feat(dcp): add selected-record sparse CKV decode

[FujitsuPolycom]

Summary

Add an experimental selected-record CKV decode path for B12X sparse MLA under DCP, including per-sequence MTP union/deduplication, pooled C1-C8 workspaces, target/draft execution-lane isolation, direct/CE transport selection, and one-shot S1/S2/S3 CE lookahead.

For eligible decode batches, vLLM finalizes top-K, builds one stable union per destination/request across MTP rows, converts logical tokens to owner-local paged-cache slots, exchanges only selected native records, patches the current token, and executes the existing local-head B12X attention plan.

Dependencies and stack note

This PR is stacked on:

• vLLM allocator/indexer #159
• vLLM native CKV prefetch #160
• Sparkinfer direct exchange #64
• Sparkinfer CE exchange #65

GitHub temporarily shows the vLLM prerequisite commits in this diff. The sparse-decode review range starts at cd0b0324fd; execution-lane and static integration fixes are folded into this draft because they protect state introduced here.

Current eligibility

Feature-gated and default off. The physically validated path requires:

• DCP2-8
• non-DBO workspace
• aligned local heads
• nvfp4_ds_mla
• native 432-byte records
• BF16 RoPE (KV_FP8_ROPE=0)
• bounded uniform decode rows and required metadata
• graph capacity for configured request count times MTP rows

Request/pool/shape mismatch falls back to stock DCP. Strict CE initialization fails loudly; automatic mode may use direct.

Validation

Validated on ai01: ASUS WRX90E-SAGE SE, Threadripper PRO 9965WX, 128 GiB RAM, 4x RTX PRO 6000 Blackwell 96 GB at 400 W, TP4/DCP4/MTP3.

Daily profile:

• max model length 300,000
• max sequences 8; batch 2,048; graph 32
• 302,047 reported KV tokens
• coding median 105.2 tok/s over five temperature-zero runs
• cold prefill 3,326 / 3,139 / 2,966 / 2,719 / 2,356 tok/s at 8K / 32K / 64K / 128K / 256K
• deterministic repeats matched near 8K, 64K, and 128K

Matched 90K coding:

• DCP4/MTP3 sparse off: 82.9 tok/s
• DCP4/MTP3 CE sparse: 99.2 tok/s (+19.6%)
• unchanged 302,080-token capacity

FP8-RoPE validation (368-byte records, TP4/DCP4/MTP3):

• 32K C1: DCP1 91.5, DCP4 stock 71.7, DCP4 sparse 92.4 tok/s
• 64K C1: DCP1 91.9, DCP4 stock 67.2, DCP4 sparse 93.1 tok/s
• 16K C4: DCP1 224.0, DCP4 stock 102.3, DCP4 sparse 141.6 tok/s
• all 27 scored samples were inference-JIT-free and accepted on attempt one
• final 300K integration profile reported 304,863 KV tokens

One-shot S1/S2/S3 improved the 64K+ prefill geometric mean by 8.5% within its layered capacity. Larger batches retain per-layer exchange.

Tests/checks:

• vLLM policy/workspace: 160 passed, 18 skipped
• mixed allocator: 3 passed
• mypy Python 3.10-3.13 and static checks passed
• four-GPU target/MTP graph capture and API/transport smoke passed

Design

GLM-5.2 Sparse CKV under Decode Context Parallelism

This remains experimental because TP6/TP8, DCP6/DCP8, switched fabrics, and prolonged C3-C8 stress are not yet physically validated. It is ready for code review, but should not be merged or enabled by default until the current GG DCP performance regression is resolved.

Credits

The design originates from Koush's sparse-CKV, shared-layer lookahead, and per-sequence MTP-deduplication work. It builds on Luke Alonso's B12X/Sparkinfer infrastructure and local-inference-lab's GLM integration.

Implementation, tests, benchmarking, and documentation were developed with OpenAI Codex assistance and manually reviewed and GPU-validated.

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Review details

⚙️ Run configuration

Configuration used: Organization UI

Review profile: CHILL

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Run ID: b5b51122-8fd0-48a8-8c6c-d7b5a14c20ba

📥 Commits

Reviewing files that changed from the base of the PR and between 6a2edcf and 3f7b34c.

