1 // Copyright (c) 2012 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 // Initial input buffer layout, dividing into regions r0_ to r4_ (note: r0_, r3_ 6 // and r4_ will move after the first load): 7 // 8 // |----------------|-----------------------------------------|----------------| 9 // 10 // request_frames_ 11 // <---------------------------------------------------------> 12 // r0_ (during first load) 13 // 14 // kKernelSize / 2 kKernelSize / 2 kKernelSize / 2 kKernelSize / 2 15 // <---------------> <---------------> <---------------> <---------------> 16 // r1_ r2_ r3_ r4_ 17 // 18 // block_size_ == r4_ - r2_ 19 // <---------------------------------------> 20 // 21 // request_frames_ 22 // <------------------ ... -----------------> 23 // r0_ (during second load) 24 // 25 // On the second request r0_ slides to the right by kKernelSize / 2 and r3_, r4_ 26 // and block_size_ are reinitialized via step (3) in the algorithm below. 27 // 28 // These new regions remain constant until a Flush() occurs. While complicated, 29 // this allows us to reduce jitter by always requesting the same amount from the 30 // provided callback. 31 // 32 // The algorithm: 33 // 34 // 1) Allocate input_buffer of size: request_frames_ + kKernelSize; this ensures 35 // there's enough room to read request_frames_ from the callback into region 36 // r0_ (which will move between the first and subsequent passes). 37 // 38 // 2) Let r1_, r2_ each represent half the kernel centered around r0_: 39 // 40 // r0_ = input_buffer_ + kKernelSize / 2 41 // r1_ = input_buffer_ 42 // r2_ = r0_ 43 // 44 // r0_ is always request_frames_ in size. r1_, r2_ are kKernelSize / 2 in 45 // size. r1_ must be zero initialized to avoid convolution with garbage (see 46 // step (5) for why). 47 // 48 // 3) Let r3_, r4_ each represent half the kernel right aligned with the end of 49 // r0_ and choose block_size_ as the distance in frames between r4_ and r2_: 50 // 51 // r3_ = r0_ + request_frames_ - kKernelSize 52 // r4_ = r0_ + request_frames_ - kKernelSize / 2 53 // block_size_ = r4_ - r2_ = request_frames_ - kKernelSize / 2 54 // 55 // 4) Consume request_frames_ frames into r0_. 56 // 57 // 5) Position kernel centered at start of r2_ and generate output frames until 58 // the kernel is centered at the start of r4_ or we've finished generating 59 // all the output frames. 60 // 61 // 6) Wrap left over data from the r3_ to r1_ and r4_ to r2_. 62 // 63 // 7) If we're on the second load, in order to avoid overwriting the frames we 64 // just wrapped from r4_ we need to slide r0_ to the right by the size of 65 // r4_, which is kKernelSize / 2: 66 // 67 // r0_ = r0_ + kKernelSize / 2 = input_buffer_ + kKernelSize 68 // 69 // r3_, r4_, and block_size_ then need to be reinitialized, so goto (3). 70 // 71 // 8) Else, if we're not on the second load, goto (4). 72 // 73 // Note: we're glossing over how the sub-sample handling works with 74 // |virtual_source_idx_|, etc. 75 76 // MSVC++ requires this to be set before any other includes to get M_PI. 77 #define _USE_MATH_DEFINES 78 79 #include "media/base/sinc_resampler.h" 80 81 #include <cmath> 82 #include <limits> 83 84 #include "base/logging.h" 85 86 #if defined(ARCH_CPU_X86_FAMILY) 87 #include <xmmintrin.h> 88 #define CONVOLVE_FUNC Convolve_SSE 89 #elif defined(ARCH_CPU_ARM_FAMILY) && defined(USE_NEON) 90 #include <arm_neon.h> 91 #define CONVOLVE_FUNC Convolve_NEON 92 #else 93 #define CONVOLVE_FUNC Convolve_C 94 #endif 95 96 namespace media { 97 98 static double SincScaleFactor(double io_ratio) { 99 // |sinc_scale_factor| is basically the normalized cutoff frequency of the 100 // low-pass filter. 101 double sinc_scale_factor = io_ratio > 1.0 ? 