Layer 3 completes the exact Qwen attention state transition
experiment
attention
runtime
kernels
fabric
telemetry
The specialized c16 path completes the exact transition with matching two-rank hashes; three isolated launches ranged from 3.873 to 14.106 ms.
Question. Can one authenticated layer-3 rank-0 slab execute the exact full-attention state transition across TP2?
| setup | |
|---|---|
| nodes | head (gx10-5e36) and peer, one GB10 each |
| kernel | 6.17.0-1031-nvidia-64k, 64 KiB |
| Rocket base | 7c5875cd7b5f1c5f49ca1c99e85366e0d9035496 plus this entry’s commit |
| checkpoint | nvidia/Qwen3.8-Flash-Next-NVFP4 at fc694b54fb0174e0913e6adf86691ef85a4ead47 |
| rank slab | a9fcca026a87ad1285b94feef19448c51b42d97516f16211c61ae4c770c6f0f4 |
| reference | vLLM 8e685d198, Apache-2.0, nvidia/model.py, nvidia/ops/hc.py |
python3 scripts/runtime/qwen38-full-attention-layer-smoke.py \
--rank 0 --m 16 --bootstrap-host 192.168.100.10 --port 18843 \
--timeout-ms 120000 \
--rank-slab-artifact /home/glwillen/calibration/qwen38-rank-slabs-fc694/a9fcca026a87ad1285b94feef19448c51b42d97516f16211c61ae4c770c6f0f4 &
rank0_pid=$!
ssh glwillen@192.168.100.11 \
'cd /home/glwillen/calibration/qwen38-full-attention-layer-live-20260908 && python3 scripts/runtime/qwen38-full-attention-layer-smoke.py --rank 1 --m 16 --bootstrap-host 192.168.100.10 --port 18843 --timeout-ms 120000'
wait "$rank0_pid"{"actual_m":16,"artifact_key":"a9fcca026a87ad1285b94feef19448c51b42d97516f16211c61ae4c770c6f0f4","attention_graph_nodes":20,"composed_stage_total_ms":3.873094,"graph_batch":16,"hc_cold_composed_effective_gbps":18.141375048347168,"hc_cold_fraction_of_238_gbps_rank_local_roof":0.07622426490902172,"hc_graph_nodes":{"combine_m1":8,"combine_m16":8,"combine_m2":8,"combine_m4":8,"combine_m8":8,"mix_m1":8,"mix_m16":8,"mix_m2":8,"mix_m4":8,"mix_m8":8},"hc_hot_cache_effective_gbps":391.07163259695767,"hc_kernel_ms":{"combine_mix_ms":0.03707840144634247,"mix_ms":0.038961601257324216},"hc_logical_bytes":29737088,"intermediate_hashes":{"attention.projected":"b364748b7a55ec690262e80957be2813abf143ae9b32dda9a8d247b1ed065745","attn_hc.block_input":"1e73ecfe195b475473bc3075d39a4f6b0b78f65b8d81a62d507e110d8af0b145","attn_hc.injection":"663ce462e1a00c39f1c20b0db978142e661cf6622285a413e4a6accbad63265f","mlp_hc.block_input":"9b4e058de274eb42d4727131364e0a67ffb648a7ccd16a102fe4099b128e2181","mlp_hc.injection":"b0cadbf2292c28305e5f84b72203efafc6467933a1f98e380695168cad01be93","mlp_hc.updated_hidden":"eb2258968d3d9c3f8f3d59f59206df988f9f9a7b7d8894ca52b33f441c6b10aa","pair_reduce.output":"fda6cb95529c9e918a1677897a4b26768e2bb359d592058a5e148aac1c7a2398"},"layer":3,"layer_stage_label_cardinality":5,"layer_stage_labels":["activation_bind","attn_hc_mix","mlp_hc_combine_mix","pair_reduce","qsa_attention"],"minimum_layer_effective_gbps":90.4690172766269,"minimum_layer_fraction_of_238_gbps_rank_local_roof":0.38012192133036515,"minimum_layer_logical_bytes":350395008,"otel_spans":12,"pair_reduce_otel":{"failures":0,"metrics":1,"spans":1},"qsa_ms":{"attention_ms":0.283323210477829,"output_projection_ms":0.026715201139450074,"score_ms":1.336723232269287,"select_expand_control_ms":0.45767841339111326,"select_expand_ms":0.2922640085220337,"sparse_attention_control_ms":0.5979167938232421,"sparse_attention_ms":0.2566080093383789,"total_ms":1.9123104512691496},"rank":0,"reference_hashes":"exact_match","result":"qwen38_layer3_full_attention_rank0","stage_ms":{"activation_bind":0.038704,"attn_hc_mix":1.324834,"mlp_hc_combine_mix":0.314352,"pair_reduce":0.127425,"qsa_attention":2.067779}}
{"m":16,"output_sha256":"fda6cb95529c9e918a1677897a4b26768e2bb359d592058a5e148aac1c7a2398","pair_reduce_otel":{"failures":0,"metrics":1,"spans":1},"rank":1,"result":"qwen38_layer3_full_attention_rank1_zero_peer"}| stage, fastest launch | latency | unit |
|---|---|---|
| attention HC mix | 1.324834 | ms |
| activation bind | 0.038704 | ms |
| QKV, QSA, output projection | 2.067779 | ms |
| TP2 PairReduce | 0.127425 | ms |
| MLP HC combine and mix | 0.314352 | ms |
| summed transition | 3.873094 | ms |
| proof | value | unit |
|---|---|---|
| minimum logical traffic | 350,395,008 | B |
| rank-local effective bandwidth | 90.469 | GB/s |
| rank-local 238 GB/s traffic roof | 38.012 | % |
| three-run transition range | 3.873 to 14.106 | ms |
| three-run range over mean | 138.99 | % |
| attention graph | 20 | nodes |
| each HC graph | 8 | nodes |
| fixed layer stage labels | 5 | labels |
| isolated launch | transition | minimum traffic rate | rank-local roof |
|---|---|---|---|
| 1 | 4.109077 ms | 85.273 GB/s | 35.829% |
| 2 | 3.873094 ms | 90.469 GB/s | 38.012% |
| completion-fence rerun | 14.106405 ms | 24.839 GB/s | 10.437% |
The first live attempt failed before reduction because cudaHostAlloc returned a base that was not 64 KiB aligned. PairReduce now overallocates by 65,535 B, registers the aligned interior, maps it by offset from the original allocation, and frees the original base.
compute-sanitizer --tool memcheck --error-exitcode 99 \
engines/qwen38-flash-next-nvfp4-2b/build/qwen38-test-hyperconnection
compute-sanitizer --tool memcheck --error-exitcode 99 \
engines/qwen38-flash-next-nvfp4-2b/build/qwen38-test-pair-reduceqwen38_hc buckets=1,2,4,8,16 output_elements=81920 result=match
========= ERROR SUMMARY: 0 errors
qwen38 PairReduce: 5 shapes bit-identical; protocol, drift, and timeout contracts passed
========= ERROR SUMMARY: 0 errors
Verdict. Accepted for the exact synthetic layer-3 rank-0 attention transition with a zero rank-1 partial. This is a kernel composition measurement, not full-model throughput.
Next.
- Replace the synthetic hidden state and zero peer with consecutive outputs from both authenticated rank slabs.
- Profile the 1.325 ms cold attention HC mix and the 2.068 ms attention graph before changing either kernel.
- Bind the pending
updated_hidden,next_block_input, andnext_injectionstate to the layer-3 MoE transition.
Reopen if.
- A CUDA runtime changes mapped interior pointer or CUDA Graph capture semantics on GB10.