media/base/sinc_resampler.cc - chromium/src - Git at Google

 // Copyright (c) 2012 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.
 //
 // Initial input buffer layout, dividing into regions r0_ to r4_ (note: r0_, r3_
 // and r4_ will move after the first load):
 //
 // |----------------|-----------------------------------------|----------------|
 //
 //                                        request_frames_
 //                   <--------------------------------------------------------->
 //                                    r0_ (during first load)
 //
 //  kKernelSize / 2   kKernelSize / 2         kKernelSize / 2   kKernelSize / 2
 // <---------------> <--------------->       <---------------> <--------------->
 //        r1_               r2_                     r3_               r4_
 //
 //                             block_size_ == r4_ - r2_
 //                   <--------------------------------------->
 //
 //                                                  request_frames_
 //                                    <------------------ ... ----------------->
 //                                               r0_ (during second load)
 //
 // On the second request r0_ slides to the right by kKernelSize / 2 and r3_, r4_
 // and block_size_ are reinitialized via step (3) in the algorithm below.
 //
 // These new regions remain constant until a Flush() occurs.  While complicated,
 // this allows us to reduce jitter by always requesting the same amount from the
 // provided callback.
 //
 // The algorithm:
 //
 // 1) Allocate input_buffer of size: request_frames_ + kKernelSize; this ensures
 //    there's enough room to read request_frames_ from the callback into region
 //    r0_ (which will move between the first and subsequent passes).
 //
 // 2) Let r1_, r2_ each represent half the kernel centered around r0_:
 //
 //        r0_ = input_buffer_ + kKernelSize / 2
 //        r1_ = input_buffer_
 //        r2_ = r0_
 //
 //    r0_ is always request_frames_ in size.  r1_, r2_ are kKernelSize / 2 in
 //    size.  r1_ must be zero initialized to avoid convolution with garbage (see
 //    step (5) for why).
 //
 // 3) Let r3_, r4_ each represent half the kernel right aligned with the end of
 //    r0_ and choose block_size_ as the distance in frames between r4_ and r2_:
 //
 //        r3_ = r0_ + request_frames_ - kKernelSize
 //        r4_ = r0_ + request_frames_ - kKernelSize / 2
 //        block_size_ = r4_ - r2_ = request_frames_ - kKernelSize / 2
 //
 // 4) Consume request_frames_ frames into r0_.
 //
 // 5) Position kernel centered at start of r2_ and generate output frames until
 //    the kernel is centered at the start of r4_ or we've finished generating
 //    all the output frames.
 //
 // 6) Wrap left over data from the r3_ to r1_ and r4_ to r2_.
 //
 // 7) If we're on the second load, in order to avoid overwriting the frames we
 //    just wrapped from r4_ we need to slide r0_ to the right by the size of
 //    r4_, which is kKernelSize / 2:
 //
 //        r0_ = r0_ + kKernelSize / 2 = input_buffer_ + kKernelSize
 //
 //    r3_, r4_, and block_size_ then need to be reinitialized, so goto (3).
 //
 // 8) Else, if we're not on the second load, goto (4).
 //
 // Note: we're glossing over how the sub-sample handling works with
 // |virtual_source_idx_|, etc.

 #include "media/base/sinc_resampler.h"

 #include <limits>

 #include "base/logging.h"
 #include "base/numerics/math_constants.h"
 #include "build/build_config.h"
 #include "cc/base/math_util.h"

 #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>
 #define CONVOLVE_FUNC Convolve_NEON
 #else
 #define CONVOLVE_FUNC Convolve_C
 #endif

 namespace media {

 static double SincScaleFactor(double io_ratio) {
   // |sinc_scale_factor| is basically the normalized cutoff frequency of the
   // low-pass filter.
   double sinc_scale_factor = io_ratio > 1.0 ? 1.0 / io_ratio : 1.0;

   // The sinc function is an idealized brick-wall filter, but since we're
   // windowing it the transition from pass to stop does not happen right away.
   // So we should adjust the low pass filter cutoff slightly downward to avoid
   // some aliasing at the very high-end.
   // TODO(crogers): this value is empirical and to be more exact should vary
   // depending on kKernelSize.
   sinc_scale_factor *= 0.9;

   return sinc_scale_factor;
 }

 static int CalculateChunkSize(int block_size_, double io_ratio) {
   return block_size_ / io_ratio;
 }