1.0 / io_ratio : 1.0; 102 103 // The sinc function is an idealized brick-wall filter, but since we're 104 // windowing it the transition from pass to stop does not happen right away. 105 // So we should adjust the low pass filter cutoff slightly downward to avoid 106 // some aliasing at the very high-end. 107 // TODO(crogers): this value is empirical and to be more exact should vary 108 // depending on kKernelSize. 109 sinc_scale_factor *= 0.9; 110 111 return sinc_scale_factor; 112 } 113 114 SincResampler::SincResampler(double io_sample_rate_ratio, 115 int request_frames, 116 const ReadCB& read_cb) 117 : io_sample_rate_ratio_(io_sample_rate_ratio), 118 read_cb_(read_cb), 119 request_frames_(request_frames), 120 input_buffer_size_(request_frames_ + kKernelSize), 121 // Create input buffers with a 16-byte alignment for SSE optimizations. 122 kernel_storage_(static_cast<float*>( 123 base::AlignedAlloc(sizeof(float) * kKernelStorageSize, 16))), 124 kernel_pre_sinc_storage_(static_cast<float*>( 125 base::AlignedAlloc(sizeof(float) * kKernelStorageSize, 16))), 126 kernel_window_storage_(static_cast<float*>( 127 base::AlignedAlloc(sizeof(float) * kKernelStorageSize, 16))), 128 input_buffer_(static_cast<float*>( 129 base::AlignedAlloc(sizeof(float) * input_buffer_size_, 16))), 130 r1_(input_buffer_.get()), 131 r2_(input_buffer_.get() + kKernelSize / 2) { 132 CHECK_GT(request_frames_, 0); 133 Flush(); 134 CHECK_GT(block_size_, kKernelSize) 135 << "block_size must be greater than kKernelSize!"; 136 137 memset(kernel_storage_.get(), 0, 138 sizeof(*kernel_storage_.get()) * kKernelStorageSize); 139 memset(kernel_pre_sinc_storage_.get(), 0, 140 sizeof(*kernel_pre_sinc_storage_.get()) * kKernelStorageSize); 141 memset(kernel_window_storage_.get(), 0, 142 sizeof(*kernel_window_storage_.get()) * kKernelStorageSize); 143 144 InitializeKernel(); 145 } 146 147 SincResampler::~SincResampler() {} 148 149 void SincResampler::UpdateRegions(bool second_load) { 150 // Setup various region pointers in the buffer (see diagram above). If we're 151 // on the second load we need to slide r0_ to the right by kKernelSize / 2. 152 r0_ = input_buffer_.get() + (second_load ? kKernelSize : kKernelSize / 2); 153 r3_ = r0_ + request_frames_ - kKernelSize; 154 r4_ = r0_ + request_frames_ - kKernelSize / 2; 155 block_size_ = r4_ - r2_; 156 157 // r1_ at the beginning of the buffer. 158 CHECK_EQ(r1_, input_buffer_.get()); 159 // r1_ left of r2_, r4_ left of r3_ and size correct. 160 CHECK_EQ(r2_ - r1_, r4_ - r3_); 161 // r2_ left of r3. 162 CHECK_LT(r2_, r3_); 163 } 164 165 void SincResampler::InitializeKernel() { 166 // Blackman window parameters. 167 static const double kAlpha = 0.16; 168 static const double kA0 = 0.5 * (1.0 - kAlpha); 169 static const double kA1 = 0.5; 170 static const double kA2 = 0.5 * kAlpha; 171 172 // Generates a set of windowed sinc() kernels. 173 // We generate a range of sub-sample offsets from 0.0 to 1.0. 174 const double sinc_scale_factor = SincScaleFactor(io_sample_rate_ratio_); 175 for (int offset_idx = 0; offset_idx <= kKernelOffsetCount; ++offset_idx) { 176 const float subsample_offset = 177 static_cast<float>(offset_idx) / kKernelOffsetCount; 178 179 for (int i = 0; i < kKernelSize; ++i) { 180 const int idx = i + offset_idx * kKernelSize; 181 const float pre_sinc = M_PI * (i - kKernelSize / 2 - subsample_offset); 182 kernel_pre_sinc_storage_[idx] = pre_sinc; 183 184 // Compute Blackman window, matching the offset of the sinc(). 185 const float x = (i - subsample_offset) / kKernelSize; 186 const float window = 187 kA0 - kA1 * cos(2.0 * M_PI * x) + kA2 * cos(4.0 * M_PI * x); 188 kernel_window_storage_[idx] = window; 189 190 // Compute the sinc with offset, then window the sinc() function and store 191 // at the correct offset. 