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Commit 62f909dc authored by dalecurtis@chromium.org's avatar dalecurtis@chromium.org
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Remove runtime CPU detection for SSE optimized media/ methods. 

SSE2 is now the baseline for X86 platforms.

BUG=378608
TEST=compiles

Review URL: https://codereview.chromium.org/308003004

git-svn-id: svn://svn.chromium.org/chrome/trunk/src@273964 0039d316-1c4b-4281-b951-d872f2087c98
parent 0776bb9e
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Showing with 162 additions and 337 deletions
media/base/media.cc
View file @ 62f909dc
...@@ -9,8 +9,6 @@ ...@@ -9,8 +9,6 @@
#include "base/path_service.h" #include "base/path_service.h"
#include "base/synchronization/lock.h" #include "base/synchronization/lock.h"
#include "build/build_config.h" #include "build/build_config.h"
#include "media/base/sinc_resampler.h"
#include "media/base/vector_math.h"
#include "media/base/yuv_convert.h" #include "media/base/yuv_convert.h"
namespace media { namespace media {
...@@ -44,9 +42,6 @@ class MediaInitializer { ...@@ -44,9 +42,6 @@ class MediaInitializer {
: initialized_(false), : initialized_(false),
tried_initialize_(false) { tried_initialize_(false) {
// Perform initialization of libraries which require runtime CPU detection. // Perform initialization of libraries which require runtime CPU detection.
// TODO(dalecurtis): Add initialization of YUV, SincResampler.
vector_math::Initialize();
SincResampler::InitializeCPUSpecificFeatures();
InitializeCPUSpecificYUVConversions(); InitializeCPUSpecificYUVConversions();
} }
......
media/base/simd/sinc_resampler_sse.cc deleted 100644 → 0
View file @ 0776bb9e
// 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/sinc_resampler.h"
#include <xmmintrin.h>
namespace media {
float SincResampler::Convolve_SSE(const float* input_ptr, const float* k1,
const float* k2,
double kernel_interpolation_factor) {
__m128 m_input;
__m128 m_sums1 = _mm_setzero_ps();
__m128 m_sums2 = _mm_setzero_ps();
// Based on |input_ptr| alignment, we need to use loadu or load. Unrolling
// these loops hurt performance in local testing.
if (reinterpret_cast<uintptr_t>(input_ptr) & 0x0F) {
for (int i = 0; i < kKernelSize; i += 4) {
m_input = _mm_loadu_ps(input_ptr + i);
m_sums1 = _mm_add_ps(m_sums1, _mm_mul_ps(m_input, _mm_load_ps(k1 + i)));
m_sums2 = _mm_add_ps(m_sums2, _mm_mul_ps(m_input, _mm_load_ps(k2 + i)));
}
} else {
for (int i = 0; i < kKernelSize; i += 4) {
m_input = _mm_load_ps(input_ptr + i);
m_sums1 = _mm_add_ps(m_sums1, _mm_mul_ps(m_input, _mm_load_ps(k1 + i)));
m_sums2 = _mm_add_ps(m_sums2, _mm_mul_ps(m_input, _mm_load_ps(k2 + i)));
}
}
// Linearly interpolate the two "convolutions".
m_sums1 = _mm_mul_ps(m_sums1, _mm_set_ps1(1.0 - kernel_interpolation_factor));
m_sums2 = _mm_mul_ps(m_sums2, _mm_set_ps1(kernel_interpolation_factor));
m_sums1 = _mm_add_ps(m_sums1, m_sums2);
// Sum components together.
