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Mojo function

mha_sm100_depth512_dispatch

def mha_sm100_depth512_dispatch[q_type: DType, KVType: MHAOperand, MaskType: MHAMask, output_type: DType, MaxPromptLenType: OptionallyStaticInt, PartitionType: MHAPartitionScheme, //, config: MHAConfig[config.dtype], group: Int, ragged: Bool, _is_cache_length_accurate: Bool](output: DeviceBuffer[output_type], q_arg: Pointer[Scalar[q_type], _safe=False], k: KVType, v: KVType, num_rows_q: Int, mask: MaskType, valid_length: Pointer[UInt32, _safe=False], max_prompt_len_arg: MaxPromptLenType, max_cache_valid_length_arg: Int, scale: Float32, kv_input_row_offsets: OptionalReg[TileTensor[DType.uint32, Layout[*?, *?], ImmutAnyOrigin]], batch_size_arg: Int, partition: PartitionType, ctx: DeviceContext)

Dispatches the pair-CTA SM100 depth=256/512 MHA prefill kernel.

Builds the Depth512SM100Config, constructs TMA tile descriptors for the Q, K, V, and output operands, creates a TransientScheduler with pair_cta=True, and enqueues the SM100MHADepth512 kernel with cluster_dim=(2, 1, 1) so both CTAs in a cluster derive the same tile index from block_idx.x >> 1. Only prefill is supported; decoding is rejected at compile time.

Parameters:

q_type (DType): The query tensor element type (inferred).
KVType (MHAOperand): The paged KV cache operand type providing the tile factory and page size (inferred).
MaskType (MHAMask): The attention mask type applied to the scores (inferred).
output_type (DType): The output buffer element type (inferred).
MaxPromptLenType (OptionallyStaticInt): The maximum prompt length as a static or runtime value (inferred).
PartitionType (MHAPartitionScheme): The KV cache partition scheme (inferred).
config (MHAConfig[config.dtype]): The MHA configuration with head count, depth, and swizzle mode used to build the Depth512SM100Config.
group (Int): Number of query heads per KV head for grouped-query attention.
ragged (Bool): Whether the batch uses ragged sequence lengths with a non-null valid_length pointer.
_is_cache_length_accurate (Bool): Whether the per-batch cache length values are exact.

Args:

output (DeviceBuffer[output_type]): Device buffer that receives the attention output.
q_arg (Pointer[Scalar[q_type], _safe=False]): Pointer to the query tensor data.
k (KVType): Key operand providing the paged KV cache tile factory.
v (KVType): Value operand providing the paged KV cache tile factory.
num_rows_q (Int): Number of query rows to process.
mask (MaskType): Causal or padding mask applied to the attention scores.
valid_length (Pointer[UInt32, _safe=False]): Per-batch pointer to valid cache lengths (used when ragged is true).
max_prompt_len_arg (MaxPromptLenType): Maximum prompt length, static or runtime.
max_cache_valid_length_arg (Int): Maximum valid cache length across the batch.
scale (Float32): Scaling factor applied to the QK dot product.
kv_input_row_offsets (OptionalReg[TileTensor[DType.uint32, Layout[*?, *?], ImmutAnyOrigin]]): Optional ragged row-offset tensor for KV input rows.
batch_size_arg (Int): Number of sequences in the batch.
partition (PartitionType): Partition scheme for the KV cache.
ctx (DeviceContext): Device context used to create TMA descriptors and enqueue the kernel.