192 if (pre_sinc == 0) { 193 kernel_storage_[idx] = sinc_scale_factor * window; 194 } else { 195 kernel_storage_[idx] = 196 window * sin(sinc_scale_factor * pre_sinc) / pre_sinc; 197 } 198 } 199 } 200 } 201 202 void SincResampler::SetRatio(double io_sample_rate_ratio) { 203 if (fabs(io_sample_rate_ratio_ - io_sample_rate_ratio) < 204 std::numeric_limits<double>::epsilon()) { 205 return; 206 } 207 208 io_sample_rate_ratio_ = io_sample_rate_ratio; 209 210 // Optimize reinitialization by reusing values which are independent of 211 // |sinc_scale_factor|. Provides a 3x speedup. 212 const double sinc_scale_factor = SincScaleFactor(io_sample_rate_ratio_); 213 for (int offset_idx = 0; offset_idx <= kKernelOffsetCount; ++offset_idx) { 214 for (int i = 0; i < kKernelSize; ++i) { 215 const int idx = i + offset_idx * kKernelSize; 216 const float window = kernel_window_storage_[idx]; 217 const float pre_sinc = kernel_pre_sinc_storage_[idx]; 218 219 if (pre_sinc == 0) { 220 kernel_storage_[idx] = sinc_scale_factor * window; 221 } else { 222 kernel_storage_[idx] = 223 window * sin(sinc_scale_factor * pre_sinc) / pre_sinc; 224 } 225 } 226 } 227 } 228 229 void SincResampler::Resample(int frames, float* destination) { 230 int remaining_frames = frames; 231 232 // Step (1) -- Prime the input buffer at the start of the input stream. 233 if (!buffer_primed_ && remaining_frames) { 234 read_cb_.Run(request_frames_, r0_); 235 buffer_primed_ = true; 236 } 237 238 // Step (2) -- Resample! const what we can outside of the loop for speed. It 239 // actually has an impact on ARM performance. See inner loop comment below. 240 const double current_io_ratio = io_sample_rate_ratio_; 241 const float* const kernel_ptr = kernel_storage_.get(); 242 while (remaining_frames) { 243 // Note: The loop construct here can severely impact performance on ARM 244 // or when built with clang. See https://codereview.chromium.org/18566009/ 245 int source_idx = virtual_source_idx_; 246 while (source_idx < block_size_) { 247 // |virtual_source_idx_| lies in between two kernel offsets so figure out 248 // what they are. 249 const double subsample_remainder = virtual_source_idx_ - source_idx; 250 251 const double virtual_offset_idx = 252 subsample_remainder * kKernelOffsetCount; 253 const int offset_idx = virtual_offset_idx; 254 255 // We'll compute "convolutions" for the two kernels which straddle 256 // |virtual_source_idx_|. 257 const float* const k1 = kernel_ptr + offset_idx * kKernelSize; 258 const float* const k2 = k1 + kKernelSize; 259 260 // Ensure |k1|, |k2| are 16-byte aligned for SIMD usage. Should always be 261 // true so long as kKernelSize is a multiple of 16. 262 DCHECK_EQ(0u, reinterpret_cast<uintptr_t>(k1) & 0x0F); 263 DCHECK_EQ(0u, reinterpret_cast<uintptr_t>(k2) & 0x0F); 264 265 // Initialize input pointer based on quantized |virtual_source_idx_|. 266 const float* const input_ptr = r1_ + source_idx; 267 268 // Figure out how much to weight each kernel's "convolution". 269 const double kernel_interpolation_factor = 270 virtual_offset_idx - offset_idx; 271 *destination++ = CONVOLVE_FUNC( 272 input_ptr, k1, k2, kernel_interpolation_factor); 273 274 // Advance the virtual index. 275 virtual_source_idx_ += current_io_ratio; 276 source_idx = virtual_source_idx_; 277 278 if (!--remaining_frames) 279 return; 280 } 281 282 // Wrap back around to the start. 283 DCHECK_GE(virtual_source_idx_, block_size_); 284 virtual_source_idx_ -= block_size_; 285 286 // Step (3) -- Copy r3_, r4_ to r1_, r2_. 287 // This wraps the last input frames back to the start of the buffer. 