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Mojo struct

Struct_ep_combine_wait

struct Struct_ep_combine_wait

Registers the ep.combine_wait graph op with the graph compiler.

Implemented traits

AnyType, Deinitable, Movable

Methods

execute

static def execute[combine_dtype: DType, router_weights_dtype: DType, //, hidden_size: Int, top_k: Int, n_experts: Int, max_token_per_rank: Int, n_gpus_per_node: Int, n_nodes: Int, has_epilogue_fusion: Bool, target: StringSpan[ImmStaticOrigin]](output_tokens: ManagedTensorSlice[IOSpec[_, _].FusedOutput, static_spec=output_tokens.static_spec], atomic_counters: ManagedTensorSlice[IOSpec[_, _].MutableInput, static_spec=atomic_counters.static_spec], recv_ptrs: ManagedTensorSlice[IOSpec[_, _].Input, static_spec=recv_ptrs.static_spec], recv_count_ptrs: ManagedTensorSlice[IOSpec[_, _].Input, static_spec=recv_count_ptrs.static_spec], router_weights: ManagedTensorSlice[IOSpec[_, _].Input, static_spec=router_weights.static_spec], context: DeviceContext)

Execute the Expert Parallelism combine completion kernel.

Waits for incoming expert outputs and computes the weighted sum of routed expert outputs for each token using the router weights.

Parameters:

• ​combine_dtype (DType): DType used for the token payload during the combine phase (inferred).
• ​router_weights_dtype (DType): DType of the router weights tensor used to compute the weighted sum (inferred).
• ​hidden_size (Int): Size of the model's hidden dimension.
• ​top_k (Int): Number of experts each token is routed to.
• ​n_experts (Int): Total number of experts across all GPUs.
• ​max_token_per_rank (Int): Maximum number of tokens any GPU can receive.
• ​n_gpus_per_node (Int): Number of GPUs per physical node.
• ​n_nodes (Int): Number of physical nodes in the deployment.
• ​has_epilogue_fusion (Bool): Whether to apply an elementwise epilogue function after computing the combined output.
• ​target (StringSpan[ImmStaticOrigin]): Compile-time device target.

Args:

• ​output_tokens (ManagedTensorSlice[IOSpec[_, _].FusedOutput, static_spec=output_tokens.static_spec]): Fused output tensor storing the weighted sum of routed expert outputs for each token. Shape [num_tokens, hidden_size].
• ​atomic_counters (ManagedTensorSlice[IOSpec[_, _].MutableInput, static_spec=atomic_counters.static_spec]): Atomic counters coordinating work across thread blocks during the combine phase.
• ​recv_ptrs (ManagedTensorSlice[IOSpec[_, _].Input, static_spec=recv_ptrs.static_spec]): Receive buffer pointers for the combine phase.
• ​recv_count_ptrs (ManagedTensorSlice[IOSpec[_, _].Input, static_spec=recv_count_ptrs.static_spec]): Receive count buffer pointers tracking the number of tokens received per expert.
• ​router_weights (ManagedTensorSlice[IOSpec[_, _].Input, static_spec=router_weights.static_spec]): Router weights for the current device used to compute the weighted sum of expert outputs. Shape [num_tokens, top_k].
• ​context (DeviceContext): GPU device context for the current device.