 SincResampler::SincResampler(double io_sample_rate_ratio,
                              int request_frames,
                              const ReadCB& read_cb)
     : io_sample_rate_ratio_(io_sample_rate_ratio),
       read_cb_(read_cb),
       request_frames_(request_frames),
       input_buffer_size_(request_frames_ + kKernelSize),
       // Create input buffers with a 16-byte alignment for SSE optimizations.
       kernel_storage_(static_cast<float*>(
           base::AlignedAlloc(sizeof(float) * kKernelStorageSize, 16))),
       kernel_pre_sinc_storage_(static_cast<float*>(
           base::AlignedAlloc(sizeof(float) * kKernelStorageSize, 16))),
       kernel_window_storage_(static_cast<float*>(
           base::AlignedAlloc(sizeof(float) * kKernelStorageSize, 16))),
       input_buffer_(static_cast<float*>(
           base::AlignedAlloc(sizeof(float) * input_buffer_size_, 16))),
       r1_(input_buffer_.get()),
       r2_(input_buffer_.get() + kKernelSize / 2) {
   CHECK_GT(request_frames_, 0);
   Flush();
   CHECK_GT(block_size_, kKernelSize)
       << "block_size must be greater than kKernelSize!";

   memset(kernel_storage_.get(), 0,
          sizeof(*kernel_storage_.get()) * kKernelStorageSize);
   memset(kernel_pre_sinc_storage_.get(), 0,
          sizeof(*kernel_pre_sinc_storage_.get()) * kKernelStorageSize);
   memset(kernel_window_storage_.get(), 0,
          sizeof(*kernel_window_storage_.get()) * kKernelStorageSize);

   InitializeKernel();
 }

 SincResampler::~SincResampler() = default;

 void SincResampler::UpdateRegions(bool second_load) {
   // Setup various region pointers in the buffer (see diagram above).  If we're
   // on the second load we need to slide r0_ to the right by kKernelSize / 2.
   r0_ = input_buffer_.get() + (second_load ? kKernelSize : kKernelSize / 2);
   r3_ = r0_ + request_frames_ - kKernelSize;
   r4_ = r0_ + request_frames_ - kKernelSize / 2;
   block_size_ = r4_ - r2_;
   chunk_size_ = CalculateChunkSize(block_size_, io_sample_rate_ratio_);

   // r1_ at the beginning of the buffer.
   CHECK_EQ(r1_, input_buffer_.get());
   // r1_ left of r2_, r4_ left of r3_ and size correct.
   CHECK_EQ(r2_ - r1_, r4_ - r3_);
   // r2_ left of r3.
   CHECK_LT(r2_, r3_);
 }

 void SincResampler::InitializeKernel() {
   // Blackman window parameters.
   static const double kAlpha = 0.16;
   static const double kA0 = 0.5 * (1.0 - kAlpha);
   static const double kA1 = 0.5;
   static const double kA2 = 0.5 * kAlpha;

   // Generates a set of windowed sinc() kernels.
   // We generate a range of sub-sample offsets from 0.0 to 1.0.
   const double sinc_scale_factor = SincScaleFactor(io_sample_rate_ratio_);
   for (int offset_idx = 0; offset_idx <= kKernelOffsetCount; ++offset_idx) {
     const float subsample_offset =
         static_cast<float>(offset_idx) / kKernelOffsetCount;

     for (int i = 0; i < kKernelSize; ++i) {
       const int idx = i + offset_idx * kKernelSize;
       const float pre_sinc =
           base::kPiFloat * (i - kKernelSize / 2 - subsample_offset);
       kernel_pre_sinc_storage_[idx] = pre_sinc;

       // Compute Blackman window, matching the offset of the sinc().
       const float x = (i - subsample_offset) / kKernelSize;
       const float window =
           static_cast<float>(kA0 - kA1 * cos(2.0 * base::kPiDouble * x) +
                              kA2 * cos(4.0 * base::kPiDouble * x));
       kernel_window_storage_[idx] = window;

