[karverma-amd]

Overview

Re-enable DeepSeek-V4.1 prefix-cache sliding-window bounded replay on gfx950. Decoder replay is a separate path and is already enabled by #59039 when cache_config.swa_bounded_replay is on. This PR only restores the prefix-cache path from #57906.

The AITER sparse MLA path consumes slot IDs that _compute_swa_indices_and_lens_kernel has already clamped to replay_start. The ROCm force-off in attention.py stays in place for every ROCm GPU other than gfx950, including gfx942. On gfx950 the sliding-window cache follows cache_config.swa_bounded_replay.

Claims

• On gfx950, prefix-cache SWA replay is no longer forced off. The flag still defaults on, and --no-swa-bounded-replay still disables it. Other ROCm GPUs stay on the existing force-off path.
• On our best MI355X config, end-to-end throughput is 13.5% higher at concurrency 128 and 12% higher at concurrency 256.
• GSM8K and RULER NIAH are unchanged between stock and replay.

Validation

GSM8K, 1,319 questions, 5-shot, temperature 0, all questions in flight:

Arm	Accuracy
Stock, replay off	0.904
Replay on	0.902

RULER niah_single_1 (single needle, word key, number value, repeated haystack), 131,072 tokens, 5 samples, temperature 0:

Arm	Score
Stock, replay off	1.0
Replay on	1.0

Prefix-cache sweep across the prefill-chunk boundary. Each point primes eight DP replicas with a shared prefix plus 128 new tokens, then repeats the query. vllm:prefix_cache_hits_total is the hit signal. Every second-wave request completed on both arms, with no GPU fault.

Prefix tokens	Stock hit tokens	Replay hit tokens
1,920	15,360	15,360
2,048	16,256	16,384
2,176	17,280	17,408
4,096	32,640	32,768

A separate single-request check on an otherwise stock nightly (00b6c4c, chunk 2048, DEP8, one request, token-id prompts) shows the config-flag A/B. Warmed requests:

Shape	Stock	Replay
8k TTFT	492 ms	316 ms
32k TTFT	1.84 s	1.23 s
128k TTFT, 1k output	7.42 s	4.83 s
128k prefill	17,667 tok/s	27,136 tok/s
128k decode	52 tok/s	49–62 tok/s

Decode does not change. A decode step is already one new token inside the window.

CI does not have this MI355X checkpoint, so Buildkite does not cover this path.

Details

DeepSeek-V4.1-Flash has 40 layers. KV is written at layers 2, 8, 14, and 20. The sliding window is 128 tokens. After layer 20 has written KV for a token, layers 21–39 only need the last 128 tokens. That trim is decoder replay (#59039). It is built from cache_config.swa_bounded_replay and is already active on ROCm when the flag is left on.

This change is the prefix-cache half. On a prefix-cache hit, the SWA cache replays from replay_start instead of storing the full sliding window. gfx950 can take that path because AITER sparse MLA uses the already-clamped slot list. The old force-off assumed an extra clamp inside the FlashInfer and FlashMLA prefill kernels, which this path does not use. gfx942 cannot take AITER sparse MLA, so it stays forced off.

To enable it on a gfx950 recipe that sets VLLM_NO_SWA_BOUNDED_REPLAY=1, remove that setting. Keep model runner V2 and breakable CUDA graphs. A 4096-token prefill chunk is above the 768-token replay trim threshold, so it uses the trimmed graph.

ROCm consumers

CDNA4 keeps prefix-cache SWA replay. Both ROCm consumers clamp to replay_start:

• Opt-in AITER sparse MLA reads slot ids from _compute_swa_indices_and_lens_kernel, which clamps start_pos.
• The default Triton gather path clamps the prefill gather length in ComputePrefillMetadataKernel and clamps swa_start again in combine_topk_swa_indices.

Every other ROCm GPU, including CDNA3, stays forced off. get_cdna_version() != 4 is the gate.
Limitations:

• Measured on gfx950 with the AITER Triton sparse MLA path.
• The flag defaults on, so gfx950 behavior changes for every DeepSeek-V4.1 server that does not pass --no-swa-bounded-replay.

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[frida-andersson]

The 32k/128k check is a single request, and the logged decoder replay behavior is already enabled by #59039. This PR re-enables the prefix-cache replay path, could you update the description to make that distinction clear?

