Bolt: Optimize Mel Filterbank with Sparse Matrix Multiplication#3
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Bolt: Optimize Mel Filterbank with Sparse Matrix Multiplication#3
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- Precompute start/end indices for non-zero elements in Mel Filterbank - Skip zero-multiplications in computeRawMel loop - Improves performance by ~3-4x on 5s audio clips Co-authored-by: google-labs-jules[bot] <161369871+google-labs-jules[bot]@users.noreply.github.com>
📝 WalkthroughWalkthroughThe PR optimizes Mel filterbank computation by precomputing sparse index ranges ( Changes
Estimated code review effort🎯 2 (Simple) | ⏱️ ~12 minutes Poem
🚥 Pre-merge checks | ✅ 3✅ Passed checks (3 passed)
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🧪 Generate unit tests (beta)
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What: Implemented sparse matrix optimization for the Mel filterbank application step.
Why: The Mel filterbank matrix is ~98.5% sparse (triangular filters). Iterating over all elements (including zeros) was a major performance bottleneck (32k ops/frame vs ~500 ops/frame needed).
Impact:
Measurement: Verify with
npm testwhich includes performance benchmarks.PR created automatically by Jules for task 7908949670163162976 started by @ysdede
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