[Attention][MLA] Add GLM-5.2 TurboQuant sparse backend with DCP/MTP

[ketor]

Summary

• extends the TurboQuant MLA work in [Attention][MLA] Add Triton-fused TurboQuant decode backend #41803 with the GLM-5.2 sparse MLA path on current main
• adds packed 4-bit latent KV storage, fused sparse decode, sparse prefill, and GLM-4 MoE MTP plumbing
• adds DCP/MTP/PP correctness fixes, canonical DCP interleave handling, CUDA-graph-safe workspaces, and asynchronous MTP handoff

Validation

• end-to-end cold and hot inference workloads completed successfully
• hot-cache median TTFT improved by 31x and median end-to-end latency improved by 8.26x in the validation workload
• all requests completed without connector, engine, worker, or completion errors
• changed-file pre-commit suite passes, including Ruff, mypy, configuration validation, and forbidden CUDA API checks

Relationship to existing work

#41803 provides the dense Triton-fused TurboQuant MLA decode foundation. This PR adds GLM-5.2 sparse attention, DCP/MTP/PP integration, and the end-to-end sparse prefill/decode path. Opened as draft because the change should likely be split for review.

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[claude]

Claude Code Review

This pull request is from a fork — automated review is disabled. A repository maintainer can comment @claude review to run a one-time review.

[LucasWilkinson]

Im not convinced this worth the complexity given HiSparse should soon be able to alleviate alot of the GPU kv-cache pressure

[mergify]

This pull request has merge conflicts that must be resolved before it can be
merged. Please rebase the PR, @ketor.

https://docs.github.com/en/pull-requests/collaborating-with-pull-requests/working-with-forks/syncing-a-fork