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Mojo struct
DistributedEPDispatch
struct DistributedEPDispatch
Registers the mo.distributed.ep.dispatch graph op with the graph compiler.
Implemented traits
Methods
execute
static def execute[dispatch_dtype: DType, hidden_size: Int, top_k: Int, n_experts: Int, max_token_per_rank: Int, n_gpus_per_node: Int, n_nodes: Int, fused_shared_expert: Bool, //, target: StringSlice[ImmStaticOrigin], _trace_name: StringSlice[ImmStaticOrigin]](output_tokens: VariadicTensors[IOSpec[_, _].Output, static_specs=output_tokens.static_specs], row_offsets: VariadicTensors[IOSpec[_, _].Output, static_specs=row_offsets.static_specs], expert_ids: VariadicTensors[IOSpec[_, _].Output, static_specs=expert_ids.static_specs], src_info: VariadicTensors[IOSpec[_, _].Output, static_specs=src_info.static_specs], input_tokens: VariadicTensors[IOSpec[_, _].Input, static_specs=input_tokens.static_specs], topk_ids: VariadicTensors[IOSpec[_, _].Input, static_specs=topk_ids.static_specs], send_ptrs: VariadicTensors[IOSpec[_, _].Input, static_specs=send_ptrs.static_specs], recv_ptrs: VariadicTensors[IOSpec[_, _].Input, static_specs=recv_ptrs.static_specs], recv_count_ptrs: VariadicTensors[IOSpec[_, _].Input, static_specs=recv_count_ptrs.static_specs], atomic_counters: VariadicTensors[IOSpec[_, _].MutableInput, static_specs=atomic_counters.static_specs], dev_ctxs: DeviceContextArray)
Multi-device fused Expert Parallelism BF16 dispatch.
Parameters:
- dispatch_dtype (
DType):DTypeused for token dispatch to experts (inferred). - hidden_size (
Int): Size of the model's hidden dimension (inferred). - top_k (
Int): Number of experts each token is routed to (inferred). - n_experts (
Int): Total number of experts across all GPUs (inferred). - max_token_per_rank (
Int): Maximum number of tokens per GPU (inferred). - n_gpus_per_node (
Int): Number of GPUs per node (inferred). - n_nodes (
Int): Number of physical nodes (inferred). - fused_shared_expert (
Bool): Whether a shared expert is fused into the dispatch kernel (inferred). - target (
StringSlice[ImmStaticOrigin]): Compile-time device target. - _trace_name (
StringSlice[ImmStaticOrigin]): Trace label for this op.
Args:
- output_tokens (
VariadicTensors[IOSpec[_, _].Output, static_specs=output_tokens.static_specs]): Output variadic tensors storing the dispatched tokens, one per device. - row_offsets (
VariadicTensors[IOSpec[_, _].Output, static_specs=row_offsets.static_specs]): Output variadic tensors storing the row offsets for the received tokens, one per device. - expert_ids (
VariadicTensors[IOSpec[_, _].Output, static_specs=expert_ids.static_specs]): Output variadic tensors storing the expert ID for each received token, one per device. - src_info (
VariadicTensors[IOSpec[_, _].Output, static_specs=src_info.static_specs]): Output variadic tensors recording the originating rank and token index for each received token, one per device. - input_tokens (
VariadicTensors[IOSpec[_, _].Input, static_specs=input_tokens.static_specs]): Input variadic tensors of tokens to dispatch, one per device. - topk_ids (
VariadicTensors[IOSpec[_, _].Input, static_specs=topk_ids.static_specs]): Input variadic tensors of top-k expert IDs per token, one per device. - send_ptrs (
VariadicTensors[IOSpec[_, _].Input, static_specs=send_ptrs.static_specs]): Send buffer pointers for the dispatch phase, one per device. - recv_ptrs (
VariadicTensors[IOSpec[_, _].Input, static_specs=recv_ptrs.static_specs]): Receive buffer pointers for the dispatch phase, one per device. - recv_count_ptrs (
VariadicTensors[IOSpec[_, _].Input, static_specs=recv_count_ptrs.static_specs]): Receive count buffer pointers tracking tokens received per expert, one per device. - atomic_counters (
VariadicTensors[IOSpec[_, _].MutableInput, static_specs=atomic_counters.static_specs]): Atomic counters coordinating work across thread blocks, one per device. - dev_ctxs (
DeviceContextArray): List of GPU device contexts, one per device.
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