float result;
m_sums2 = _mm_add_ps(_mm_movehl_ps(m_sums1, m_sums1), m_sums1);
_mm_store_ss(&result, _mm_add_ss(m_sums2, _mm_shuffle_ps(
m_sums2, m_sums2, 1)));
return result;
}
} // namespace media
media/base/simd/vector_math_sse.cc deleted 100644 → 0
View file @ 0776bb9e
// 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
media/base/sinc_resampler.cc
View file @ 62f909dc
...@@ -81,11 +81,16 @@ ...@@ -81,11 +81,16 @@
#include <cmath> #include <cmath>
#include <limits> #include <limits>
#include "base/cpu.h"
#include "base/logging.h" #include "base/logging.h"
#if defined(ARCH_CPU_ARM_FAMILY) && defined(USE_NEON) #if defined(ARCH_CPU_X86_FAMILY)
#include <xmmintrin.h>
#define CONVOLVE_FUNC Convolve_SSE
#elif defined(ARCH_CPU_ARM_FAMILY) && defined(USE_NEON)
#include <arm_neon.h> #include <arm_neon.h>
#define CONVOLVE_FUNC Convolve_NEON
#else
#define CONVOLVE_FUNC Convolve_C
#endif #endif
namespace media { namespace media {
...@@ -106,36 +111,6 @@ static double SincScaleFactor(double io_ratio) { ...@@ -106,36 +111,6 @@ static double SincScaleFactor(double io_ratio) {
return sinc_scale_factor; return sinc_scale_factor;
} }
// If we know the minimum architecture at compile time, avoid CPU detection.
// Force NaCl code to use C routines since (at present) nothing there uses these
// methods and plumbing the -msse built library is non-trivial.
#if defined(ARCH_CPU_X86_FAMILY) && !defined(OS_NACL)
#if defined(__SSE__)
#define CONVOLVE_FUNC Convolve_SSE
void SincResampler::InitializeCPUSpecificFeatures() {}
#else
// X86 CPU detection required. Functions will be set by
// InitializeCPUSpecificFeatures().
// TODO(dalecurtis): Once Chrome moves to an SSE baseline this can be removed.
#define CONVOLVE_FUNC g_convolve_proc_
typedef float (*ConvolveProc)(const float*, const float*, const float*, double);
static ConvolveProc g_convolve_proc_ = NULL;
void SincResampler::InitializeCPUSpecificFeatures() {
CHECK(!g_convolve_proc_);
g_convolve_proc_ = base::CPU().has_sse() ? Convolve_SSE : Convolve_C;
}
#endif
#elif defined(ARCH_CPU_ARM_FAMILY) && defined(USE_NEON)
#define CONVOLVE_FUNC Convolve_NEON
void SincResampler::InitializeCPUSpecificFeatures() {}
#else
// Unknown architecture.
#define CONVOLVE_FUNC Convolve_C
void SincResampler::InitializeCPUSpecificFeatures() {}
#endif
SincResampler::SincResampler(double io_sample_rate_ratio, SincResampler::SincResampler(double io_sample_rate_ratio,
int request_frames, int request_frames,
const ReadCB& read_cb) const ReadCB& read_cb)
...@@ -321,8 +296,6 @@ void SincResampler::Resample(int frames, float* destination) { ...@@ -321,8 +296,6 @@ void SincResampler::Resample(int frames, float* destination) {
} }
} }
#undef CONVOLVE_FUNC
int SincResampler::ChunkSize() const { int SincResampler::ChunkSize() const {
return block_size_ / io_sample_rate_ratio_; return block_size_ / io_sample_rate_ratio_;
} }
...@@ -354,7 +327,44 @@ float SincResampler::Convolve_C(const float* input_ptr, const float* k1, ...@@ -354,7 +327,44 @@ float SincResampler::Convolve_C(const float* input_ptr, const float* k1,
+ kernel_interpolation_factor * sum2; + kernel_interpolation_factor * sum2;
} }
#if defined(ARCH_CPU_ARM_FAMILY) && defined(USE_NEON) #if defined(ARCH_CPU_X86_FAMILY)
float SincResampler::Convolve_SSE(const float* input_ptr, const float* k1,
const float* k2,
double kernel_interpolation_factor) {
__m128 m_input;
__m128 m_sums1 = _mm_setzero_ps();
__m128 m_sums2 = _mm_setzero_ps();
// Based on |input_ptr| alignment, we need to use loadu or load. Unrolling
// these loops hurt performance in local testing.
