)]}'
{
  "commit": "fd5dadbea9e36368e184394e0dfd7330061a46aa",
  "tree": "c6f35721450ee0017f1160014199a31163c4268a",
  "parents": [
    "be810cba199757e2911adede723e823d6f7856ca"
  ],
  "author": {
    "name": "Alessio Bazzica",
    "email": "alessiob@webrtc.org",
    "time": "Thu Nov 26 13:32:14 2020"
  },
  "committer": {
    "name": "Commit Bot",
    "email": "commit-bot@chromium.org",
    "time": "Thu Dec 03 11:50:09 2020"
  },
  "message": "RNN VAD: use `VectorMath::DotProduct()` for pitch search\n\nThis CL brings a large improvement to the RNN VAD CPU performance\nby finally using `VectorMath::DotProduct()` for pitch search.\n\nThe realtime factor improved from about 390x to 570x for SSE2\n(+180x, 45% faster) and to 610x for AVX2 (+235x, 60% faster).\n\nRNN VAD benchmark results:\n```\n+-----+-------+------+------+\n| run | none* | SSE2 | AVX2 |\n+-----+-------+------+------+\n|   1 | 393x  | 572x | 618x |\n|   2 | 388x  | 568x | 607x |\n|   3 | 393x  | 564x | 599x |\n+-----+-------+------+------+\n```\n*: baseline, no SIMD used for pitch search, but SSE2 used for the RNN\n\nResults obtained as follows:\n1. Force SSE2 in `DISABLED_RnnVadPerformance` for the RNN part in\n   order to measure the baseline correctly:\n```\nRnnBasedVad rnn_vad({/*sse2\u003d*/true, /*avx2\u003d*/true, /*neon\u003d*/false});\n```\n2. Run the test:\n```\n$ ./out/release/modules_unittests \\\n  --gtest_filter\u003d*RnnVadTest*DISABLED_RnnVadPerformance* \\\n  --gtest_also_run_disabled_tests --logs\n```\n\nBug: webrtc:10480\nChange-Id: I89a2bd420265540026944b9c0f1fdd4bfda7f475\nReviewed-on: https://webrtc-review.googlesource.com/c/src/+/195001\nReviewed-by: Gustaf Ullberg \u003cgustaf@webrtc.org\u003e\nCommit-Queue: Alessio Bazzica \u003calessiob@webrtc.org\u003e\nCr-Commit-Position: refs/heads/master@{#32755}\n",
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