{"record":{"id":"9de6ab54ee468682","repo":"sgl-project/sglang","slug":"flashattention-combine-kernel-cannot-be-implemente","errorCode":null,"errorMessage":"FlashAttention combine kernel cannot be implemented with given parameters","messagePattern":"FlashAttention combine kernel cannot be implemented with given parameters","errorType":"error_code","errorClass":"RuntimeError","httpStatus":null,"severity":"critical","filePath":"python/sglang/kernels/ops/attention/flash_attn/cute/interface.py","lineNumber":2341,"sourceCode":"    fa_combine = FlashAttentionForwardCombine(\n        dtype=dtype,\n        dtype_partial=dtype_partial,\n        head_dim=head_dim,\n        tile_m=tile_m,\n        k_block_size=k_block_size,\n        log_max_splits=log_max_splits,\n        use_pdl=use_pdl,\n    )\n    if not fa_combine.can_implement(\n        dtype,\n        dtype_partial,\n        head_dim,\n        tile_m,\n        k_block_size,\n        log_max_splits,\n        num_threads=256,\n    ):\n        raise RuntimeError(\n            \"FlashAttention combine kernel cannot be implemented with given parameters\"\n        )\n\n    if has_cu_seqlens:\n        # Varlen: (num_splits, total_q, nheads, headdim)\n        num_splits, total_q, nheads = sym(), sym(), sym()\n        mO_partial = fake_tensor(\n            dtype_partial, (num_splits, total_q, nheads, head_dim), divisibility=div\n        )\n        mLSE_partial = fake_tensor(\n            Float32, (num_splits, total_q, nheads), divisibility=1, leading_dim=1\n        )\n        mO = fake_tensor(dtype, (total_q, nheads, head_dim), divisibility=div)\n        mLSE = (\n            fake_tensor(Float32, (total_q, nheads), divisibility=1, leading_dim=0)\n            if has_lse\n            else None\n        )","sourceCodeStart":2323,"sourceCodeEnd":2359,"githubUrl":"https://github.com/sgl-project/sglang/blob/0132848349585cfe6aae51c4941cbae872505f8a/python/sglang/kernels/ops/attention/flash_attn/cute/interface.py#L2323-L2359","documentation":"The FlashAttention split-KV combine kernel could not be instantiated because the chosen tile/parameter combination (head_dim, tile_m, k_block_size, log_max_splits, num_threads=256) falls outside the implementable envelope. This is an internal configuration constraint check in _compile_fwd_combine, reached via _flash_attn_fwd_combine.","triggerScenarios":"The varlen forward runs with an excessive number of KV splits (large log_max_splits) or an unusual head_dim / tile_m combination such that a single thread block cannot cover the combine work with 256 threads; typically triggered by very long sequences with small batch and many splits, or non-standard head dims.","commonSituations":"Extremely long context lengths causing num_splits beyond what the combine kernel supports; custom head_dim configurations; downstream of automatic split-kv heuristics picking an oversized log_max_splits.","solutions":["Report the exact head_dim, seqlen, and split configuration to maintainers — this is a kernel-coverage bug, not user error in most cases.","Reduce sequence length or increase batch so fewer KV splits are needed.","If you control the wrapper, cap num_splits / lower log_max_splits so the combine kernel fits the envelope."],"exampleFix":null,"handlingStrategy":"fallback","validationCode":null,"typeGuard":null,"tryCatchPattern":"try:\n    _flash_attn_fwd_combine(...)\nexcept RuntimeError as e:\n    if \"combine kernel cannot be implemented\" in str(e):\n        # fall back to a kernel/config with fewer KV splits\n        run_with_fewer_splits()\n    else:\n        raise","preventionTips":["Avoid extreme seqlen/batch ratios that force huge split counts.","Pin known-good sglang versions for long-context workloads; this check indicates a coverage gap."],"tags":["cuda","attention","split-kv","kernel-config"],"backgroundTag":"kernel-parameter-constraint-violation","analyzedSha":"0132848349585cfe6aae51c4941cbae872505f8a","analyzedAt":"2026-08-28T05:10:05.995Z","schemaVersion":2},"datasetVersion":"2026-08-28T06:17:29.519Z"}