if (reinterpret_cast<uintptr_t>(input_ptr) & 0x0F) {
for (int i = 0; i < kKernelSize; i += 4) {
m_input = _mm_loadu_ps(input_ptr + i);
m_sums1 = _mm_add_ps(m_sums1, _mm_mul_ps(m_input, _mm_load_ps(k1 + i)));
m_sums2 = _mm_add_ps(m_sums2, _mm_mul_ps(m_input, _mm_load_ps(k2 + i)));
}
} else {
for (int i = 0; i < kKernelSize; i += 4) {
m_input = _mm_load_ps(input_ptr + i);
m_sums1 = _mm_add_ps(m_sums1, _mm_mul_ps(m_input, _mm_load_ps(k1 + i)));
m_sums2 = _mm_add_ps(m_sums2, _mm_mul_ps(m_input, _mm_load_ps(k2 + i)));
}
}
// Linearly interpolate the two "convolutions".
m_sums1 = _mm_mul_ps(m_sums1, _mm_set_ps1(1.0 - kernel_interpolation_factor));
m_sums2 = _mm_mul_ps(m_sums2, _mm_set_ps1(kernel_interpolation_factor));
m_sums1 = _mm_add_ps(m_sums1, m_sums2);
// Sum components together.
float result;
m_sums2 = _mm_add_ps(_mm_movehl_ps(m_sums1, m_sums1), m_sums1);
_mm_store_ss(&result, _mm_add_ss(m_sums2, _mm_shuffle_ps(
m_sums2, m_sums2, 1)));
return result;
}
#elif defined(ARCH_CPU_ARM_FAMILY) && defined(USE_NEON)
float SincResampler::Convolve_NEON(const float* input_ptr, const float* k1, float SincResampler::Convolve_NEON(const float* input_ptr, const float* k1,
const float* k2, const float* k2,
double kernel_interpolation_factor) { double kernel_interpolation_factor) {
......
media/base/sinc_resampler.h
View file @ 62f909dc
...@@ -34,10 +34,6 @@ class MEDIA_EXPORT SincResampler { ...@@ -34,10 +34,6 @@ class MEDIA_EXPORT SincResampler {
kKernelStorageSize = kKernelSize * (kKernelOffsetCount + 1), kKernelStorageSize = kKernelSize * (kKernelOffsetCount + 1),
}; };
// Selects runtime specific CPU features like SSE. Must be called before
// using SincResampler.
static void InitializeCPUSpecificFeatures();
// Callback type for providing more data into the resampler. Expects |frames| // Callback type for providing more data into the resampler. Expects |frames|
// of data to be rendered into |destination|; zero padded if not enough frames // of data to be rendered into |destination|; zero padded if not enough frames
// are available to satisfy the request. // are available to satisfy the request.
......
media/base/sinc_resampler_perftest.cc
View file @ 62f909dc
...@@ -4,7 +4,6 @@ ...@@ -4,7 +4,6 @@
#include "base/bind.h" #include "base/bind.h"
#include "base/bind_helpers.h" #include "base/bind_helpers.h"
#include "base/cpu.h"
#include "base/time/time.h" #include "base/time/time.h"
#include "media/base/sinc_resampler.h" #include "media/base/sinc_resampler.h"
#include "testing/gmock/include/gmock/gmock.h" #include "testing/gmock/include/gmock/gmock.h"
...@@ -61,9 +60,6 @@ TEST(SincResamplerPerfTest, Convolve) { ...@@ -61,9 +60,6 @@ TEST(SincResamplerPerfTest, Convolve) {
&resampler, SincResampler::Convolve_C, true, "unoptimized_aligned"); &resampler, SincResampler::Convolve_C, true, "unoptimized_aligned");
#if defined(CONVOLVE_FUNC) #if defined(CONVOLVE_FUNC)
#if defined(ARCH_CPU_X86_FAMILY)
ASSERT_TRUE(base::CPU().has_sse());
#endif
RunConvolveBenchmark( RunConvolveBenchmark(
&resampler, SincResampler::CONVOLVE_FUNC, true, "optimized_aligned"); &resampler, SincResampler::CONVOLVE_FUNC, true, "optimized_aligned");
RunConvolveBenchmark( RunConvolveBenchmark(
......