       // Compute the sinc with offset, then window the sinc() function and store
       // at the correct offset.
       kernel_storage_[idx] = static_cast<float>(
           window * (pre_sinc ? sin(sinc_scale_factor * pre_sinc) / pre_sinc
                              : sinc_scale_factor));
     }
   }
 }

 void SincResampler::SetRatio(double io_sample_rate_ratio) {
   if (fabs(io_sample_rate_ratio_ - io_sample_rate_ratio) <
       std::numeric_limits<double>::epsilon()) {
     return;
   }

   io_sample_rate_ratio_ = io_sample_rate_ratio;
   chunk_size_ = CalculateChunkSize(block_size_, io_sample_rate_ratio_);

   // Optimize reinitialization by reusing values which are independent of
   // |sinc_scale_factor|.  Provides a 3x speedup.
   const double sinc_scale_factor = SincScaleFactor(io_sample_rate_ratio_);
   for (int offset_idx = 0; offset_idx <= kKernelOffsetCount; ++offset_idx) {
     for (int i = 0; i < kKernelSize; ++i) {
       const int idx = i + offset_idx * kKernelSize;
       const float window = kernel_window_storage_[idx];
       const float pre_sinc = kernel_pre_sinc_storage_[idx];

       kernel_storage_[idx] = static_cast<float>(
           window * (pre_sinc ? sin(sinc_scale_factor * pre_sinc) / pre_sinc
                              : sinc_scale_factor));
     }
   }
 }

 void SincResampler::Resample(int frames, float* destination) {
   int remaining_frames = frames;

   // Step (1) -- Prime the input buffer at the start of the input stream.
   if (!buffer_primed_ && remaining_frames) {
     read_cb_.Run(request_frames_, r0_);
     buffer_primed_ = true;
   }

   // Step (2) -- Resample!
   while (remaining_frames) {
     // Silent audio can contain non-zero samples small enough to result in
     // subnormals internally. Disabling subnormals can be significantly faster.
     {
       cc::ScopedSubnormalFloatDisabler disable_subnormals;

       while (virtual_source_idx_ < block_size_) {
         // |virtual_source_idx_| lies in between two kernel offsets so figure
         // out what they are.
         const int source_idx = static_cast<int>(virtual_source_idx_);
         const double virtual_offset_idx =
             (virtual_source_idx_ - source_idx) * kKernelOffsetCount;
         const int offset_idx = static_cast<int>(virtual_offset_idx);

         // We'll compute "convolutions" for the two kernels which straddle
         // |virtual_source_idx_|.
         const float* k1 = kernel_storage_.get() + offset_idx * kKernelSize;
         const float* k2 = k1 + kKernelSize;

         // Ensure |k1|, |k2| are 16-byte aligned for SIMD usage.  Should always
         // be true so long as kKernelSize is a multiple of 16.
         DCHECK_EQ(0u, reinterpret_cast<uintptr_t>(k1) & 0x0F);
         DCHECK_EQ(0u, reinterpret_cast<uintptr_t>(k2) & 0x0F);

         // Initialize input pointer based on quantized |virtual_source_idx_|.
         const float* input_ptr = r1_ + source_idx;

         // Figure out how much to weight each kernel's "convolution".
         const double kernel_interpolation_factor =
             virtual_offset_idx - offset_idx;
         *destination++ =
             CONVOLVE_FUNC(input_ptr, k1, k2, kernel_interpolation_factor);

         // Advance the virtual index.
         virtual_source_idx_ += io_sample_rate_ratio_;
         if (!--remaining_frames)
           return;
       }
     }

     // Wrap back around to the start.
     DCHECK_GE(virtual_source_idx_, block_size_);
     virtual_source_idx_ -= block_size_;

     // Step (3) -- Copy r3_, r4_ to r1_, r2_.
     // This wraps the last input frames back to the start of the buffer.
     memcpy(r1_, r3_, sizeof(*input_buffer_.get()) * kKernelSize);

     // Step (4) -- Reinitialize regions if necessary.
     if (r0_ == r2_)
       UpdateRegions(true);

     // Step (5) -- Refresh the buffer with more input.
     read_cb_.Run(request_frames_, r0_);
   }
 }

 void SincResampler::PrimeWithSilence() {
   // By enforcing the buffer hasn't been primed, we ensure the input buffer has
   // already been zeroed during construction or by a previous Flush() call.
   DCHECK(!buffer_primed_);
   DCHECK_EQ(input_buffer_[0], 0.0f);
   UpdateRegions(true);
 }

 void SincResampler::Flush() {
   virtual_source_idx_ = 0;
   buffer_primed_ = false;
   memset(input_buffer_.get(), 0,
          sizeof(*input_buffer_.get()) * input_buffer_size_);
   UpdateRegions(false);
 }

 double SincResampler::BufferedFrames() const {
   return buffer_primed_ ? request_frames_ - virtual_source_idx_ : 0;
 }

 float SincResampler::Convolve_C(const float* input_ptr, const float* k1,
                                 const float* k2,
                                 double kernel_interpolation_factor) {
   float sum1 = 0;
   float sum2 = 0;

