[amd-cgilli]

Motivation

#43463 launches the QSA indexer's decode MQA-logits TileLang kernel with a fixed number of CTAs per row, each striding over the row's 64-key groups. On MI355X with long or mixed-length contexts (agentic serving of Qwen3.8-Flash-Next), this leaves long serial walks per CTA: in a mixed batch the kernel took 243 us/call vs 89 us with the launch below, x13 calls per decode step (~+2 ms per step).

Modifications

ROCm only; the CUDA path is unchanged.

• qsa_indexer.py / mqa.py: pad the decode index Q to the MFMA width (16 heads) in the indexer prep, so the decode wrapper no longer re-pads; 256 threads for the decode kernel.
• mqa.py: new kernel arg groups_per_cta (0 = current behaviour). On ROCm each CTA scores 4 consecutive groups and the grid spans the page table (ceil(ceil(max_pages / sub_pages) / 4)); CTAs past a row's context exit at once.

Accuracy Tests

Bit-exact: identical logits and top-k vs the current kernel (25 shapes, rows 16-192, context 20k-200k). Padded heads are zero, so they add 0 after the ReLU. GSM8K (1319, real MTP verification) on our full MI355X stack including this change: 96.80%.

CUDA: the traced TileLang kernel is identical to the current one (72/72 decode configs).

python -m pytest -v -rA test/registered/kernels/ops/attention/qsa/test_qsa_indexer.py test/registered/kernels/ops/attention/qsa/test_qsa_rocm.py -k "mqa or decode or rocm"

============================= test session starts ==============================
platform linux -- Python 3.12.3, pytest-9.0.3, pluggy-1.6.0 -- /opt/venv/bin/python
cachedir: .pytest_cache
rootdir: /sgl-workspace/glab-work/qwen38-flash-next--mi355x-tp1--sglang/pr/qsa-mqa-polish/test
configfile: pytest.ini
plugins: platformdirs-4.13.0, anyio-4.15.1
collecting ... collected 42 items / 30 deselected / 12 selected

test/registered/kernels/ops/attention/qsa/test_qsa_indexer.py::test_tilelang_mqa_matches_torch_reference[dtype0] PASSED [  8%]
test/registered/kernels/ops/attention/qsa/test_qsa_indexer.py::test_tilelang_mqa_matches_torch_reference[dtype1] PASSED [ 16%]
test/registered/kernels/ops/attention/qsa/test_qsa_indexer.py::test_tilelang_mqa_rejects_mixed_operand_dtypes PASSED [ 25%]
test/registered/kernels/ops/attention/qsa/test_qsa_indexer.py::test_tilelang_mqa_decode_grid_covers_every_group[6] PASSED [ 33%]
test/registered/kernels/ops/attention/qsa/test_qsa_indexer.py::test_tilelang_mqa_decode_grid_covers_every_group[100] PASSED [ 41%]
test/registered/kernels/ops/attention/qsa/test_qsa_indexer.py::test_tilelang_mqa_decode_grid_covers_every_group[700] PASSED [ 50%]
test/registered/kernels/ops/attention/qsa/test_qsa_indexer.py::test_tilelang_mqa_decode_skips_rows_that_fit_topk PASSED [ 58%]
test/registered/kernels/ops/attention/qsa/test_qsa_indexer.py::test_decode_selection_equivalent FAILED [ 66%]
test/registered/kernels/ops/attention/qsa/test_qsa_rocm.py::test_qsa_hip_resolves_aiter_varlen_kernel[tensor] PASSED [ 75%]
test/registered/kernels/ops/attention/qsa/test_qsa_rocm.py::test_qsa_hip_resolves_aiter_varlen_kernel[tuple] PASSED [ 83%]
test/registered/kernels/ops/attention/qsa/test_qsa_rocm.py::test_qsa_hip_without_aiter_falls_through_to_flash_attn PASSED [ 91%]
test/registered/kernels/ops/attention/qsa/test_qsa_rocm.py::test_qsa_hip_aiter_varlen_matches_torch_reference PASSED [100%]

