In CP=8 + NSA-shared-KV + HiCache disagg-prefill, cache-hit prefill produced
incoherent decode output. Cold prefill on CP was correct; pure CP without
HiCache was correct. The bug lived at the HiCache load_cp / device-alloc
interface.
Root cause: cache_controller.load_cp called the plain
mem_pool_device_allocator.alloc(logical_len), which returns logical pages
with no CP owner-pattern preservation. Cold prefill instead uses
alloc_extend_compute_owner with a zigzag owner pattern from
build_in_seq_page_compute_owners. The saved CpHiCacheNodeMetadata.owned_positions
records WHICH POSITIONS in the write-time alloc were owned by this rank. At
load time, those same positions are applied to a new alloc whose per-position
owner pattern is arbitrary -- each rank loads its host bytes into physical
slots whose corresponding logical page is owned by a DIFFERENT rank.
Attention's materialize_shared_token_kv_buffer reads from the owner's
physical slot, which was never loaded. Result: garbage.
Fix:
- CpHiCacheNodeMetadata gains two required fields: page_owners (int8 per
logical page, identical on all CP ranks) and page_size. __post_init__
validates; split() bisects page_owners by page index with a page-alignment
check.
- _write_cp derives page_owners from device_indices (page-first slot of each
page -> logical page id -> layout.owner_for_logical_pages) and stores in
both metadata-construction sites (zero-owned and normal).
- New CPSharedPagedTokenToKVPoolAllocator.alloc_pages_with_owners() reuses
_select_compute_owner_pages (with its tai-kernel fast path) and returns
page-contiguous token locs whose per-page owner sequence equals the input.
- load_cp now concats page_owners across nodes_to_load and calls
alloc_pages_with_owners. On None (lane exhausted) the caller hits the
retry-with-eviction path; further failure returns None and degrades to
cache miss. No silent fallback to plain alloc -- that recreated the bug.
- load_back retry path now calls _evict_for_compute_owner_lanes (module-top
import) instead of plain evict(); this targets the deficit lane and gives
the next alloc attempt a chance to satisfy it.
- envs import moved to module top in cache_controller.py per code-review
feedback. Removed an over-defensive owned_check.all().item() in load_cp
that would have re-introduced the host-sync anti-pattern 97a9f850c
removed -- the invariant is already guaranteed by alloc_pages_with_owners.
Tests: 40 existing CpHiCacheNodeMetadata constructions migrated to pass the
new required fields. 9 new metadata tests (validators + split page-alignment).
10 new allocator tests in test_alloc_pages_with_owners.py covering input-order
preservation, lane exhaustion, release_pages fallback, debug-mode invariant.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
CP shared KV now avoids the PyTorch sort/search remap for the single-request current-only path by deriving compact rows from page-level inverse mapping. The same change keeps sort NVTX attribution gated and splits high-frequency MoE sort markers behind a separate env var so profiling does not perturb normal runs.
Decode-side disaggregation prealloc also avoids rebuilding large token index tensors and records finer allocation timing, while compute-owner allocation/free tests cover the shared-KV page-lane behavior.
Constraint: The runtime tree used for validation is the remote /sgl-workspace/sglang-tai mount, which is not itself a Git repository, so these tracked files were synchronized into the local repo before commit.
Rejected: Keep torch.sort/searchsorted for current remap | it emits ATen/CCCL radixSortKVInPlace kernels in the attention hot path.
Rejected: Enable MoE sort NVTX under the generic sort env | the MoE preprocess sort is too frequent and can make profiling look like a hang.
Confidence: medium
Scope-risk: moderate
Directive: Do not reintroduce token-level torch.sort/searchsorted in CP shared-KV current remap without profiling the attention hot path under Nsight.
Tested: Remote container py_compile for modified runtime files; git diff --cached --check.
Not-tested: Full multi-node GLM5 PD throughput/profile rerun after the page-inverse current remap.
Shared KV now relies on page-aligned CP metadata and compute-owner page allocation so persistent MLA KV and NSA index shards can be written by the rank that computed them. The compatibility read path keeps the dense full-view contract for existing topk and attention kernels, but removes duplicated prev/next index materialize, adds optional tai materialize integration, and tightens tests/docs around the fallback boundaries.
Constraint: Decode remains non-CP while prefill CP owns the shared-KV changes
Constraint: Existing attention/topk kernels still expect dense full-view KV/index inputs
Rejected: Change attention kernels to read owner-sharded KV directly | larger semantic change reserved for later phases
Rejected: Merge index K/scale storage with MLA KV storage | would couple topk and attention cache lifecycles before materialize overhead is isolated
Confidence: medium
Scope-risk: broad
Directive: Do not remove fallback logging or debug-gated assertions without reproducing long-context chunked/radix-hit paths
Tested: git diff --check --cached
Not-tested: Local pytest/runtime server verification not run in this commit step per current workflow constraints
Prefill CP previously replicated NSA/MLA persistent KV on every CP rank, so CP8 consumed eight copies of KV memory while exposing only one rank of logical cache capacity. This change splits logical KV locs from per-rank physical storage, shards MLA latent KV and NSA index K/scale by deterministic page ownership, and keeps existing NSA attention kernels working through a full-view runtime materialization layer.
Mooncake PD transfer now sends each prefill CP rank's owned physical pages with explicit logical page positions so non-CP decode can reconstruct full-layout KV. The implementation is guarded by an explicit server flag and startup checks, and the design documentation records the implemented scope, debug environment, and Phase 3 boundary.
Constraint: Phase 2 must preserve existing NSA attention/index kernels via runtime full-view materialization
Constraint: Decode side remains non-CP and receives full KV through Mooncake
Rejected: Shard-aware NSA attention in this change | belongs to Phase 3 because it requires distributed topk/softmax/output contracts
Rejected: Request-contiguous CP ownership | unstable under chunked prefill and tied to attention split mode
Confidence: medium
Scope-risk: broad
Directive: Do not enable round-robin CP shared KV without wiring runtime materialization/PD transfer contracts for that split mode
Directive: Keep SGLANG_DEBUG_CP_SHARED_KV disabled for perf measurements; it intentionally enables CUDA-syncing diagnostics
Tested: Remote py_compile for shared-KV touched Python files in g0034 container
Tested: Remote pytest selected cp_shared/shared_kv/nsa suite: 37 passed, 34 deselected
Not-tested: Full GLM5 multi-node throughput/regression run after final doc update
Not-tested: Phase 3 shard-aware runtime, round-robin CP mode, and non-Mooncake PD backends