media/base/sinc_resampler_unittest.cc
View file @ 62f909dc
...@@ -9,7 +9,6 @@ ...@@ -9,7 +9,6 @@
#include "base/bind.h" #include "base/bind.h"
#include "base/bind_helpers.h" #include "base/bind_helpers.h"
#include "base/cpu.h"
#include "base/strings/string_number_conversions.h" #include "base/strings/string_number_conversions.h"
#include "base/time/time.h" #include "base/time/time.h"
#include "build/build_config.h" #include "build/build_config.h"
...@@ -121,10 +120,6 @@ TEST(SincResamplerTest, DISABLED_SetRatioBench) { ...@@ -121,10 +120,6 @@ TEST(SincResamplerTest, DISABLED_SetRatioBench) {
static const double kKernelInterpolationFactor = 0.5; static const double kKernelInterpolationFactor = 0.5;
TEST(SincResamplerTest, Convolve) { TEST(SincResamplerTest, Convolve) {
#if defined(ARCH_CPU_X86_FAMILY)
ASSERT_TRUE(base::CPU().has_sse());
#endif
// Initialize a dummy resampler. // Initialize a dummy resampler.
MockSource mock_source; MockSource mock_source;
SincResampler resampler( SincResampler resampler(
......
media/base/vector_math.cc
View file @ 62f909dc
...@@ -7,63 +7,29 @@ ...@@ -7,63 +7,29 @@
#include <algorithm> #include <algorithm>
#include "base/cpu.h"
#include "base/logging.h" #include "base/logging.h"
#include "build/build_config.h" #include "build/build_config.h"
#if defined(ARCH_CPU_ARM_FAMILY) && defined(USE_NEON) // NaCl does not allow intrinsics.
#include <arm_neon.h>
#endif
namespace media {
namespace vector_math {
// If we know the minimum architecture at compile time, avoid CPU detection.
// Force NaCl code to use C routines since (at present) nothing there uses these
// methods and plumbing the -msse built library is non-trivial.
#if defined(ARCH_CPU_X86_FAMILY) && !defined(OS_NACL) #if defined(ARCH_CPU_X86_FAMILY) && !defined(OS_NACL)
#if defined(__SSE__) #include <xmmintrin.h>
#define FMAC_FUNC FMAC_SSE #define FMAC_FUNC FMAC_SSE
#define FMUL_FUNC FMUL_SSE #define FMUL_FUNC FMUL_SSE
#define EWMAAndMaxPower_FUNC EWMAAndMaxPower_SSE #define EWMAAndMaxPower_FUNC EWMAAndMaxPower_SSE
void Initialize() {}
#else
// X86 CPU detection required. Functions will be set by Initialize().
// TODO(dalecurtis): Once Chrome moves to an SSE baseline this can be removed.
#define FMAC_FUNC g_fmac_proc_
#define FMUL_FUNC g_fmul_proc_
#define EWMAAndMaxPower_FUNC g_ewma_power_proc_
typedef void (*MathProc)(const float src[], float scale, int len, float dest[]);
static MathProc g_fmac_proc_ = NULL;
static MathProc g_fmul_proc_ = NULL;
typedef std::pair<float, float> (*EWMAAndMaxPowerProc)(
float initial_value, const float src[], int len, float smoothing_factor);
static EWMAAndMaxPowerProc g_ewma_power_proc_ = NULL;
void Initialize() {
CHECK(!g_fmac_proc_);
CHECK(!g_fmul_proc_);
CHECK(!g_ewma_power_proc_);
const bool kUseSSE = base::CPU().has_sse();
g_fmac_proc_ = kUseSSE ? FMAC_SSE : FMAC_C;
g_fmul_proc_ = kUseSSE ? FMUL_SSE : FMUL_C;
g_ewma_power_proc_ = kUseSSE ? EWMAAndMaxPower_SSE : EWMAAndMaxPower_C;
}
#endif
#elif defined(ARCH_CPU_ARM_FAMILY) && defined(USE_NEON) #elif defined(ARCH_CPU_ARM_FAMILY) && defined(USE_NEON)
#include <arm_neon.h>
#define FMAC_FUNC FMAC_NEON #define FMAC_FUNC FMAC_NEON
#define FMUL_FUNC FMUL_NEON #define FMUL_FUNC FMUL_NEON
#define EWMAAndMaxPower_FUNC EWMAAndMaxPower_NEON #define EWMAAndMaxPower_FUNC EWMAAndMaxPower_NEON
void Initialize() {}
#else #else
// Unknown architecture.