Please also sweep with prefix caching on across the prefill-chunk boundary, and add RULER NIAH or GPQA Diamond for the same replay-on/off comparison

[karverma-amd]

Thanks @frida-andersson — agreed. I updated the implementation to keep this prefix-cache path disabled on gfx942 and only enable it on gfx950, where the AITER sparse MLA path consumes slot IDs already clamped to replay_start. Decoder replay is independent and was already enabled by #59039; this PR only re-enables bounded SWA replay for prefix-cache hits.

I also ran a stock/replay prefix-cache sweep across 1,920, 2,048, 2,176, and 4,096-token prefixes. Eight DP replicas were primed per point and all cached-prefix queries hit successfully on both arms.

[simondanielsson]

Thanks for the fix!

Suggestion: Would be great with a reproducer that shows that indeed prefix caching yields accurate output.

Question: How come we could enable this now on gfx950?

Nit: can we also update the title accordingly?

[karverma-amd]

@okorzh-amd -

The TTFT and concurrency numbers in the description compare the flag off with the flag on, so they include decoder replay from #59039. I reran the same nightly with the flag on for both arms, on the default Triton gather path (VLLM_ROCM_USE_AITER_TRITON_SPARSE_MLA unset). Warmed single-request TTFT is 0.317 s vs 0.317 s at 8k and 1.25 s vs 1.28 s at 32k. This PR does not move that number. It only enables the prefix-cache SWA path on gfx950. I will update the description so those tables are not attributed to this change.

The comment now names both consumers. Opt-in AITER sparse MLA reads slot ids from _compute_swa_indices_and_lens_kernel, which clamps start_pos. The default Triton gather path clamps the prefill gather length in ComputePrefillMetadataKernel and clamps swa_start again in combine_topk_swa_indices. GSM8K, 1,319 questions, 5-shot, temperature 0, that env unset, flag on: stock 0.912 , this PR 0.907

@simondanielsson -

Prefix-cache check on gfx950, flag on. A prompt states that the secret vault code is 427193 and asks for that number. Eight DP replicas were used.

The same 3,027-token prompt was sent twice. The second wave hit 23,552 cached tokens and all 8 replies contained 427193.

A second check stores a 2,176-token prefix, then reuses only the first 1,800 tokens, which is 248 tokens before the 2,048-token chunk boundary, followed by a 27-token question. That hit 14,336 cached tokens and all 8 replies contained 427193.

gfx950 can take this path because both ROCm consumers already clamp to replay_start. Opt-in AITER sparse MLA reads slot ids from _compute_swa_indices_and_lens_kernel. The default Triton gather path clamps the prefill gather length in ComputePrefillMetadataKernel and clamps swa_start again in combine_topk_swa_indices. gfx942 stays off.

[Fangzhou-Ai]

Hi @karverma-amd can you give more details on "On our best MI355X config, end-to-end throughput is 13.5% higher at concurrency 128 and 12% higher at concurrency 256." e.g. what's the server configs here?

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[karverma-amd]

/ci run

[github-actions]

✅ Triggered Buildkite CI #98727 for commit 40f19c8725a7.

ℹ️ This PR is 1 commit behind upstream main. Merged upstream main into this branch as 40f19c8725a7 before starting CI. Pull the branch before pushing more changes.

[simondanielsson]

I'm still thinking if we should add a unit test to make sure prefix caching works with bounded replay.

Nothing in the CI had to change when we disabled prefix caching, and nothing breaks now when we enabled it. So in the future if we accidentally break this feature the CI will not catch it

[mergify]

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[karverma-amd]

I'm still thinking if we should add a unit test to make sure prefix caching works with bounded replay.

Nothing in the CI had to change when we disabled prefix caching, and nothing breaks now when we enabled it. So in the future if we accidentally break this feature the CI will not catch it

@simondanielsson : A unit test is the right catch for this. test_prefix_replay.py already checks that a bounded-replay sliding-window spec makes a prefix hit recompute the window, but it builds that spec by hand. Nothing was reading the spec the attention layer actually publishes, so CI stayed green when the window was forced back into the prefix cache and again when CDNA4 turned replay back on.

test_prefix_cache_replays_the_swa_window builds the real layer with prefix caching left on and checks the published spec. It passed, 4 of 4, and is on the branch as 3b1029d.

Non-ROCm and ROCm CDNA4 keep the window out of the prefix cache and set prefix_replay_tokens to the window.
ROCm CDNA3, and a disabled flag, put the window back into the prefix cache.

[karverma-amd]

/ci run

[github-actions]

✅ Triggered Buildkite CI #98734 for commit fc403952dd33.