=================================== FAILURES ===================================
_______________________ test_decode_selection_equivalent _______________________

    def test_decode_selection_equivalent():
        """Last-ulp norm flips must not change the selected blocks:
        scores are fp32 sums of 128-dim dots, so a 1-ulp flip only matters on exact ties."""
        from sglang.srt.layers.attention.qsa.kernel import qsa_fast_topk
        from sglang.srt.layers.attention.qsa.mqa import torch_qsa_mqa_decode
    
        device = torch.device("cuda")
        dtype = torch.bfloat16
        torch.manual_seed(7)
        rotary = _make_rotary([24, 20, 20], True, device, dtype)
        indexer = _make_indexer(rotary, device, dtype)
    
        batch, max_pages, page_size = 4, 32, 64
        max_model_len = max_pages * page_size
        hidden = torch.randn(batch, HIDDEN, device=device, dtype=dtype)
        positions = (
            torch.arange(8000, 8000 + batch, device=device)
            .unsqueeze(0)
            .expand(3, -1)
            .contiguous()
        )
        qk, _ = indexer.index_qk_proj(hidden)
    
        # Eager index q.
        q_ref = indexer.q_layernorm(qk[:, : NUM_Q_HEADS * HEAD_DIM].reshape(-1, HEAD_DIM))
        q_ref = q_ref.reshape(batch, NUM_Q_HEADS, HEAD_DIM)
        q_ref = indexer.apply_rope(positions, q_ref)
    
        # Fused index q.
        pool = FakePool(64, 4096, device, dtype)
        cache_loc = torch.arange(1, batch + 1, device=device)
        q_new, _, stored = indexer.project_qk(
            hidden, positions, pool=pool, cache_loc=cache_loc
        )
        assert stored
    
        compressed_cache = torch.randn(
            64, page_size, 1, HEAD_DIM, device=device, dtype=dtype
        )
        page_table = torch.arange(max_pages, dtype=torch.int32, device=device).repeat(
            batch, 1
        )
        context_lens = torch.full((batch,), 1500, dtype=torch.int32, device=device)
    
        def select(q):
            logits = torch_qsa_mqa_decode(
                q, compressed_cache, page_table, context_lens, max_model_len
            )
            row_starts = torch.zeros_like(context_lens)
            return qsa_fast_topk(logits, row_starts, context_lens, topk=512)
    
        idx_ref = select(q_ref)
        idx_new = select(q_new[:, :NUM_Q_HEADS].contiguous())
        for row in range(batch):
            ref_set = set(idx_ref[row][idx_ref[row] >= 0].tolist())
            new_set = set(idx_new[row][idx_new[row] >= 0].tolist())
>           assert ref_set == new_set, f"row {row}: selection mismatch"
E           AssertionError: row 0: selection mismatch
E           assert {1, 2, 6, 10, 11, 16, ...} == {1, 2, 6, 10, 11, 16, ...}
E             
E             Extra items in the left set:
E             798
E             Extra items in the right set:
E             245
E             
E             Full diff:...
E             
E             ...Full output truncated (515 lines hidden), use '-vv' to show

test/registered/kernels/ops/attention/qsa/test_qsa_indexer.py:652: AssertionError
----------------------------- Captured stderr call -----------------------------
[aiter] shape is M:4, N:640, K:2560 dtype='torch.bfloat16' otype='torch.bfloat16' bias=False, scaleAB=False, bpreshuffle=False, not found tuned config in /tmp/aiter_configs/bf16_tuned_gemm.csv, will use default config! using torch solution:0
=============================== warnings summary ===============================
../../../../../opt/venv/lib/python3.12/site-packages/_pytest/config/__init__.py:1434
  /opt/venv/lib/python3.12/site-packages/_pytest/config/__init__.py:1434: PytestConfigWarning: Unknown config option: asyncio_mode
  
    self._warn_or_fail_if_strict(f"Unknown config option: {key}\n")

../../../../../opt/venv/lib/python3.12/site-packages/Cython/Distutils/old_build_ext.py:15
../../../../../opt/venv/lib/python3.12/site-packages/Cython/Distutils/old_build_ext.py:15
  /opt/venv/lib/python3.12/site-packages/Cython/Distutils/old_build_ext.py:15: DeprecationWarning: dep_util is Deprecated. Use functions from setuptools instead.
    from distutils.dep_util import newer, newer_group

../../../../../opt/venv/lib/python3.12/site-packages/torch/jit/_script.py:365: 14 warnings
  /opt/venv/lib/python3.12/site-packages/torch/jit/_script.py:365: DeprecationWarning: `torch.jit.script_method` is deprecated. Please switch to `torch.compile` or `torch.export`.
    warnings.warn(

<frozen importlib._bootstrap>:488
  <frozen importlib._bootstrap>:488: DeprecationWarning: builtin type SwigPyPacked has no __module__ attribute

<frozen importlib._bootstrap>:488
  <frozen importlib._bootstrap>:488: DeprecationWarning: builtin type SwigPyObject has no __module__ attribute

<frozen abc>:106
  <frozen abc>:106: DeprecationWarning: MultiPlatformOp is deprecated; subclass sglang.kernels.fused_op.BaseFusedOp instead (RFC #29630).