#define FMAC_FUNC FMAC_C #define FMAC_FUNC FMAC_C
#define FMUL_FUNC FMUL_C #define FMUL_FUNC FMUL_C
#define EWMAAndMaxPower_FUNC EWMAAndMaxPower_C #define EWMAAndMaxPower_FUNC EWMAAndMaxPower_C
void Initialize() {}
#endif #endif
namespace media {
namespace vector_math {
void FMAC(const float src[], float scale, int len, float dest[]) { void FMAC(const float src[], float scale, int len, float dest[]) {
// Ensure |src| and |dest| are 16-byte aligned. // Ensure |src| and |dest| are 16-byte aligned.
DCHECK_EQ(0u, reinterpret_cast<uintptr_t>(src) & (kRequiredAlignment - 1)); DCHECK_EQ(0u, reinterpret_cast<uintptr_t>(src) & (kRequiredAlignment - 1));
...@@ -116,6 +82,111 @@ std::pair<float, float> EWMAAndMaxPower_C( ...@@ -116,6 +82,111 @@ std::pair<float, float> EWMAAndMaxPower_C(
return result; return result;
} }
#if defined(ARCH_CPU_X86_FAMILY) && !defined(OS_NACL)
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;
}
#endif
#if defined(ARCH_CPU_ARM_FAMILY) && defined(USE_NEON) #if defined(ARCH_CPU_ARM_FAMILY) && defined(USE_NEON)
void FMAC_NEON(const float src[], float scale, int len, float dest[]) { void FMAC_NEON(const float src[], float scale, int len, float dest[]) {
const int rem = len % 4; const int rem = len % 4;
......
media/base/vector_math.h
View file @ 62f909dc
...@@ -15,11 +15,6 @@ namespace vector_math { ...@@ -15,11 +15,6 @@ namespace vector_math {
// Required alignment for inputs and outputs to all vector math functions // Required alignment for inputs and outputs to all vector math functions
enum { kRequiredAlignment = 16 }; enum { kRequiredAlignment = 16 };
// Selects runtime specific optimizations such as SSE. Must be called prior to
// calling FMAC() or FMUL(). Called during media library initialization; most
// users should never have to call this.
MEDIA_EXPORT void Initialize();
// Multiply each element of |src| (up to |len|) by |scale| and add to |dest|. // Multiply each element of |src| (up to |len|) by |scale| and add to |dest|.
// |src| and |dest| must be aligned by kRequiredAlignment. // |src| and |dest| must be aligned by kRequiredAlignment.
MEDIA_EXPORT void FMAC(const float src[], float scale, int len, float dest[]); MEDIA_EXPORT void FMAC(const float src[], float scale, int len, float dest[]);
......
media/base/vector_math_perftest.cc
View file @ 62f909dc
...@@ -2,7 +2,6 @@ ...@@ -2,7 +2,6 @@
// Use of this source code is governed by a BSD-style license that can be // Use of this source code is governed by a BSD-style license that can be
// found in the LICENSE file. // found in the LICENSE file.
#include "base/cpu.h"
#include "base/memory/aligned_memory.h" #include "base/memory/aligned_memory.h"
#include "base/memory/scoped_ptr.h" #include "base/memory/scoped_ptr.h"
#include "base/time/time.h" #include "base/time/time.h"
...@@ -80,11 +79,15 @@ class VectorMathPerfTest : public testing::Test { ...@@ -80,11 +79,15 @@ class VectorMathPerfTest : public testing::Test {
DISALLOW_COPY_AND_ASSIGN(VectorMathPerfTest); DISALLOW_COPY_AND_ASSIGN(VectorMathPerfTest);
}; };
// Define platform independent function name for FMAC* perf tests. // Define platform dependent function names for SIMD optimized methods.
