Files
LocalAI/backend/cpp/llama-cpp/patches
Ettore Di Giacinto db6ebc53b2 feat(paged): block-table within-step host cache (patch 0029)
Mirror of paged-dev commit e2acb3b (lever 5). get_block_table() is recomputed
once per full-attention layer per decode step, but the KV cell layout is fixed
for the whole step (it only changes in apply()). This caches the table the first
time it is built in a step and memcpy-reuses the identical bytes for the rest,
invalidating in apply(). Bit-exact; toggle off with LLAMA_PAGED_NO_BT_CACHE=1.

Host-side get_block_table time (llama-batched-bench, npp128 ntg128 npl128,
cache OFF -> ON): MoE 112.94 -> 14.82 ms (-87%), dense 193.78 -> 16.90 ms (-91%).
Dense decode is partly host-bound and gains (TG 364.8 -> 374.7 t/s, ~96% of the
vLLM 391 t/s @npl128 reference); MoE decode is compute-bound (FP4 GEMM) so the
saved host time is off the critical path and MoE TG is flat. Details in
LEVER5_HOSTPIPE_RESULTS.md.

Also records the per-path bit-exactness gate (PAGED_BITEXACT_NOTE.md): the
paged-MoE greedy md5 (8cb0ce23) differs from the non-paged md5 (07db32c2) by a
benign FP-accumulation-order difference of the paged attention reduction, not a
bug. KL-validated vs the f16 reference (16 chunks, c512): KLD(paged||f16) =
0.13600 <= KLD(nonpaged||f16) = 0.13660, PPL(paged) = 7.4009 ~ PPL(nonpaged) =
7.3896 (within +/- 0.29). Canonical references are now per path: non-paged MoE
07db32c2 and paged MoE 8cb0ce23; dense is bit-exact across paths (5951a5b4).

Assisted-by: Claude:opus-4.8 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2026-06-27 01:47:08 +00:00
..

llama.cpp patch series — paged attention (vLLM-parity engine)

A stacking series: each patch is a small, self-contained, independently-buildable step toward an in-model paged-attention engine. They apply in numeric order on top of the pinned LLAMA_VERSION (backend/cpp/llama-cpp/Makefile). The build applies them automatically after checkout (see the llama.cpp: target). Keeping the work as ordered patches — rather than one big diff — is what lets us rebase cleanly across llama.cpp bumps and avoid drift: when a patch stops applying, only that small patch needs fixing, and the failure points at exactly which step the upstream change touched.

Base

  • LLAMA_VERSION pin in ../Makefile. All patches are generated against that exact commit. Bumping the pin = re-run the regen workflow below and fix only the patches that no longer apply.

The series (phases → patches)

# Patch What Verifies
0001 0001-vendor-paged-kv-manager.patch Add src/paged-kv-manager.{h,cpp} (vLLM-parity block manager, CPU foundation) + CMake; no behavior change builds; unit-tested separately under ../paged/
0002 0002-paged-kv-storage.patch Shared block-pool KV tensor + set_rows-by-slot writes, behind LLAMA_KV_PAGED builds; write/gather round-trip
0003 0003-paged-gather-read.patch build_attn_paged gather-read in llama-graph.cpp Gate 0: token-identical greedy gen, single + multi-seq
0004 0004-paged-ondemand-alloc.patch On-demand block allocation via PagedKVManager max concurrent seqs before OOM
0005 0005-paged-continuous-batching.patch Block-granular admit/evict in the server slot path tok/s vs concurrency, mixed-length
0006 0006-paged-prefix-caching.patch Block-hash cross-request prefix dedup TTFT + memory on shared prefixes

Each row is a separate git commit on the dev branch (below), exported 1:1 as a patch. Default off (LLAMA_KV_PAGED) until Gate 0 (0003) is green, so partial series never changes stock behavior.

Regen workflow (the anti-drift recipe)

# 1. check out the exact pin into a dev tree
git -C /tmp clone https://github.com/ggml-org/llama.cpp llama-dev && cd /tmp/llama-dev
git checkout <LLAMA_VERSION from ../Makefile>
git checkout -b paged

# 2. apply the current series (each becomes a commit), or develop the next patch
git am /path/to/backend/cpp/llama-cpp/patches/00*.patch     # or `git apply` + commit per patch

# 3. iterate a phase as ONE commit, then export the whole series 1:1
git format-patch <LLAMA_VERSION>..paged -o /path/to/backend/cpp/llama-cpp/patches/ --zero-commit -N

# 4. on a pin bump: rebase `paged` onto the new pin; only conflicting patches need edits; re-export.

Build integration

../Makefile's llama.cpp: target runs, after git checkout -b build $(LLAMA_VERSION):

for p in $(CURRENT_MAKEFILE_DIR)/patches/0*.patch; do git apply --verbose "$p"; done

All variants (avx/avx2/avx512/cuda/…) copy the patched llama.cpp/ tree, so the series ships everywhere.

Status

  • 0001 vendor manager — DONE. Applies clean to the pin; builds into libllama.
  • 0002 block placement — DONE + VERIFIED. Built llama-simple at the pin; greedy generation is token-identical stock vs LLAMA_KV_PAGED=1 (Qwen3-0.6B), paged branch confirmed firing.
  • 0003 gather-read — DONE + VERIFIED (Gate 0 green). Implemented in the additive form (ADDITIVE_DESIGN.md): all logic in new src/paged-attn.{h,cpp} (a llm_graph_input_i gather-index subclass + the K/V/mask gather), hooked by one line in build_attn + two thin accessors on llama_kv_cache_context + 1 CMake line (216 insertions; no edit to llm_graph_input_attn_kv or llama-graph.h). Greedy generation is token-identical stock vs LLAMA_KV_PAGED=1 (Qwen3-0.6B, 9/9 across 3 prompts × {32,96,128} tokens), with n_gather=71 < n_kv=256 confirming real compaction. Patch: 0003-paged-gather-read-env-LLAMA_KV_PAGED.patch.
    • Key correctness finding: get_gather_idxs must emit cells sorted by token position. The CPU flash-attn online softmax reduces cells in physical-array order and is FP-order-sensitive, so 0002's scattered placement alone (full-window read, no gather) diverges from stock once a sequence crosses the first 16-cell block. The position-sorted gather reproduces stock's exact reduction order -> bit- identical, not merely mathematically equivalent. So 0002 is the placement substrate; 0003 is what makes paged placement token-identical under flash-attn.
  • 00040006 follow.

Honest parity note (important)

This series delivers the paged-attention engine (capacity + scheduling + prefix sharing). It does not by itself reach vLLM throughput parity, because the measured prefill bottleneck is the FP4 MoE GEMM kernel (Lever 3: mul_mat_q<MXFP4> ~22 TFLOP/s, ~27× behind vLLM) — a per-token compute gap that paging does not touch. Paged attention closes the concurrency/memory gap (more sequences, prefix reuse); the prefill/throughput gap additionally needs the tcgen05/CUTLASS grouped-GEMM (deferred, upstream-grade, no shortcut — see ../paged/UPSTREAM_GGML_ISSUE.md and DGX_BLACKWELL_PLAN.md). So full vLLM parity = this series AND the kernel; neither alone suffices.