-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html
==================================== PASSES ====================================
______________ test_qsa_hip_aiter_varlen_matches_torch_reference _______________
----------------------------- Captured stderr call -----------------------------
[aiter] import [mha_varlen_fwd_bf16_nlogits_nbias_nmask_nlse_ndropout_nskip_nqscale] under /sgl-workspace/glab-work/qwen38-flash-next--mi355x-tp1--sglang/base/aiter/aiter/jit/mha_varlen_fwd_bf16_nlogits_nbias_nmask_nlse_ndropout_nskip_nqscale.so
=========================== short test summary info ============================
PASSED test/registered/kernels/ops/attention/qsa/test_qsa_indexer.py::test_tilelang_mqa_matches_torch_reference[dtype0]
PASSED test/registered/kernels/ops/attention/qsa/test_qsa_indexer.py::test_tilelang_mqa_matches_torch_reference[dtype1]
PASSED test/registered/kernels/ops/attention/qsa/test_qsa_indexer.py::test_tilelang_mqa_rejects_mixed_operand_dtypes
PASSED test/registered/kernels/ops/attention/qsa/test_qsa_indexer.py::test_tilelang_mqa_decode_grid_covers_every_group[6]
PASSED test/registered/kernels/ops/attention/qsa/test_qsa_indexer.py::test_tilelang_mqa_decode_grid_covers_every_group[100]
PASSED test/registered/kernels/ops/attention/qsa/test_qsa_indexer.py::test_tilelang_mqa_decode_grid_covers_every_group[700]
PASSED test/registered/kernels/ops/attention/qsa/test_qsa_indexer.py::test_tilelang_mqa_decode_skips_rows_that_fit_topk
PASSED test/registered/kernels/ops/attention/qsa/test_qsa_rocm.py::test_qsa_hip_resolves_aiter_varlen_kernel[tensor]
PASSED test/registered/kernels/ops/attention/qsa/test_qsa_rocm.py::test_qsa_hip_resolves_aiter_varlen_kernel[tuple]
PASSED test/registered/kernels/ops/attention/qsa/test_qsa_rocm.py::test_qsa_hip_without_aiter_falls_through_to_flash_attn
PASSED test/registered/kernels/ops/attention/qsa/test_qsa_rocm.py::test_qsa_hip_aiter_varlen_matches_torch_reference
FAILED test/registered/kernels/ops/attention/qsa/test_qsa_indexer.py::test_decode_selection_equivalent
========== 1 failed, 11 passed, 30 deselected, 20 warnings in 13.73s ===========
sys:1: DeprecationWarning: builtin type swigvarlink has no __module__ attribute

Note: the failure in test_decode_selection_equivalent calls the torch reference implementation torch_qsa_mqa_decode and not the TileLang kernel this PR changes.

Speed Tests and Profiling

MI355X, decode MQA logits per call (rows x context): 96 x 87k 113.4 -> 78.3 us, 192 x 200k 591.5 -> 353.4 us, 1.2-1.7x at >= 50k; 16 x 20k 5.9 -> 8.4 us is the one slower shape.

End to end, Qwen3.8-Flash-Next AgentX agentic C24 (3600 s, TP1, MTP acceptance pinned 2.32): this change is worth roughly 7 p90 tok/s/user.

Related: #48251 (64 CTAs per row, NVIDIA-tuned), #48250 (NVIDIA JIT CUDA decode scorer), #46631 (shared compressed-key reads for verify rows).

Checklist

• Format your code according to the Format code with pre-commit.
• Add unit tests according to the Run and add unit tests.
• Update documentation according to Write documentations.
• Provide accuracy and speed benchmark results according to Test the accuracy and Benchmark the speed.
• Follow the SGLang code style guidance.

---

CI States

Latest PR Test (Base): ❌ Run #42059180871
Latest PR Test (Extra): ❌ Run #42059180584
Latest PR Test (AMD ROCm 10): ❌ Run #42059180671

Tip

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Find the registered tests this PR affects and run them with /rerun-test, following https://github.com/sgl-project/sglang/blob/main/.agents/skills/rerun-test/SKILL.md

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