#if defined(ARCH_CPU_X86_FAMILY) #if defined(ARCH_CPU_X86_FAMILY)
#define FMAC_FUNC FMAC_SSE #define FMAC_FUNC FMAC_SSE
#define FMUL_FUNC FMUL_SSE
#define EWMAAndMaxPower_FUNC EWMAAndMaxPower_SSE
#elif defined(ARCH_CPU_ARM_FAMILY) && defined(USE_NEON) #elif defined(ARCH_CPU_ARM_FAMILY) && defined(USE_NEON)
#define FMAC_FUNC FMAC_NEON #define FMAC_FUNC FMAC_NEON
#define FMUL_FUNC FMUL_NEON
#define EWMAAndMaxPower_FUNC EWMAAndMaxPower_NEON
#endif #endif
// Benchmark for each optimized vector_math::FMAC() method. // Benchmark for each optimized vector_math::FMAC() method.
...@@ -93,9 +96,6 @@ TEST_F(VectorMathPerfTest, FMAC) { ...@@ -93,9 +96,6 @@ TEST_F(VectorMathPerfTest, FMAC) {
RunBenchmark( RunBenchmark(
vector_math::FMAC_C, true, "vector_math_fmac", "unoptimized"); vector_math::FMAC_C, true, "vector_math_fmac", "unoptimized");
#if defined(FMAC_FUNC) #if defined(FMAC_FUNC)
#if defined(ARCH_CPU_X86_FAMILY)
ASSERT_TRUE(base::CPU().has_sse());
#endif
// Benchmark FMAC_FUNC() with unaligned size. // Benchmark FMAC_FUNC() with unaligned size.
ASSERT_NE((kVectorSize - 1) % (vector_math::kRequiredAlignment / ASSERT_NE((kVectorSize - 1) % (vector_math::kRequiredAlignment /
sizeof(float)), 0U); sizeof(float)), 0U);
...@@ -109,24 +109,12 @@ TEST_F(VectorMathPerfTest, FMAC) { ...@@ -109,24 +109,12 @@ TEST_F(VectorMathPerfTest, FMAC) {
#endif #endif
} }
#undef FMAC_FUNC
// Define platform independent function name for FMULBenchmark* tests.
#if defined(ARCH_CPU_X86_FAMILY)
#define FMUL_FUNC FMUL_SSE
#elif defined(ARCH_CPU_ARM_FAMILY) && defined(USE_NEON)
#define FMUL_FUNC FMUL_NEON
#endif
// Benchmark for each optimized vector_math::FMUL() method. // Benchmark for each optimized vector_math::FMUL() method.
TEST_F(VectorMathPerfTest, FMUL) { TEST_F(VectorMathPerfTest, FMUL) {
// Benchmark FMUL_C(). // Benchmark FMUL_C().
RunBenchmark( RunBenchmark(
vector_math::FMUL_C, true, "vector_math_fmul", "unoptimized"); vector_math::FMUL_C, true, "vector_math_fmul", "unoptimized");
#if defined(FMUL_FUNC) #if defined(FMUL_FUNC)
#if defined(ARCH_CPU_X86_FAMILY)
ASSERT_TRUE(base::CPU().has_sse());
#endif
// Benchmark FMUL_FUNC() with unaligned size. // Benchmark FMUL_FUNC() with unaligned size.
