docs(deploy): add pinned GLM-5.2 sparse CKV integration release

[FujitsuPolycom]

Summary

Adds a pinned, reproducible deployment package for the validated GLM-5.2 sparse-CKV stack on 4x RTX PRO 6000 Blackwell:

• immutable base-image, vLLM, Sparkinfer, and model pins
• Dockerfile and Compose configuration for TP4/DCP4/MTP3
• fixed 3,426,112,942-byte/GPU KV allocation and 300K model limit
• replicated indexer, native 432-byte CKV depth-3 prefetch, and C1-C8 selected-record decode
• strict copy-engine bulk S1/S2/S3 transport with direct-P2P available as an alternative
• topology/model preflight, deterministic API validator, version lock, and benchmark report

This PR is intentionally based on codex/sparse-ckv-bulk-prefetch: it packages that already-reviewed feature stack and does not add another runtime implementation.

Why this is not duplicate work

No open PR with the same integration/release scope was found in FujitsuPolycom/vllm, local-inference-lab/vllm, or vllm-project/vllm. Existing sparse-CKV PRs implement individual runtime pieces; this PR supplies the pinned build, exact launcher, validation tooling, and measured deployment profile needed to reproduce the combined stack.

Validation

Build-time focused tests in the public-input image:

• Sparkinfer transport/policy: 56 passed, 4 GPU-only skipped
• vLLM attention/workspace policy: 120 passed, 18 skipped
• mixed-DCP KV allocation: 3 passed, 75 deselected

Repository checks:

• applicable pre-commit hooks passed, including Ruff, Markdownlint, typos, mypy, SPDX, and vLLM policy checks
• ShellCheck passed for both shell scripts in the official container
• bash -n, Compose rendering, JSON parsing, and launcher dry-run checks passed
• Dockerfile graph hook is not applicable because docker/Dockerfile is unchanged

Four-GPU release-image gate:

• TP4/DCP4/MTP3, max model length 300,000, batch 2,048, graph 32
• exact NCCL all-reduce command includes --disable-custom-all-reduce
• reported logical KV capacity: 302,047 tokens
• CUDA graph capture completed
• runtime confirmed replicated indexer, C1-C8 selected-record decode, depth 3, and one bulk S1/S2/S3 exchange
• validate-api.py returned sparse-ckv-ready identically twice

Historical model/performance validation for the pinned source stack is documented in RESULTS.md, including a 105.2 tok/s five-run coding median, long-context prefill through 256K, and deterministic output comparisons through 128K.

Boundaries

Validated on one 4-GPU PCIe host with full peer access, NVFP4 CKV, and BF16 RoPE. TP6/TP8, FP8 RoPE, LMCache, calibrated MLA outer scales, and absorbed-QBMM memory work are explicitly out of scope.

AI assistance

OpenAI Codex assisted with implementation, testing, benchmarking, packaging, and documentation. The submitter reviewed the resulting deployment and validated it on the target hardware.

Design document

GLM-5.2 Sparse CKV under Decode Context Parallelism is the canonical architecture, configuration, validation, and upstream-decomposition reference for this PR stack.

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