   // Generate a single output sample.  Unrolling this loop hurt performance in
   // local testing.
   int n = kKernelSize;
   while (n--) {
     sum1 += *input_ptr * *k1++;
     sum2 += *input_ptr++ * *k2++;
   }

   // Linearly interpolate the two "convolutions".
   return static_cast<float>((1.0 - kernel_interpolation_factor) * sum1 +
       kernel_interpolation_factor * sum2);
 }

 #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(
       static_cast<float>(1.0 - kernel_interpolation_factor)));
   m_sums2 = _mm_mul_ps(m_sums2, _mm_set_ps1(
       static_cast<float>(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,
                                    const float* k2,
                                    double kernel_interpolation_factor) {
   float32x4_t m_input;
   float32x4_t m_sums1 = vmovq_n_f32(0);
   float32x4_t m_sums2 = vmovq_n_f32(0);

   const float* upper = input_ptr + kKernelSize;
   for (; input_ptr < upper; ) {
     m_input = vld1q_f32(input_ptr);
     input_ptr += 4;
     m_sums1 = vmlaq_f32(m_sums1, m_input, vld1q_f32(k1));
     k1 += 4;
     m_sums2 = vmlaq_f32(m_sums2, m_input, vld1q_f32(k2));
     k2 += 4;
   }

   // Linearly interpolate the two "convolutions".
   m_sums1 = vmlaq_f32(
       vmulq_f32(m_sums1, vmovq_n_f32(1.0 - kernel_interpolation_factor)),
       m_sums2, vmovq_n_f32(kernel_interpolation_factor));

   // Sum components together.
   float32x2_t m_half = vadd_f32(vget_high_f32(m_sums1), vget_low_f32(m_sums1));
   return vget_lane_f32(vpadd_f32(m_half, m_half), 0);
 }
 #endif

 }  // namespace media
	// Copyright (c) 2012 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.
	//
	// Initial input buffer layout, dividing into regions r0_ to r4_ (note: r0_, r3_
	// and r4_ will move after the first load):
	//
	// \|----------------\|-----------------------------------------\|----------------\|
	//
	// request_frames_
	// <--------------------------------------------------------->
	// r0_ (during first load)
	//
	// kKernelSize / 2 kKernelSize / 2 kKernelSize / 2 kKernelSize / 2
	// <---------------> <---------------> <---------------> <--------------->
	// r1_ r2_ r3_ r4_
	//
	// block_size_ == r4_ - r2_
	// <--------------------------------------->
	//
	// request_frames_
	// <------------------ ... ----------------->
	// r0_ (during second load)
	//
	// On the second request r0_ slides to the right by kKernelSize / 2 and r3_, r4_
	// and block_size_ are reinitialized via step (3) in the algorithm below.
	//
	// These new regions remain constant until a Flush() occurs. While complicated,
	// this allows us to reduce jitter by always requesting the same amount from the
	// provided callback.
	//
	// The algorithm:
	//
	// 1) Allocate input_buffer of size: request_frames_ + kKernelSize; this ensures
	// there's enough room to read request_frames_ from the callback into region
	// r0_ (which will move between the first and subsequent passes).
	//
	// 2) Let r1_, r2_ each represent half the kernel centered around r0_:
	//
	// r0_ = input_buffer_ + kKernelSize / 2
	// r1_ = input_buffer_
	// r2_ = r0_
	//
	// r0_ is always request_frames_ in size. r1_, r2_ are kKernelSize / 2 in
	// size. r1_ must be zero initialized to avoid convolution with garbage (see
	// step (5) for why).
	//
	// 3) Let r3_, r4_ each represent half the kernel right aligned with the end of
	// r0_ and choose block_size_ as the distance in frames between r4_ and r2_:
	//
	// r3_ = r0_ + request_frames_ - kKernelSize
	// r4_ = r0_ + request_frames_ - kKernelSize / 2
	// block_size_ = r4_ - r2_ = request_frames_ - kKernelSize / 2
	//
	// 4) Consume request_frames_ frames into r0_.
	//
	// 5) Position kernel centered at start of r2_ and generate output frames until
	// the kernel is centered at the start of r4_ or we've finished generating
	// all the output frames.
	//
	// 6) Wrap left over data from the r3_ to r1_ and r4_ to r2_.
	//
	// 7) If we're on the second load, in order to avoid overwriting the frames we
	// just wrapped from r4_ we need to slide r0_ to the right by the size of
	// r4_, which is kKernelSize / 2:
	//
	// r0_ = r0_ + kKernelSize / 2 = input_buffer_ + kKernelSize
	//
	// r3_, r4_, and block_size_ then need to be reinitialized, so goto (3).
	//
	// 8) Else, if we're not on the second load, goto (4).
	//
	// Note: we're glossing over how the sub-sample handling works with
	// \|virtual_source_idx_\|, etc.