ASSERT_NE((kVectorSize - 1) % (vector_math::kRequiredAlignment / ASSERT_NE((kVectorSize - 1) % (vector_math::kRequiredAlignment /
sizeof(float)), 0U); sizeof(float)), 0U);
...@@ -140,14 +128,6 @@ TEST_F(VectorMathPerfTest, FMUL) { ...@@ -140,14 +128,6 @@ TEST_F(VectorMathPerfTest, FMUL) {
#endif #endif
} }
#undef FMUL_FUNC
#if defined(ARCH_CPU_X86_FAMILY)
#define EWMAAndMaxPower_FUNC EWMAAndMaxPower_SSE
#elif defined(ARCH_CPU_ARM_FAMILY) && defined(USE_NEON)
#define EWMAAndMaxPower_FUNC EWMAAndMaxPower_NEON
#endif
// Benchmark for each optimized vector_math::EWMAAndMaxPower() method. // Benchmark for each optimized vector_math::EWMAAndMaxPower() method.
TEST_F(VectorMathPerfTest, EWMAAndMaxPower) { TEST_F(VectorMathPerfTest, EWMAAndMaxPower) {
// Benchmark EWMAAndMaxPower_C(). // Benchmark EWMAAndMaxPower_C().
...@@ -156,9 +136,6 @@ TEST_F(VectorMathPerfTest, EWMAAndMaxPower) { ...@@ -156,9 +136,6 @@ TEST_F(VectorMathPerfTest, EWMAAndMaxPower) {
"vector_math_ewma_and_max_power", "vector_math_ewma_and_max_power",
"unoptimized"); "unoptimized");
#if defined(EWMAAndMaxPower_FUNC) #if defined(EWMAAndMaxPower_FUNC)
#if defined(ARCH_CPU_X86_FAMILY)
ASSERT_TRUE(base::CPU().has_sse());
#endif
// Benchmark EWMAAndMaxPower_FUNC() with unaligned size. // Benchmark EWMAAndMaxPower_FUNC() with unaligned size.
ASSERT_NE((kVectorSize - 1) % (vector_math::kRequiredAlignment / ASSERT_NE((kVectorSize - 1) % (vector_math::kRequiredAlignment /
sizeof(float)), 0U); sizeof(float)), 0U);
...@@ -176,6 +153,4 @@ TEST_F(VectorMathPerfTest, EWMAAndMaxPower) { ...@@ -176,6 +153,4 @@ TEST_F(VectorMathPerfTest, EWMAAndMaxPower) {
#endif #endif
} }
#undef EWMAAndMaxPower_FUNC
} // namespace media } // namespace media
media/base/vector_math_testing.h
View file @ 62f909dc
...@@ -19,7 +19,7 @@ MEDIA_EXPORT void FMUL_C(const float src[], float scale, int len, float dest[]); ...@@ -19,7 +19,7 @@ MEDIA_EXPORT void FMUL_C(const float src[], float scale, int len, float dest[]);
MEDIA_EXPORT std::pair<float, float> EWMAAndMaxPower_C( MEDIA_EXPORT std::pair<float, float> EWMAAndMaxPower_C(
float initial_value, const float src[], int len, float smoothing_factor); float initial_value, const float src[], int len, float smoothing_factor);
#if defined(ARCH_CPU_X86_FAMILY) #if defined(ARCH_CPU_X86_FAMILY) && !defined(OS_NACL)
MEDIA_EXPORT void FMAC_SSE(const float src[], float scale, int len, MEDIA_EXPORT void FMAC_SSE(const float src[], float scale, int len,
float dest[]); float dest[]);
MEDIA_EXPORT void FMUL_SSE(const float src[], float scale, int len, MEDIA_EXPORT void FMUL_SSE(const float src[], float scale, int len,
......
