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fix: vectorize 3-bit and 6-bit bitstream packing (~1900× speedup) - #12

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pbertsch merged 1 commit into
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fix/bitstream-vectorize
Jun 30, 2026
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fix: vectorize 3-bit and 6-bit bitstream packing (~1900× speedup)#12
pbertsch merged 1 commit into
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fix/bitstream-vectorize

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Summary

  • Replace Python for loops in _pack_bitstream / _unpack_bitstream with NumPy broadcasting
  • Same public API, same wire format — zero behavioral change
  • _pack_2bit and _pack_4bit were already vectorized; this brings 3-bit and 6-bit to the same level

Root cause

LCM(3,8) = 24 means each 3-bit block spans 8 indices × 3 bytes. The old implementation looped over every block in Python — O(n / block_size) interpreter ticks. For a typical LLaMA-3 8B KV cache (16M elements), that's 2M Python iterations per serialize call.

Fix

# Pack (n_full blocks at once)
blocks = flat[:n_full * block_indices].reshape(n_full, block_indices).astype(np.uint32)
acc = (blocks << idx_shifts).sum(axis=1, dtype=np.uint32)
bytes_2d = ((acc[:, None] >> byte_shifts) & 0xFF).astype(np.uint8)
out[:n_full * block_bytes] = bytes_2d.ravel()

Tail elements (< 8 for 3-bit) still use a tiny Python loop — they're negligible.

Benchmark (CPU, 131 072 elements, bits=3)

Time
Before ~444 ms (from serde bench)
After 0.23 ms
Speedup ~1 900×

Test plan

  • All 139 packing tests pass (pytest tests/test_packing.py)
  • Full 787-test suite passes
  • Manual roundtrip verified for bits ∈ {3, 6} at n ∈ {131 072, 1 048 576}

🤖 Generated with Claude Code

Replace the Python for-loop over every block with NumPy broadcasting:
  - reshape indices into (n_blocks, block_indices), cast to uint32
  - multiply-broadcast per-position shifts, reduce with .sum(axis=1)
  - extract bytes via right-shift + mask on the (n_blocks, block_bytes) view
Inverse uses the same pattern in reverse.

This eliminates the O(n) Python interpreter overhead that made 3-bit packing
~20× slower than 4-bit in serde benchmarks.

Measured speedup on CPU (n=131072 elements, bits=3):
  before: ~444ms  (from serde benchmark, normalized)
  after:    0.23ms
  ratio: ~1900× faster

All 787 existing packing + quantizer tests pass unchanged.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
@pbertsch

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CI failures are pre-existing and unrelated to this PR:

  • lint: F541 in benchmarks/benchmark_v05.py (untouched by this PR) — pre-existing since April
  • macOS Metal GPU hang: flaky MLX test in test_compressed_cache.py — same failure on main for all recent commits

Linux 3.10/3.11/3.12 all pass. The packing change itself is a single-file edit with 787/787 tests green.

@pbertsch
pbertsch merged commit 8821b08 into main Jun 30, 2026
3 of 6 checks passed
@pbertsch
pbertsch deleted the fix/bitstream-vectorize branch June 30, 2026 17:52
pbertsch added a commit that referenced this pull request Jun 30, 2026
* docs: add README for lmcache-turbo-quant-serde integration

Documents installation, quick start, LMCache v1 architecture (eviction →
serde → L2 backend flow), wire format, configuration reference, CPU
benchmark table, and a prioritised roadmap (CUDA kernel, async pipeline,
3-bit unpack, per-layer bit allocation, PyPI release).

Also removes the stale bench_serde.py note that called the 3-bit packer
"Python-level" — it was vectorised in v0.6 (PR #12).

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

* docs: add LMCache integration section to main README

Adds a short section pointing to the lmcache-turbo-quant-serde plugin —
3-line setup snippet, bits trade-off table, and a link to the full
integrations/lmcache/README.md.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

---------

Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
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