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Move Q² WASM kernel from main thread to worker (issue #76)#77

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devlux76 merged 7 commits intomainfrom
claude/wasm-marshalling-performance-DwBi0
Mar 21, 2026
Merged

Move Q² WASM kernel from main thread to worker (issue #76)#77
devlux76 merged 7 commits intomainfrom
claude/wasm-marshalling-performance-DwBi0

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Previously the worker sent the raw embedding buffer (~16–64 KB for fp32 at n=4096–16384) to the main thread via postMessage, which then copied it into the Q² WASM module's linear memory before quantising.

Now the worker runs the Q² kernel itself immediately after extracting the embedding, and sends only the compact result (n/4 packed bytes + 64-bit key) to the main thread — roughly 64× less data crossing the thread boundary for a typical hidden dimension of 4096.

Changes:

  • types.ts: add Q2Msg (packed ArrayBuffer + bigint key + n); add to WorkerOutMsg union alongside the existing EmbeddingMsg
  • worker.ts: import getKernel + memory-offset constants from q2.ts; add quantiseAndSend() helper that copies the embedding into WASM memory, runs q2_quantise / q2_key, slices the output into a transferable buffer, and sends a Q2Msg
  • app.ts: remove getKernel, DTYPE_TO_Q2, Q2_DTYPE_FP32, Q2_INPUT_OFFSET, Q2_OUTPUT_OFFSET imports; add onQ2(msg: Q2Msg) handler that calls renderQ2Result directly; add 'q2' case to handleWorkerMessage; strip the WASM kernel block (and its TS fallback) from onEmbedding so the main thread never touches the raw activation buffer
  • test/app.test.ts: add onQ2 unit test covering the no-raw-buffer path

https://claude.ai/code/session_01LhgZ1cdXDG4YwSvtrbUvdk

Description

Related Issue

Closes #76

Previously the worker sent the raw embedding buffer (~16–64 KB for fp32
at n=4096–16384) to the main thread via postMessage, which then copied
it into the Q² WASM module's linear memory before quantising.

Now the worker runs the Q² kernel itself immediately after extracting
the embedding, and sends only the compact result (n/4 packed bytes +
64-bit key) to the main thread — roughly 64× less data crossing the
thread boundary for a typical hidden dimension of 4096.

Changes:
- types.ts: add Q2Msg (packed ArrayBuffer + bigint key + n); add to
  WorkerOutMsg union alongside the existing EmbeddingMsg
- worker.ts: import getKernel + memory-offset constants from q2.ts;
  add quantiseAndSend() helper that copies the embedding into WASM
  memory, runs q2_quantise / q2_key, slices the output into a
  transferable buffer, and sends a Q2Msg
- app.ts: remove getKernel, DTYPE_TO_Q2, Q2_DTYPE_FP32, Q2_INPUT_OFFSET,
  Q2_OUTPUT_OFFSET imports; add onQ2(msg: Q2Msg) handler that calls
  renderQ2Result directly; add 'q2' case to handleWorkerMessage; strip
  the WASM kernel block (and its TS fallback) from onEmbedding so the
  main thread never touches the raw activation buffer
- test/app.test.ts: add onQ2 unit test covering the no-raw-buffer path

https://claude.ai/code/session_01LhgZ1cdXDG4YwSvtrbUvdk
Copilot AI review requested due to automatic review settings March 21, 2026 06:01
The function is scaffolding for when embedding extraction is wired up;
until then it must match /^_/ to satisfy @typescript-eslint/no-unused-vars.

https://claude.ai/code/session_01LhgZ1cdXDG4YwSvtrbUvdk
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Pull request overview

This PR aims to move the Q² WASM quantisation work into the worker so the main thread no longer receives/transfers the full raw embedding buffer, and instead only receives the compact Q² output (packed bytes + 64-bit key).

Changes:

  • Add a new Q2Msg worker→main message type carrying { packed: ArrayBuffer, key: bigint, n }.
  • Introduce a worker-side quantiseAndSend() helper that runs the Q² WASM kernel and posts Q2Msg with a transferable packed buffer.
  • Update the app’s worker message handler to render Q² results via a new onQ2() handler; add a unit test for onQ2.

Reviewed changes

Copilot reviewed 4 out of 4 changed files in this pull request and generated 2 comments.

File Description
test/app.test.ts Adds a unit test asserting onQ2() updates the embedding stats UI without needing the raw embedding buffer.
src/worker.ts Imports the Q² kernel + offsets and adds quantiseAndSend() to compute and post compact Q² results from inside the worker.
src/types.ts Defines Q2Msg and extends WorkerOutMsg union to include it.
src/app.ts Removes main-thread Q² kernel usage from onEmbedding() and adds onQ2() + message routing for type: 'q2'.

