Index: media/base/simd/vector_math_sse.cc |
diff --git a/media/base/simd/vector_math_sse.cc b/media/base/simd/vector_math_sse.cc |
deleted file mode 100644 |
index c2121225cd6b715f56b1b6025e12897213a3f4bb..0000000000000000000000000000000000000000 |
--- a/media/base/simd/vector_math_sse.cc |
+++ /dev/null |
@@ -1,118 +0,0 @@ |
-// Copyright 2013 The Chromium Authors. All rights reserved. |
-// Use of this source code is governed by a BSD-style license that can be |
-// found in the LICENSE file. |
- |
-#include "media/base/vector_math_testing.h" |
- |
-#include <algorithm> |
- |
-#include <xmmintrin.h> // NOLINT |
- |
-namespace media { |
-namespace vector_math { |
- |
-void FMUL_SSE(const float src[], float scale, int len, float dest[]) { |
- const int rem = len % 4; |
- const int last_index = len - rem; |
- __m128 m_scale = _mm_set_ps1(scale); |
- for (int i = 0; i < last_index; i += 4) |
- _mm_store_ps(dest + i, _mm_mul_ps(_mm_load_ps(src + i), m_scale)); |
- |
- // Handle any remaining values that wouldn't fit in an SSE pass. |
- for (int i = last_index; i < len; ++i) |
- dest[i] = src[i] * scale; |
-} |
- |
-void FMAC_SSE(const float src[], float scale, int len, float dest[]) { |
- const int rem = len % 4; |
- const int last_index = len - rem; |
- __m128 m_scale = _mm_set_ps1(scale); |
- for (int i = 0; i < last_index; i += 4) { |
- _mm_store_ps(dest + i, _mm_add_ps(_mm_load_ps(dest + i), |
- _mm_mul_ps(_mm_load_ps(src + i), m_scale))); |
- } |
- |
- // Handle any remaining values that wouldn't fit in an SSE pass. |
- for (int i = last_index; i < len; ++i) |
- dest[i] += src[i] * scale; |
-} |
- |
-// Convenience macro to extract float 0 through 3 from the vector |a|. This is |
-// needed because compilers other than clang don't support access via |
-// operator[](). |
-#define EXTRACT_FLOAT(a, i) \ |
- (i == 0 ? \ |
- _mm_cvtss_f32(a) : \ |
- _mm_cvtss_f32(_mm_shuffle_ps(a, a, i))) |
- |
-std::pair<float, float> EWMAAndMaxPower_SSE( |
- float initial_value, const float src[], int len, float smoothing_factor) { |
- // When the recurrence is unrolled, we see that we can split it into 4 |
- // separate lanes of evaluation: |
- // |
- // y[n] = a(S[n]^2) + (1-a)(y[n-1]) |
- // = a(S[n]^2) + (1-a)^1(aS[n-1]^2) + (1-a)^2(aS[n-2]^2) + ... |
- // = z[n] + (1-a)^1(z[n-1]) + (1-a)^2(z[n-2]) + (1-a)^3(z[n-3]) |
- // |
- // where z[n] = a(S[n]^2) + (1-a)^4(z[n-4]) + (1-a)^8(z[n-8]) + ... |
- // |
- // Thus, the strategy here is to compute z[n], z[n-1], z[n-2], and z[n-3] in |
- // each of the 4 lanes, and then combine them to give y[n]. |
- |
- const int rem = len % 4; |
- const int last_index = len - rem; |
- |
- const __m128 smoothing_factor_x4 = _mm_set_ps1(smoothing_factor); |
- const float weight_prev = 1.0f - smoothing_factor; |
- const __m128 weight_prev_x4 = _mm_set_ps1(weight_prev); |
- const __m128 weight_prev_squared_x4 = |
- _mm_mul_ps(weight_prev_x4, weight_prev_x4); |
- const __m128 weight_prev_4th_x4 = |
- _mm_mul_ps(weight_prev_squared_x4, weight_prev_squared_x4); |
- |
- // Compute z[n], z[n-1], z[n-2], and z[n-3] in parallel in lanes 3, 2, 1 and |
- // 0, respectively. |
- __m128 max_x4 = _mm_setzero_ps(); |
- __m128 ewma_x4 = _mm_setr_ps(0.0f, 0.0f, 0.0f, initial_value); |
- int i; |
- for (i = 0; i < last_index; i += 4) { |
- ewma_x4 = _mm_mul_ps(ewma_x4, weight_prev_4th_x4); |
- const __m128 sample_x4 = _mm_load_ps(src + i); |
- const __m128 sample_squared_x4 = _mm_mul_ps(sample_x4, sample_x4); |
- max_x4 = _mm_max_ps(max_x4, sample_squared_x4); |
- // Note: The compiler optimizes this to a single multiply-and-accumulate |
- // instruction: |
- ewma_x4 = _mm_add_ps(ewma_x4, |
- _mm_mul_ps(sample_squared_x4, smoothing_factor_x4)); |
- } |
- |
- // y[n] = z[n] + (1-a)^1(z[n-1]) + (1-a)^2(z[n-2]) + (1-a)^3(z[n-3]) |
- float ewma = EXTRACT_FLOAT(ewma_x4, 3); |
- ewma_x4 = _mm_mul_ps(ewma_x4, weight_prev_x4); |
- ewma += EXTRACT_FLOAT(ewma_x4, 2); |
- ewma_x4 = _mm_mul_ps(ewma_x4, weight_prev_x4); |
- ewma += EXTRACT_FLOAT(ewma_x4, 1); |
- ewma_x4 = _mm_mul_ss(ewma_x4, weight_prev_x4); |
- ewma += EXTRACT_FLOAT(ewma_x4, 0); |
- |
- // Fold the maximums together to get the overall maximum. |
- max_x4 = _mm_max_ps(max_x4, |
- _mm_shuffle_ps(max_x4, max_x4, _MM_SHUFFLE(3, 3, 1, 1))); |
- max_x4 = _mm_max_ss(max_x4, _mm_shuffle_ps(max_x4, max_x4, 2)); |
- |
- std::pair<float, float> result(ewma, EXTRACT_FLOAT(max_x4, 0)); |
- |
- // Handle remaining values at the end of |src|. |
- for (; i < len; ++i) { |
- result.first *= weight_prev; |
- const float sample = src[i]; |
- const float sample_squared = sample * sample; |
- result.first += sample_squared * smoothing_factor; |
- result.second = std::max(result.second, sample_squared); |
- } |
- |
- return result; |
-} |
- |
-} // namespace vector_math |
-} // namespace media |