	#include "media/base/sinc_resampler.h"

	#include <limits>

	#include "base/logging.h"
	#include "base/numerics/math_constants.h"
	#include "build/build_config.h"
	#include "cc/base/math_util.h"

	#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>
	#define CONVOLVE_FUNC Convolve_NEON
	#else
	#define CONVOLVE_FUNC Convolve_C
	#endif

	namespace media {

	static double SincScaleFactor(double io_ratio) {
	// \|sinc_scale_factor\| is basically the normalized cutoff frequency of the
	// low-pass filter.
	double sinc_scale_factor = io_ratio > 1.0 ? 1.0 / io_ratio : 1.0;

	// The sinc function is an idealized brick-wall filter, but since we're
	// windowing it the transition from pass to stop does not happen right away.
	// So we should adjust the low pass filter cutoff slightly downward to avoid
	// some aliasing at the very high-end.
	// TODO(crogers): this value is empirical and to be more exact should vary
	// depending on kKernelSize.
	sinc_scale_factor *= 0.9;

	return sinc_scale_factor;
	}

	static int CalculateChunkSize(int block_size_, double io_ratio) {
	return block_size_ / io_ratio;
	}

	SincResampler::SincResampler(double io_sample_rate_ratio,
	int request_frames,
	const ReadCB& read_cb)
	: io_sample_rate_ratio_(io_sample_rate_ratio),
	read_cb_(read_cb),
	request_frames_(request_frames),
	input_buffer_size_(request_frames_ + kKernelSize),
	// Create input buffers with a 16-byte alignment for SSE optimizations.
	kernel_storage_(static_cast<float*>(
	base::AlignedAlloc(sizeof(float) * kKernelStorageSize, 16))),
	kernel_pre_sinc_storage_(static_cast<float*>(
	base::AlignedAlloc(sizeof(float) * kKernelStorageSize, 16))),
	kernel_window_storage_(static_cast<float*>(
	base::AlignedAlloc(sizeof(float) * kKernelStorageSize, 16))),
	input_buffer_(static_cast<float*>(
	base::AlignedAlloc(sizeof(float) * input_buffer_size_, 16))),
	r1_(input_buffer_.get()),
	r2_(input_buffer_.get() + kKernelSize / 2) {
	CHECK_GT(request_frames_, 0);
	Flush();
	CHECK_GT(block_size_, kKernelSize)
	<< "block_size must be greater than kKernelSize!";

	memset(kernel_storage_.get(), 0,
	sizeof(kernel_storage_.get()) kKernelStorageSize);
	memset(kernel_pre_sinc_storage_.get(), 0,
	sizeof(kernel_pre_sinc_storage_.get()) kKernelStorageSize);
	memset(kernel_window_storage_.get(), 0,
	sizeof(kernel_window_storage_.get()) kKernelStorageSize);

	InitializeKernel();
	}

	SincResampler::~SincResampler() = default;

	void SincResampler::UpdateRegions(bool second_load) {
	// Setup various region pointers in the buffer (see diagram above). If we're
	// on the second load we need to slide r0_ to the right by kKernelSize / 2.
	r0_ = input_buffer_.get() + (second_load ? kKernelSize : kKernelSize / 2);
	r3_ = r0_ + request_frames_ - kKernelSize;
	r4_ = r0_ + request_frames_ - kKernelSize / 2;
	block_size_ = r4_ - r2_;
	chunk_size_ = CalculateChunkSize(block_size_, io_sample_rate_ratio_);

