| // 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 |