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Comment thread src/worker.ts Outdated
Comment on lines +277 to +307
async function _quantiseAndSend(
embeddingBuffer: ArrayBuffer,
seqLen: number,
hiddenDim: number,
dtype: EmbeddingMsg['dtype'],
): Promise<void> {
const n = hiddenDim;
const dtypeId = DTYPE_TO_Q2[dtype] ?? Q2_DTYPE_FP32;
try {
const kernel = await getKernel();
const mem = new Uint8Array(kernel.memory.buffer);

// Copy activation bytes into WASM linear memory at the fixed input offset.
mem.set(new Uint8Array(embeddingBuffer), Q2_INPUT_OFFSET);

// L2-normalise last token, threshold, Gray-encode → packed output at Q2_OUTPUT_OFFSET.
kernel.quantise(Q2_INPUT_OFFSET, seqLen, n, dtypeId, Q2_OUTPUT_OFFSET);

// Derive the 64-bit transition key.
const key = BigInt.asUintN(64, kernel.key(Q2_OUTPUT_OFFSET, n));

// Slice to an independent buffer so we can transfer ownership without
// detaching the WASM module's shared memory view.
const packed = new Uint8Array(kernel.memory.buffer, Q2_OUTPUT_OFFSET, n >> 2).slice();

workerLog('debug', 'Q² kernel produced key', { key: `0x${key.toString(16).padStart(16, '0')}`, n });
send({ type: 'q2', packed: packed.buffer, key, n }, [packed.buffer]);
} catch (err) {
workerLog('warn', 'Q² kernel failed; skipping quantisation result', { error: err });
}
}
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quantiseAndSend() is never invoked (only defined). As a result, the worker will never emit { type: 'q2' } messages, and since app.ts no longer runs the Q² kernel in onEmbedding, the UI will never render Q² results. Wire this helper into the embedding-extraction path (or remove the unused helper + revert the main-thread removal).

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Comment thread src/worker.ts
Comment on lines +292 to +294
// L2-normalise last token, threshold, Gray-encode → packed output at Q2_OUTPUT_OFFSET.
kernel.quantise(Q2_INPUT_OFFSET, seqLen, n, dtypeId, Q2_OUTPUT_OFFSET);

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quantiseAndSend() no longer guards against seqLen < 1 (previously the main-thread path skipped quantisation in that case). Calling kernel.quantise(..., seqLen, ...) with seqLen=0 will make the kernel read from an invalid last-token position. Add an early return/log when seqLen < 1 (and consider validating hiddenDim/n as well).

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claude added 4 commits March 21, 2026 06:06
After text generation completes the worker now tokenizes the full
conversation and calls pipe.model() directly for one additional forward
pass (no KV cache, O(seqLen) attention).  If the loaded ONNX model
exports a `last_hidden_state` output node, the resulting [1, seqLen,
hiddenDim] tensor is passed to quantiseAndSend() which runs the Q²
kernel in-worker and sends only the compact Q2Msg to the main thread.

When `last_hidden_state` is absent (standard onnx-community models
export only logits + past_key_values) the step is skipped silently at
debug log level — the generation flow is unaffected.

This removes the _-prefix from quantiseAndSend (it is now called on
every non-aborted generation turn) and eliminates the dead-code warning
block that previously told callers the feature was unsupported.

https://claude.ai/code/session_01LhgZ1cdXDG4YwSvtrbUvdk
Problem: most models don't use the name 'last_hidden_state', so Q²
fingerprinting silently did nothing and there was no way for the user
to know why or what to do about it.

Changes:

types.ts
  Add ModelOutputsMsg { outputs: Record<string, number[]>, hiddenStateKey: string|null }
  sent once per generation turn to the main thread regardless of outcome.

worker.ts
  Replace the single hardcoded 'last_hidden_state' lookup with a two-pass
  detection strategy:
    1. Try HIDDEN_STATE_CANDIDATES in order (covers standard HF naming and
       likely LFM2.5 variants such as 'last_conv_hidden_states').
    2. Fall back to any 3-D output (shape [batch, seq, hidden]) — catches
       models that use non-standard but unambiguous output names.
  Always collect output shapes and send ModelOutputsMsg so the main thread
  can display exactly what the model exports.

app.ts
  Add onModelOutputs() handler: shows the full output node list in the
  embedding panel.  When hiddenStateKey is null, displays a clear message
  explaining Q² is unavailable and what the model would need to export to
  enable it.  Routes 'model-outputs' in handleWorkerMessage.

https://claude.ai/code/session_01LhgZ1cdXDG4YwSvtrbUvdk
Markdown parses a bare * as italic/bold markup before KaTeX renders
the surrounding $$ block, so lint-md flagged it as an error.

https://claude.ai/code/session_01LhgZ1cdXDG4YwSvtrbUvdk
Reflects @playwright/test addition and transitive dependency
resolution changes from bun install.

https://claude.ai/code/session_01LhgZ1cdXDG4YwSvtrbUvdk
@devlux76
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@copilot Please perform a fresh code review from the top. There were a lot of misc fixes committed between your last review and now. Fix any oustanding issues you find so we can close this PR.

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Copilot AI commented Mar 21, 2026

@devlux76 I've opened a new pull request, #78, to work on those changes. Once the pull request is ready, I'll request review from you.

@devlux76 devlux76 merged commit 488d9ad into main Mar 21, 2026
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@devlux76 devlux76 deleted the claude/wasm-marshalling-performance-DwBi0 branch March 21, 2026 06:35
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4 participants