |
| 45 _mm_cvtss_f32(a) : \ | |
| 46 _mm_cvtss_f32(_mm_shuffle_ps(a, a, i))) | |
| 47 | |
| 48 std::pair<float, float> EWMAAndMaxPower_SSE( | |
| 49 float initial_value, const float src[], int len, float smoothing_factor) { | |
| 50 // When the recurrence is unrolled, we see that we can split it into 4 | |
| 51 // separate lanes of evaluation: | |
| 52 // | |
| 53 // y[n] = a(S[n]^2) + (1-a)(y[n-1]) | |
| 54 // = a(S[n]^2) + (1-a)^1(aS[n-1]^2) + (1-a)^2(aS[n-2]^2) + ... | |
| 55 // = z[n] + (1-a)^1(z[n-1]) + (1-a)^2(z[n-2]) + (1-a)^3(z[n-3]) | |
| 56 // | |
| 57 // where z[n] = a(S[n]^2) + (1-a)^4(z[n-4]) + (1-a)^8(z[n-8]) + ... | |
| 58 // | |
| 59 // Thus, the strategy here is to compute z[n], z[n-1], z[n-2], and z[n-3] in | |
| 60 // each of the 4 lanes, and then combine them to give y[n]. | |
| 61 | |
| 62 const int rem = len % 4; | |
| 63 const int last_index = len - rem; | |
| 64 | |
| 65 const __m128 smoothing_factor_x4 = _mm_set_ps1(smoothing_factor); | |
| 66 const float weight_prev = 1.0f - smoothing_factor; | |
| 67 const __m128 weight_prev_x4 = _mm_set_ps1(weight_prev); | |
| 68 const __m128 weight_prev_squared_x4 = | |
| 69 _mm_mul_ps(weight_prev_x4, weight_prev_x4); | |
| 70 const __m128 weight_prev_4th_x4 = | |
| 71 _mm_mul_ps(weight_prev_squared_x4, weight_prev_squared_x4); | |
| 72 | |
| 73 // Compute z[n], z[n-1], z[n-2], and z[n-3] in parallel in lanes 3, 2, 1 and | |
| 74 // 0, respectively. | |
| 75 __m128 max_x4 = _mm_setzero_ps(); | |
| 76 __m128 ewma_x4 = _mm_setr_ps(0.0f, 0.0f, 0.0f, initial_value); | |
| 77 int i; | |
| 78 for (i = 0; i < last_index; i += 4) { | |
| 79 ewma_x4 = _mm_mul_ps(ewma_x4, weight_prev_4th_x4); | |
| 80 const __m128 sample_x4 = _mm_load_ps(src + i); | |
| 81 const __m128 sample_squared_x4 = _mm_mul_ps(sample_x4, sample_x4); | |
| 82 max_x4 = _mm_max_ps(max_x4, sample_squared_x4); | |
| 83 // Note: The compiler optimizes this to a single multiply-and-accumulate | |
| 84 // instruction: | |
| 85 ewma_x4 = _mm_add_ps(ewma_x4, | |
| 86 _mm_mul_ps(sample_squared_x4, smoothing_factor_x4)); | |
| 87 } | |
| 88 | |
| 89 // y[n] = z[n] + (1-a)^1(z[n-1]) + (1-a)^2(z[n-2]) + (1-a)^3(z[n-3]) | |
| 90 float ewma = EXTRACT_FLOAT(ewma_x4, 3); | |
| 91 ewma_x4 = _mm_mul_ps(ewma_x4, weight_prev_x4); | |
| 92 ewma += EXTRACT_FLOAT(ewma_x4, 2); | |
| 93 ewma_x4 = _mm_mul_ps(ewma_x4, weight_prev_x4); | |
| 94 ewma += EXTRACT_FLOAT(ewma_x4, 1); | |
| 95 ewma_x4 = _mm_mul_ss(ewma_x4, weight_prev_x4); | |
| 96 ewma += EXTRACT_FLOAT(ewma_x4, 0); | |
| 97 | |
| 98 // Fold the maximums together to get the overall maximum. | |
| 99 max_x4 = _mm_max_ps(max_x4, | |
| 100 _mm_shuffle_ps(max_x4, max_x4, _MM_SHUFFLE(3, 3, 1, 1))); | |
| 101 max_x4 = _mm_max_ss(max_x4, _mm_shuffle_ps(max_x4, max_x4, 2)); | |
| 102 | |
| 103 std::pair<float, float> result(ewma, EXTRACT_FLOAT(max_x4, 0)); | |
| 104 | |
| 105 // Handle remaining values at the end of |src|. | |
| 106 for (; i < len; ++i) { | |
| 107 result.first *= weight_prev; | |
| 108 const float sample = src[i]; | |
| 109 const float sample_squared = sample * sample; | |
| 110 result.first += sample_squared * smoothing_factor; | |
| 111 result.second = std::max(result.second, sample_squared); | |
| 112 } | |
| 113 | |
| 114 return result; | |
| 115 } | |
| 116 | |
| 117 } // namespace vector_math | |
| 118 } // namespace media | |
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