Bolt: Optimize mel filterbank matrix multiplication#5
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Precomputes start/end indices for non-zero filterbank values to avoid iterating over zeros (approx 98% sparse). Reduces processing time for 10s audio from ~134ms to ~46ms (~3x speedup). Co-authored-by: google-labs-jules[bot] <161369871+google-labs-jules[bot]@users.noreply.github.com>
📝 WalkthroughWalkthroughDocumentation and implementation of a Mel filterbank optimization strategy. The changes precompute start and end indices for non-zero values in sparse filterbanks, enabling the filterbank computation to skip zero multiplications during mel-spectrogram processing. Changes
Estimated code review effort🎯 3 (Moderate) | ⏱️ ~20 minutes Poem
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🧪 Generate unit tests (beta)
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Actionable comments posted: 1
🤖 Fix all issues with AI agents
In @.jules/bolt.md:
- Around line 1-3: Update the documentation header date in .jules/bolt.md (the
line starting with "## 2024-05-23 - Mel Filterbank Sparsity") to the correct PR
date (February 2026) or the actual change date; edit that header so it reads the
accurate date (e.g., "## 2026-02-XX - Mel Filterbank Sparsity") to keep the
changelog consistent with the PR.
🧹 Nitpick comments (1)
src/mel.js (1)
264-291: Edge case: an all-zero mel bin row will silently fall back to a full-range scan.If every filterbank value for a given mel bin is zero (unlikely but possible with unusual
nMels/sampleRate/nFftcombos), neitherbreakfires, sostartstays0andendstaysthis.nFreqBins— the loop degrades to the old full-range behavior. This is functionally safe but worth a note.You could also tighten it by initializing
end = 0so that the inner loop becomes a no-op for empty rows:Suggested tweak
for (let m = 0; m < this.nMels; m++) { - let start = 0; - let end = this.nFreqBins; + let start = this.nFreqBins; // default: empty range + let end = 0; const fbOff = m * this.nFreqBins; // Find first non-zero
| ## 2024-05-23 - Mel Filterbank Sparsity | ||
| **Learning:** Mel filterbanks are extremely sparse (~98% zeros). Iterating over the full frequency range for each mel bin is a major bottleneck. | ||
| **Action:** Precompute start/end indices for non-zero values in filterbanks to skip zero multiplications. This yielded a ~3x speedup. |
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Stale date in the documentation header.
The date 2024-05-23 doesn't match the PR date (February 2026). Consider updating it to reflect the actual date of the change.
🤖 Prompt for AI Agents
In @.jules/bolt.md around lines 1 - 3, Update the documentation header date in
.jules/bolt.md (the line starting with "## 2024-05-23 - Mel Filterbank
Sparsity") to the correct PR date (February 2026) or the actual change date;
edit that header so it reads the accurate date (e.g., "## 2026-02-XX - Mel
Filterbank Sparsity") to keep the changelog consistent with the PR.
What: Implemented sparse iteration for the Mel filterbank matrix multiplication.
Why: The Mel filterbank is ~98% sparse (mostly zeros). Iterating over the full frequency range for each mel bin was performing unnecessary multiplications by zero.
Impact: Reduces processing time by ~3x (134ms -> 46ms for 10s audio).
Measurement: Verified with a custom benchmark script and existing ONNX correctness tests.
PR created automatically by Jules for task 5107709169723486900 started by @ysdede
Summary by CodeRabbit
Documentation
Added documentation describing Mel filterbank optimization strategy leveraging sparsity patterns.
Refactor
Optimized Mel filterbank computation by precomputing non-zero index ranges, achieving approximately 3x performance improvement.