media/base/vector_math_unittest.cc
View file @ 62f909dc
...@@ -6,7 +6,6 @@ ...@@ -6,7 +6,6 @@
#define _USE_MATH_DEFINES #define _USE_MATH_DEFINES
#include <cmath> #include <cmath>
#include "base/cpu.h"
#include "base/memory/aligned_memory.h" #include "base/memory/aligned_memory.h"
#include "base/memory/scoped_ptr.h" #include "base/memory/scoped_ptr.h"
#include "base/strings/string_number_conversions.h" #include "base/strings/string_number_conversions.h"
...@@ -76,7 +75,6 @@ TEST_F(VectorMathTest, FMAC) { ...@@ -76,7 +75,6 @@ TEST_F(VectorMathTest, FMAC) {
#if defined(ARCH_CPU_X86_FAMILY) #if defined(ARCH_CPU_X86_FAMILY)
{ {
ASSERT_TRUE(base::CPU().has_sse());
SCOPED_TRACE("FMAC_SSE"); SCOPED_TRACE("FMAC_SSE");
FillTestVectors(kInputFillValue, kOutputFillValue); FillTestVectors(kInputFillValue, kOutputFillValue);
vector_math::FMAC_SSE( vector_math::FMAC_SSE(
...@@ -118,7 +116,6 @@ TEST_F(VectorMathTest, FMUL) { ...@@ -118,7 +116,6 @@ TEST_F(VectorMathTest, FMUL) {
#if defined(ARCH_CPU_X86_FAMILY) #if defined(ARCH_CPU_X86_FAMILY)
{ {
ASSERT_TRUE(base::CPU().has_sse());
SCOPED_TRACE("FMUL_SSE"); SCOPED_TRACE("FMUL_SSE");
FillTestVectors(kInputFillValue, kOutputFillValue); FillTestVectors(kInputFillValue, kOutputFillValue);
vector_math::FMUL_SSE( vector_math::FMUL_SSE(
...@@ -227,7 +224,6 @@ class EWMATestScenario { ...@@ -227,7 +224,6 @@ class EWMATestScenario {
#if defined(ARCH_CPU_X86_FAMILY) #if defined(ARCH_CPU_X86_FAMILY)
{ {
ASSERT_TRUE(base::CPU().has_sse());
SCOPED_TRACE("EWMAAndMaxPower_SSE"); SCOPED_TRACE("EWMAAndMaxPower_SSE");
const std::pair<float, float>& result = vector_math::EWMAAndMaxPower_SSE( const std::pair<float, float>& result = vector_math::EWMAAndMaxPower_SSE(
initial_value_, data_.get(), data_len_, smoothing_factor_); initial_value_, data_.get(), data_len_, smoothing_factor_);
......
media/media.gyp
View file @ 62f909dc
...@@ -922,7 +922,6 @@ ...@@ -922,7 +922,6 @@
'dependencies': [ 'dependencies': [
'media_asm', 'media_asm',
'media_mmx', 'media_mmx',
'media_sse',
'media_sse2', 'media_sse2',
], ],
'sources': [ 'sources': [
...@@ -1338,11 +1337,6 @@ ...@@ -1338,11 +1337,6 @@
'USE_NEON' 'USE_NEON'
], ],
}], }],
['target_arch=="ia32" or target_arch=="x64"', {
'dependencies': [
'shared_memory_support_sse'
],
}],
], ],
}, },
], ],
...@@ -1451,22 +1445,6 @@ ...@@ -1451,22 +1445,6 @@
'base/simd/filter_yuv_mmx.cc', 'base/simd/filter_yuv_mmx.cc',
], ],
}, },
{
'target_name': 'media_sse',
'type': 'static_library',
'cflags': [
'-msse',
],
'defines': [
'MEDIA_IMPLEMENTATION',
],
'include_dirs': [
'..',
],
'sources': [
'base/simd/sinc_resampler_sse.cc',
],
},
{ {
'target_name': 'media_sse2', 'target_name': 'media_sse2',
'type': 'static_library', 'type': 'static_library',
...@@ -1485,22 +1463,6 @@ ...@@ -1485,22 +1463,6 @@
'base/simd/filter_yuv_sse2.cc', 'base/simd/filter_yuv_sse2.cc',
], ],
}, },
{
'target_name': 'shared_memory_support_sse',
'type': 'static_library',
'cflags': [
'-msse',
],
'defines': [
'MEDIA_IMPLEMENTATION',
],
'include_dirs': [
'..',
],
'sources': [
'base/simd/vector_math_sse.cc',
],
},
], # targets ], # targets
}], }],
['use_x11==1', { ['use_x11==1', {
......
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