ℹ️ This PR is 2 commits behind upstream main. Merged upstream main into this branch as fc403952dd33 before starting CI. Pull the branch before pushing more changes.

[peymanr]

PR Pundit review

(Testing PR Pundit Code Review agent. Not all comments may be relevant. This is a one-time automated pass: please address what is useful, no need to request a re-review. A quick reply per point (useful or not, and why) helps us calibrate the agent. Reach out to @peymanr for suggestions and feedback.)

#		Finding	Where
1	🟠	Importing attention.py with no GPU raises RuntimeError: this PR added top-level ROCm platform import	vllm/models/deepseek_v41/attention.py:66
2	🟠	Stale comment in amd/model.py wrongly claims ROCm always forces per-layer SWA replay off	vllm/models/deepseek_v41/amd/model.py:578

1. 🟠 Should fix: Importing attention.py with no GPU raises RuntimeError: this PR added top-level ROCm platform import

vllm/models/deepseek_v41/attention.py:66

The new module-level from vllm.platforms.rocm import get_cdna_version in the shared vllm/models/deepseek_v41/attention.py (also imported by nvidia/model.py, nvidia/flashmla.py and nvidia/flashinfer_sparse.py) runs ROCm platform import side effects on every platform. On load, vllm.platforms.rocm tries amdsmi, vllm._C and vllm._rocm_C, logging a warning for each failed import. It then evaluates _GCN_ARCH = _get_gcn_arch(), which falls back to torch.cuda.get_device_properties("cuda") without catching errors. With no GPU visible, importing attention.py now fails with RuntimeError: No CUDA GPUs are available; at the base it imported cleanly. Import get_cdna_version lazily inside the current_platform.is_rocm() branch, or move the CDNA4 gate into the ROCm subclass in amd/rocm.py.

Who is affected: Anyone who imports the DeepSeek-V4.1 attention module (NVIDIA/CUDA builds, or any process with no visible GPU, such as CPU-side tests or tooling).

Checked against the code by an independent pass.

Related past reviews: #49839 on tests/kernels/core/test_fused_quant_layernorm.py, #47896 on tests/kernels/turboquant/test_flydsl_turboquant_decode.py, #49839 on tests/kernels/core/test_layernorm.py, #43615 on vllm/_aiter_ops.py, #43615 on vllm/envs.py, #50654 on tests/models/kimi_k3/test_amd_kda_decode.py, #22527 on vllm/model_executor/layers/quantization/petit.py, #22976 on vllm/distributed/kv_transfer/kv_connector/v1/nixl_connector.py, #43835 on vllm/v1/attention/backends/triton_attn.py, #12591 on vllm/platforms/interface.py

2. 🟠 Should fix: Stale comment in amd/model.py wrongly claims ROCm always forces per-layer SWA replay off

vllm/models/deepseek_v41/amd/model.py:578

The comment above the AMD decoder-replay gate (# Config flag is the switch: ROCm forces swa_cache_layer.bounded_replay off.) is stale after this PR. DeepseekV4Attention now only disables swa_bounded_replay on ROCm when get_cdna_version() != 4, so on CDNA4 (gfx950) the per-layer swa_cache_layer.bounded_replay stays on. Update the comment to say ROCm forces it off only on non-CDNA4 archs. The AMD gate keying decoder replay on the config flag alone is pre-existing and intentional, not changed by this PR.

Who is affected: Readers and maintainers of vllm/models/deepseek_v41/amd/model.py; there is no runtime effect.

Checked against the code by an independent pass.

_{Shared from a pilot of PR Pundit, an agentic code reviewer that builds and tests the change and reads the project's past reviews. Reviewed at 40f19c87; findings checked and posted by @peymanr; points already raised on this PR are left out.}

[karverma-amd]

/ci retry

[github-actions]

✅ Queued 4 failed job(s) for retry in Buildkite CI #98734.

[peymanr]

PR Pundit review

(Testing PR Pundit Code Review agent. Not all comments may be relevant. This is a one-time automated pass: please address what is useful, no need to request a re-review. A quick reply per point (useful or not, and why) helps us calibrate the agent. Reach out to @peymanr for suggestions and feedback.)