288 memcpy(r1_, r3_, sizeof(*input_buffer_.get()) * kKernelSize); 289 290 // Step (4) -- Reinitialize regions if necessary. 291 if (r0_ == r2_) 292 UpdateRegions(true); 293 294 // Step (5) -- Refresh the buffer with more input. 295 read_cb_.Run(request_frames_, r0_); 296 } 297 } 298 299 int SincResampler::ChunkSize() const { 300 return block_size_ / io_sample_rate_ratio_; 301 } 302 303 void SincResampler::Flush() { 304 virtual_source_idx_ = 0; 305 buffer_primed_ = false; 306 memset(input_buffer_.get(), 0, 307 sizeof(*input_buffer_.get()) * input_buffer_size_); 308 UpdateRegions(false); 309 } 310 311 float SincResampler::Convolve_C(const float* input_ptr, const float* k1, 312 const float* k2, 313 double kernel_interpolation_factor) { 314 float sum1 = 0; 315 float sum2 = 0; 316 317 // Generate a single output sample. Unrolling this loop hurt performance in 318 // local testing. 319 int n = kKernelSize; 320 while (n--) { 321 sum1 += *input_ptr * *k1++; 322 sum2 += *input_ptr++ * *k2++; 323 } 324 325 // Linearly interpolate the two "convolutions". 326 return (1.0 - kernel_interpolation_factor) * sum1 327 + kernel_interpolation_factor * sum2; 328 } 329 330 #if defined(ARCH_CPU_X86_FAMILY) 331 float SincResampler::Convolve_SSE(const float* input_ptr, const float* k1, 332 const float* k2, 333 double kernel_interpolation_factor) { 334 __m128 m_input; 335 __m128 m_sums1 = _mm_setzero_ps(); 336 __m128 m_sums2 = _mm_setzero_ps(); 337 338 // Based on |input_ptr| alignment, we need to use loadu or load. Unrolling 339 // these loops hurt performance in local testing. 340 if (reinterpret_cast<uintptr_t>(input_ptr) & 0x0F) { 341 for (int i = 0; i < kKernelSize; i += 4) { 342 m_input = _mm_loadu_ps(input_ptr + i); 343 m_sums1 = _mm_add_ps(m_sums1, _mm_mul_ps(m_input, _mm_load_ps(k1 + i))); 344 m_sums2 = _mm_add_ps(m_sums2, _mm_mul_ps(m_input, _mm_load_ps(k2 + i))); 345 } 346 } else { 347 for (int i = 0; i < kKernelSize; i += 4) { 348 m_input = _mm_load_ps(input_ptr + i); 349 m_sums1 = _mm_add_ps(m_sums1, _mm_mul_ps(m_input, _mm_load_ps(k1 + i))); 350 m_sums2 = _mm_add_ps(m_sums2, _mm_mul_ps(m_input, _mm_load_ps(k2 + i))); 351 } 352 } 353 354 // Linearly interpolate the two "convolutions". 355 m_sums1 = _mm_mul_ps(m_sums1, _mm_set_ps1(1.0 - kernel_interpolation_factor)); 356 m_sums2 = _mm_mul_ps(m_sums2, _mm_set_ps1(kernel_interpolation_factor)); 357 m_sums1 = _mm_add_ps(m_sums1, m_sums2); 358 359 // Sum components together. 360 float result; 361 m_sums2 = _mm_add_ps(_mm_movehl_ps(m_sums1, m_sums1), m_sums1); 362 _mm_store_ss(&result, _mm_add_ss(m_sums2, _mm_shuffle_ps( 363 m_sums2, m_sums2, 1))); 364 365 return result; 366 } 367 #elif defined(ARCH_CPU_ARM_FAMILY) && defined(USE_NEON) 368 float SincResampler::Convolve_NEON(const float* input_ptr, const float* k1, 369 const float* k2, 370 double kernel_interpolation_factor) { 371 float32x4_t m_input; 372 float32x4_t m_sums1 = vmovq_n_f32(0); 373 float32x4_t m_sums2 = vmovq_n_f32(0); 374 375 const float* upper = input_ptr + kKernelSize; 376 for (; input_ptr < upper; ) { 377 m_input = vld1q_f32(input_ptr); 378 input_ptr += 4; 379 m_sums1 = vmlaq_f32(m_sums1, m_input, vld1q_f32(k1)); 380 k1 += 4; 381 m_sums2 = vmlaq_f32(m_sums2, m_input, vld1q_f32(k2)); 382 k2 += 4; 383 } 384 385 // Linearly interpolate the two "convolutions". 386 m_sums1 = vmlaq_f32( 387 vmulq_f32(m_sums1, vmovq_n_f32(1.0 - kernel_interpolation_factor)), 388 m_sums2, vmovq_n_f32(kernel_interpolation_factor)); 389 390 // Sum components together. 391 float32x2_t m_half = vadd_f32(vget_high_f32(m_sums1), vget_low_f32(m_sums1)); 392 return vget_lane_f32(vpadd_f32(m_half, m_half), 0); 393 } 394 #endif 395 396 } // namespace media 397