Optimize MatchedFilter.
Changing to an index for-loop (instead of using std::max_element & std::distance) tracking even & odd elements separately allows the compiler to produce code with less pipeline stall. Bug: None Change-Id: Iaa3e820a3a3b61e2eb276f0dac9106c848db1891 Reviewed-on: https://webrtc-review.googlesource.com/c/src/+/240061 Reviewed-by: Per Åhgren <peah@webrtc.org> Commit-Queue: Christian Schuldt <cschuldt@google.com> Cr-Commit-Position: refs/heads/main@{#35729}
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@ -308,6 +308,41 @@ void MatchedFilterCore(size_t x_start_index,
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}
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}
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size_t MaxSquarePeakIndex(rtc::ArrayView<const float> h) {
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if (h.size() < 2) {
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return 0;
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}
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float max_element1 = h[0] * h[0];
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float max_element2 = h[1] * h[1];
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size_t lag_estimate1 = 0;
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size_t lag_estimate2 = 1;
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const size_t last_index = h.size() - 1;
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// Keeping track of even & odd max elements separately typically allows the
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// compiler to produce more efficient code.
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for (size_t k = 2; k < last_index; k += 2) {
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float element1 = h[k] * h[k];
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float element2 = h[k + 1] * h[k + 1];
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if (element1 > max_element1) {
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max_element1 = element1;
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lag_estimate1 = k;
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}
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if (element2 > max_element2) {
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max_element2 = element2;
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lag_estimate2 = k + 1;
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}
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}
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if (max_element2 > max_element1) {
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max_element1 = max_element2;
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lag_estimate1 = lag_estimate2;
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}
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// In case of odd h size, we have not yet checked the last element.
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float last_element = h[last_index] * h[last_index];
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if (last_element > max_element1) {
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return last_index;
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}
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return lag_estimate1;
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}
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} // namespace aec3
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MatchedFilter::MatchedFilter(ApmDataDumper* data_dumper,
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@ -400,17 +435,15 @@ void MatchedFilter::Update(const DownsampledRenderBuffer& render_buffer,
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}
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// Compute anchor for the matched filter error.
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const float error_sum_anchor =
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std::inner_product(y.begin(), y.end(), y.begin(), 0.f);
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float error_sum_anchor = 0.0f;
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for (size_t k = 0; k < y.size(); ++k) {
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error_sum_anchor += y[k] * y[k];
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}
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// Estimate the lag in the matched filter as the distance to the portion in
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// the filter that contributes the most to the matched filter output. This
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// is detected as the peak of the matched filter.
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const size_t lag_estimate = std::distance(
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filters_[n].begin(),
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std::max_element(
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filters_[n].begin(), filters_[n].end(),
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[](float a, float b) -> bool { return a * a < b * b; }));
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const size_t lag_estimate = aec3::MaxSquarePeakIndex(filters_[n]);
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// Update the lag estimates for the matched filter.
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lag_estimates_[n] = LagEstimate(
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@ -74,6 +74,9 @@ void MatchedFilterCore(size_t x_start_index,
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bool* filters_updated,
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float* error_sum);
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// Find largest peak of squared values in array.
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size_t MaxSquarePeakIndex(rtc::ArrayView<const float> h);
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} // namespace aec3
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// Produces recursively updated cross-correlation estimates for several signal
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@ -176,6 +176,28 @@ TEST(MatchedFilter, TestAvx2Optimizations) {
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#endif
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// Verifies that the (optimized) function MaxSquarePeakIndex() produces output
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// equal to the corresponding std-functions.
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TEST(MatchedFilter, MaxSquarePeakIndex) {
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Random random_generator(42U);
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constexpr int kMaxLength = 128;
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constexpr int kNumIterationsPerLength = 256;
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for (int length = 1; length < kMaxLength; ++length) {
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std::vector<float> y(length);
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for (int i = 0; i < kNumIterationsPerLength; ++i) {
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RandomizeSampleVector(&random_generator, y);
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size_t lag_from_function = MaxSquarePeakIndex(y);
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size_t lag_from_std = std::distance(
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y.begin(),
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std::max_element(y.begin(), y.end(), [](float a, float b) -> bool {
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return a * a < b * b;
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}));
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EXPECT_EQ(lag_from_function, lag_from_std);
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}
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}
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}
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// Verifies that the matched filter produces proper lag estimates for
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// artificially
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// delayed signals.
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