	// r1_ at the beginning of the buffer.
	CHECK_EQ(r1_, input_buffer_.get());
	// r1_ left of r2_, r4_ left of r3_ and size correct.
	CHECK_EQ(r2_ - r1_, r4_ - r3_);
	// r2_ left of r3.
	CHECK_LT(r2_, r3_);
	}

	void SincResampler::InitializeKernel() {
	// Blackman window parameters.
	static const double kAlpha = 0.16;
	static const double kA0 = 0.5 * (1.0 - kAlpha);
	static const double kA1 = 0.5;
	static const double kA2 = 0.5 * kAlpha;

	// Generates a set of windowed sinc() kernels.
	// We generate a range of sub-sample offsets from 0.0 to 1.0.
	const double sinc_scale_factor = SincScaleFactor(io_sample_rate_ratio_);
	for (int offset_idx = 0; offset_idx <= kKernelOffsetCount; ++offset_idx) {
	const float subsample_offset =
	static_cast<float>(offset_idx) / kKernelOffsetCount;

	for (int i = 0; i < kKernelSize; ++i) {
	const int idx = i + offset_idx * kKernelSize;
	const float pre_sinc =
	base::kPiFloat * (i - kKernelSize / 2 - subsample_offset);
	kernel_pre_sinc_storage_[idx] = pre_sinc;

	// Compute Blackman window, matching the offset of the sinc().
	const float x = (i - subsample_offset) / kKernelSize;
	const float window =
	static_cast<float>(kA0 - kA1 * cos(2.0 * base::kPiDouble * x) +
	kA2 * cos(4.0 * base::kPiDouble * x));
	kernel_window_storage_[idx] = window;

	// Compute the sinc with offset, then window the sinc() function and store
	// at the correct offset.
	kernel_storage_[idx] = static_cast<float>(
	window * (pre_sinc ? sin(sinc_scale_factor * pre_sinc) / pre_sinc
	: sinc_scale_factor));
	}
	}
	}

	void SincResampler::SetRatio(double io_sample_rate_ratio) {
	if (fabs(io_sample_rate_ratio_ - io_sample_rate_ratio) <
	std::numeric_limits<double>::epsilon()) {
	return;
	}

	io_sample_rate_ratio_ = io_sample_rate_ratio;
	chunk_size_ = CalculateChunkSize(block_size_, io_sample_rate_ratio_);

	// Optimize reinitialization by reusing values which are independent of
	// \|sinc_scale_factor\|. Provides a 3x speedup.
	const double sinc_scale_factor = SincScaleFactor(io_sample_rate_ratio_);
	for (int offset_idx = 0; offset_idx <= kKernelOffsetCount; ++offset_idx) {
	for (int i = 0; i < kKernelSize; ++i) {
	const int idx = i + offset_idx * kKernelSize;
	const float window = kernel_window_storage_[idx];
	const float pre_sinc = kernel_pre_sinc_storage_[idx];

	kernel_storage_[idx] = static_cast<float>(
	window * (pre_sinc ? sin(sinc_scale_factor * pre_sinc) / pre_sinc
	: sinc_scale_factor));
	}
	}
	}

	void SincResampler::Resample(int frames, float* destination) {
	int remaining_frames = frames;

	// Step (1) -- Prime the input buffer at the start of the input stream.
	if (!buffer_primed_ && remaining_frames) {
	read_cb_.Run(request_frames_, r0_);
	buffer_primed_ = true;
	}

	// Step (2) -- Resample!
	while (remaining_frames) {
	// Silent audio can contain non-zero samples small enough to result in
	// subnormals internally. Disabling subnormals can be significantly faster.
	{
	cc::ScopedSubnormalFloatDisabler disable_subnormals;

	while (virtual_source_idx_ < block_size_) {
	// \|virtual_source_idx_\| lies in between two kernel offsets so figure
	// out what they are.
	const int source_idx = static_cast<int>(virtual_source_idx_);
	const double virtual_offset_idx =
	(virtual_source_idx_ - source_idx) * kKernelOffsetCount;
	const int offset_idx = static_cast<int>(virtual_offset_idx);

	// We'll compute "convolutions" for the two kernels which straddle
	// \|virtual_source_idx_\|.
	const float* k1 = kernel_storage_.get() + offset_idx * kKernelSize;
	const float* k2 = k1 + kKernelSize;

