[ROCm][Bugfix] Add +256 col guard to preshuffle logits buffer (DSv3.2)

[frida-andersson]

Summary

The AITER gluon preshuffle kernel (_gluon_deepgemm_fp8_paged_mqa_logits_preshuffle) performs unmasked buffer_store writes up to ~190 float32 elements past context_length in each logits row when block_size=64. With the previous exact-size allocation those stores corrupt the logits of the adjacent row, causing wrong top-k selection and degenerate output.

Solution

Introduce _get_paged_logits_buffer which allocates (rows, cols + _PAGED_LOGITS_COL_PADDING) where _PAGED_LOGITS_COL_PADDING=256. The returned tensor is contiguous with stride(0)=cols+256, stride(1)=1. The only consumer, top_k_per_row_decode, already takes logits.stride(0) and logits.stride(1) as explicit arguments and bounds iteration by seq_lens, so the wider row stride is fully transparent.

A fresh allocation is used on every call (rather than caching) so that each HIP graph bucket retains its own stable tensor pointer; caching a shared global that gets reallocated for a larger batch bucket would leave earlier-captured graphs with dangling pointers on replay.

Also fixes device="cuda" → q_fp8.device so TP ranks > 0 allocate on the correct GPU.

Test plan

• GSM8K 5-shot flexible-extract: 0.9416 on TP4 with HIP graphs and --block-size 64 (reference fork: 0.9409)
• Existing behaviour with block_size=1 is unchanged (takes the _stage1 path, _get_paged_logits_buffer is never called)

Dependency: #41760 (correctness fix for DSv3.2 TP4 HIP graphs).

Related

• [ROCm][DSv3.2] Adopt new paged-MQA-logits API + cached logits buffer with defensive padding #40643 (maeehart): companion PR adopting the same padding with buffer caching; currently draft pending further MAF investigation at num_speculative_tokens=2

Co-authored-by: Markus Hartikainen maeehart@users.noreply.github.com

[claude]

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[mergify]

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

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

[gemini-code-assist]

Code Review

This pull request introduces a helper function, _get_paged_logits_buffer, which allocates logits buffers with additional column padding to safely absorb out-of-bounds stores from the AITER preshuffle kernel. It also ensures that fresh tensors are allocated to maintain stability during HIP graph captures. Review feedback points out that the function currently returns the over-allocated tensor's logical shape, which could break downstream code or cause inconsistencies with fallback paths. It is recommended to return a sliced view of the tensor so that the logical dimensions remain correct while the underlying storage retains the necessary padding.

[gemini-code-assist]

The _get_paged_logits_buffer function currently returns a tensor with a logical width of cols + _PAGED_LOGITS_COL_PADDING. This causes rocm_fp8_paged_mqa_logits to return a tensor of shape (rows, max_model_len + 256), which is inconsistent with its fallback path (fp8_paged_mqa_logits_torch) and its docstring (which specifies a shape of [B * next_n, max_model_len]). This inconsistency can lead to errors in downstream code that expects the exact max_model_len width, such as when performing reshapes, views, or assignments to pre-allocated buffers.

To fix this while preserving the padding in the underlying storage for the AITER kernel, you should return a slice of the over-allocated tensor. This maintains the correct logical shape for the caller while keeping the wider stride that protects against out-of-bounds writes. Since top_k_per_row_decode already uses explicit strides, it will continue to function correctly with the sliced view.

def _get_paged_logits_buffer(
    rows: int, cols: int, device: torch.device
) -> torch.Tensor:
    """Return a fresh (rows, cols) float32 tensor pre-filled with -inf.

    Allocating fresh each call is intentional: vLLM captures a separate HIP
    graph for every batch-size bucket.  Each graph records the pointer of the
    tensor that was live at capture time.  If we handed out a cached tensor and
    then reallocated it for a larger bucket, the old graph would replay against
    a freed pointer.  The fresh allocation ensures every captured graph owns
    its own stable buffer for the lifetime of the graph.

    The extra _PAGED_LOGITS_COL_PADDING columns in the underlying storage
    guard against OOB stores from the AITER preshuffle kernel, which does
    unmasked buffer_store up to ~190 elements past context_length.
    top_k_per_row_decode uses explicit strides and seq_lens so the extra
    columns never affect the selected top-k indices.
    """
    return torch.full(
        (rows, cols + _PAGED_LOGITS_COL_PADDING),
        float("-inf"),
        device=device,
        dtype=torch.float32,
    )[:, :cols]

[frida-andersson]

Superseded by #41856 (branch history was corrupted by a shallow-clone amend; this PR cannot be reopened)