#		Finding	Where
1	🟠	Non-CDNA4 users see no reason replay was disabled: this PR replaced the #57906 explanation with a one-line arch statement	vllm/models/deepseek_v41/attention.py:554-563
2	🟠	New test never exercises the gfx950 kernel path: this PR adds only a spec-flag unit test for the enabled replay	tests/v1/attention/test_deepseek_v4_swa_visible.py:924

1. 🟠 Should fix: Non-CDNA4 users see no reason replay was disabled: this PR replaced the #57906 explanation with a one-line arch statement

vllm/models/deepseek_v41/attention.py:554-563

The new warning Prefix-cache SWA replay is only enabled on ROCm CDNA4 gives no reason why swa_bounded_replay stays off on CDNA3 and other ROCm architectures. Restoring the #57906 wording is not the fix: it says the replay_start clamp exists only in the FlashInfer/FlashMLA prefill kernels, but the shared sparse SWA builder clamps gather_lens by replay_start (sparse_swa.py:379-381), and the old text would contradict this PR enabling replay on gfx950. A short comment next to the get_cdna_version() != 4 gate, saying what has not been validated on non-CDNA4 archs, would keep the reason for maintainers.

Who is affected: Users on ROCm GPUs other than gfx950 (e.g. MI300/gfx942) who enable swa_bounded_replay and see the override warning without a reason.

Checked against the code by an independent pass.

Related past reviews: #51714 on tests/kernels/attention/test_rocm_triton_attn_dsv4.py, #4545 on tests/core/block/e2e/test_correctness_sliding_window.py

2. 🟠 Should fix: New test never exercises the gfx950 kernel path: this PR adds only a spec-flag unit test for the enabled replay

tests/v1/attention/test_deepseek_v4_swa_visible.py:924

The new test_prefix_cache_replays_the_swa_window only checks the KV-cache spec flags (bounded_replay, prefix_cacheable, prefix_replay_tokens) with is_rocm and get_cdna_version monkeypatched. It never runs a gfx950 prefix hit with a nonzero replay_start through the AITER sparse-MLA path. The window clamp this PR relies on is already covered at the metadata level: the shared builder in sparse_swa.py clamps prefill and decode indices to replay_start, the ROCm builder builds its ragged prefill indices from those, and test_builder_replay_start_bounds_prefill_window_and_gather and test_dsv41_gfx942_decode_meta.py test this. An end-to-end gfx950 prefix-hit forward test would still add confidence. The skipif(not torch.cuda.is_available()) matches the rest of the file and is needed, because layer construction fails without a device.

Who is affected: Only test coverage: there is no end-to-end check of SWA bounded replay on ROCm CDNA4 (gfx950), where this PR enables it.

Checked against the code by an independent pass.

Related past reviews: #51714 on tests/kernels/attention/test_rocm_triton_attn_dsv4.py, #43718 on tests/models/test_deepseek_v4_rocm_multistream.py, #54485 on vllm/v1/attention/backends/triton_attn.py, #34931 on tests/v1/kv_connector/unit/test_example_connector.py

_{Shared from a pilot of PR Pundit, an agentic code reviewer that builds and tests the change and reads the project's past reviews. Reviewed at fc403952; findings checked and posted by @peymanr; points already raised on this PR are left out.}

[karverma-amd]

@peymanr : 1. Fixed. get_cdna_version is imported only inside the is_rocm() branch, so attention.py no longer loads the ROCm platform on CUDA or when no GPU is visible.
2. Fixed. The amd/model.py comment now says ROCm forces swa_cache_layer.bounded_replay off only when the CDNA version is not 4.
3. Fixed. The gate comment says CDNA3 and other ROCm archs are not validated. The warning stays the CDNA4-only line; the old #57906 wording would contradict the shared replay_start clamp.
4. The new test checks the KV spec this PR publishes (bounded_replay, prefix_cacheable, prefix_replay_tokens) for CUDA, CDNA4, and CDNA3. The replay_start clamp is already covered by test_builder_replay_start_bounds_prefill_window_and_gather. A gfx950 AITER forward is not added here.

[karverma-amd]

/ci run

[github-actions]

✅ Triggered Buildkite CI #98778 for commit 03eda184c9d3.

ℹ️ This PR is 7 commits behind upstream main. Merged upstream main into this branch as 03eda184c9d3 before starting CI. Pull the branch before pushing more changes.

[karverma-amd]

/ci run

[github-actions]

✅ Triggered Buildkite CI #98796 for commit 89b5ee77348b.

ℹ️ This PR is 2 commits behind upstream main. Merged upstream main into this branch as 89b5ee77348b before starting CI. Pull the branch before pushing more changes.

[simondanielsson]

LGTM

[simondanielsson]

Nit: this can be much shorter:

# TODO: validate prefix caching on CDNA 3