	// Ensure \|k1\|, \|k2\| are 16-byte aligned for SIMD usage. Should always
	// be true so long as kKernelSize is a multiple of 16.
	DCHECK_EQ(0u, reinterpret_cast<uintptr_t>(k1) & 0x0F);
	DCHECK_EQ(0u, reinterpret_cast<uintptr_t>(k2) & 0x0F);

	// Initialize input pointer based on quantized \|virtual_source_idx_\|.
	const float* input_ptr = r1_ + source_idx;

	// Figure out how much to weight each kernel's "convolution".
	const double kernel_interpolation_factor =
	virtual_offset_idx - offset_idx;
	*destination++ =
	CONVOLVE_FUNC(input_ptr, k1, k2, kernel_interpolation_factor);

	// Advance the virtual index.
	virtual_source_idx_ += io_sample_rate_ratio_;
	if (!--remaining_frames)
	return;
	}
	}

	// Wrap back around to the start.
	DCHECK_GE(virtual_source_idx_, block_size_);
	virtual_source_idx_ -= block_size_;

	// Step (3) -- Copy r3_, r4_ to r1_, r2_.
	// This wraps the last input frames back to the start of the buffer.
	memcpy(r1_, r3_, sizeof(input_buffer_.get()) kKernelSize);

	// Step (4) -- Reinitialize regions if necessary.
	if (r0_ == r2_)
	UpdateRegions(true);

	// Step (5) -- Refresh the buffer with more input.
	read_cb_.Run(request_frames_, r0_);
	}
	}

	void SincResampler::PrimeWithSilence() {
	// By enforcing the buffer hasn't been primed, we ensure the input buffer has
	// already been zeroed during construction or by a previous Flush() call.
	DCHECK(!buffer_primed_);
	DCHECK_EQ(input_buffer_[0], 0.0f);
	UpdateRegions(true);
	}

	void SincResampler::Flush() {
	virtual_source_idx_ = 0;
	buffer_primed_ = false;
	memset(input_buffer_.get(), 0,
	sizeof(input_buffer_.get()) input_buffer_size_);
	UpdateRegions(false);
	}

	double SincResampler::BufferedFrames() const {
	return buffer_primed_ ? request_frames_ - virtual_source_idx_ : 0;
	}

	float SincResampler::Convolve_C(const float* input_ptr, const float* k1,
	const float* k2,
	double kernel_interpolation_factor) {
	float sum1 = 0;
	float sum2 = 0;

	// Generate a single output sample. Unrolling this loop hurt performance in
	// local testing.
	int n = kKernelSize;
	while (n--) {
	sum1 += input_ptr *k1++;
	sum2 += input_ptr++ *k2++;
	}

	// Linearly interpolate the two "convolutions".
	return static_cast<float>((1.0 - kernel_interpolation_factor) * sum1 +
	kernel_interpolation_factor * sum2);
	}

	#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(
	static_cast<float>(1.0 - kernel_interpolation_factor)));
	m_sums2 = _mm_mul_ps(m_sums2, _mm_set_ps1(
	static_cast<float>(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,
	const float* k2,
	double kernel_interpolation_factor) {
	float32x4_t m_input;
	float32x4_t m_sums1 = vmovq_n_f32(0);
	float32x4_t m_sums2 = vmovq_n_f32(0);

	const float* upper = input_ptr + kKernelSize;
	for (; input_ptr < upper; ) {
	m_input = vld1q_f32(input_ptr);
	input_ptr += 4;
	m_sums1 = vmlaq_f32(m_sums1, m_input, vld1q_f32(k1));
	k1 += 4;
	m_sums2 = vmlaq_f32(m_sums2, m_input, vld1q_f32(k2));
	k2 += 4;
	}

	// Linearly interpolate the two "convolutions".
	m_sums1 = vmlaq_f32(
	vmulq_f32(m_sums1, vmovq_n_f32(1.0 - kernel_interpolation_factor)),
	m_sums2, vmovq_n_f32(kernel_interpolation_factor));

	// Sum components together.
	float32x2_t m_half = vadd_f32(vget_high_f32(m_sums1), vget_low_f32(m_sums1));
	return vget_lane_f32(vpadd_f32(m_half, m_half), 0);
	}
	#endif

	} // namespace media