📒 Files selected for processing (23)

• tests/model_executor/layers/test_sparse_attn_indexer_b12x.py
• tests/models/test_dcp_shard_draft_defaults.py
• tests/v1/attention/test_b12x_ckv_prefetch_policy.py
• tests/v1/attention/test_b12x_mla_dcp_workspace.py
• tests/v1/attention/test_b12x_mla_fp8_rope_writer.py
• tests/v1/attention/test_b12x_sparse_ckv_decode_policy.py
• tests/v1/attention/test_indexer_dcp_localize.py
• tests/v1/core/test_kv_cache_utils.py
• tests/v1/core/test_prefix_caching.py
• tests/v1/worker/test_attn_utils.py
• tests/v1/worker/test_gpu_block_table.py
• vllm/distributed/parallel_state.py
• vllm/envs.py
• vllm/model_executor/layers/attention/mla_attention.py
• vllm/model_executor/layers/sparse_attn_indexer.py
• vllm/model_executor/models/deepseek_v2.py
• vllm/v1/attention/backends/mla/b12x_mla_sparse.py
• vllm/v1/attention/backends/mla/b12x_sparse_ckv_decode.py
• vllm/v1/attention/backends/mla/b12x_sparse_ckv_union.cu
• vllm/v1/attention/backends/mla/indexer.py
• vllm/v1/core/block_pool.py
• vllm/v1/core/kv_cache_coordinator.py
• vllm/v1/core/kv_cache_utils.py

✨ Finishing Touches

🧪 Generate unit tests (beta)

• Create PR with unit tests

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[voipmonitor]

Current GG/v20 revalidation (2026-07-22)

The updated stack was revalidated at the current PR heads, including compact 368-byte FP8-RoPE records:

• vLLM feat(dcp): add native depth-N CKV prefetch #160: b95b8e45
• vLLM feat(dcp): add selected-record sparse CKV decode #161: 5ae1516c
• Sparkinfer [eldritch] Allow GLM TP6 head66 in B12X sparse MLA #64: 0bf4e34a
• Sparkinfer dspark: cap TileLang threads at 128 for <=16 heads/rank (TP=4) #65: b17cab90

Configuration: GLM-5.2 MXFP8/NVFP4/NF3 hybrid, TP4/DCP4/MTP3, nvfp4_ds_mla, FP8 RoPE, max sequences 8, graph 32, and the hybrid DCP policy (a2a up to 16 rows, ag_rs above it). Both arms used NCCL for TP all-reduce to match the original validation profile. Model loading was completed before measurement, and the two rounds swapped GPU groups.

Runtime activation was verified from the server log:

• PCIeSelectedRecordCopyExchange
• record_bytes=368, prefetch depth 3
• one bulk S1/S2/S3 exchange
• transient full-CKV prefill gather

All benchmark cells completed with zero request errors. More than 400 focused vLLM/Sparkinfer CPU and GPU tests passed, including DCP2/DCP4 and 368/432-byte transport coverage.

Sustained decode results

Test	Context	Current sparse-off	Selected-record sparse	Delta
C1	32K	93.60	92.94	-0.70%
C1	64K	93.80	93.51	-0.31%
C1	128K	91.11	90.48	-0.70%
C4	16K	212.77	200.63	-5.71%
C4	32K	208.34	197.84	-5.04%
C4	64K	205.51	194.08	-5.56%

The first swapped round had noisier C1 samples but confirmed the same C4 direction: -7.04%, -8.17%, and -10.84% at 16K/32K/64K.

The absolute sparse C1 result reproduces the original result closely (about 92.4/93.1 tok/s at 32K/64K). The previous relative uplift does not reproduce because current GG sparse-off already reaches about 93-94 tok/s through the low-latency Sparkinfer/B12X PCIe DCP pool; the older comparison used a 67-72 tok/s stock DCP baseline. At C4 the current baseline is also substantially faster than the historical baseline.

A separate sparse-off run with production B12X TP all-reduce selected B12X_PCIE_ONESHOT_DMA and measured 97.60/96.57/95.78 tok/s at C1 32K/64K/128K and 213.79/207.67/210.53 tok/s at C4 16K/32K/64K. This was effectively neutral versus NCCL TP all-reduce and does not restore the historical sparse uplift.

Current disposition

Keep this implementation feature-gated and default-off as an experimental/research path. It preserves the selected-record transport, MTP union/deduplication, and prefetch work for future profiling or different fabrics, but it should not be enabled by the release helper or included as a required v20 image patch while it regresses the current optimized DCP path at C4.

[FujitsuPolycom]

Validated on ai01 (4x RTX PRO 6000, TP4/DCP4/MTP3) against the RAM-only LMCache integration. The original failure occurred when a 189,033-token request resumed from a 187,136-token LMCache prefix and B12X returned a valid token-major projection buffer. The previous guard accepted only head-major storage and terminated all workers.

Post-fix reproducer:

• stored prompt: 187,140 tokens
• resumed prompt: 188,778 tokens
• LMCache prefix hit: 187,136 tokens
• grouped DCP load: 256 tokens/rank
• resumed request: 1.106 s, HTTP 200
• service remained healthy

Exact-image unit gate: 30 passed. The projection still requires the expected shape/dtypes and borrowed-storage alias; only the two dense layouts consumed correctly by the existing transpose/copy are accepted.