For the complete documentation index, see llms.txt. Markdown versions of all pages are available by appending .md to any URL (e.g. /max/get-started.md).

Mojo function

fused_silu_fp8_kernel

fused_silu_fp8_kernel[fp8_dtype: DType, scales_dtype: DType, input_dtype: DType, output_layout: TensorLayout, scales_layout: TensorLayout, input_layout: TensorLayout, offsets_layout: TensorLayout, num_threads: Int, num_sms: Int, group_size: Int = 128](output_tensor: TileTensor[fp8_dtype, output_layout, MutExternalOrigin], scales_tensor: TileTensor[scales_dtype, scales_layout, MutExternalOrigin], input_tensor: TileTensor[input_dtype, input_layout, ImmutExternalOrigin], row_offsets: TileTensor[DType.uint32, offsets_layout, ImmutExternalOrigin])

This kernel performs the SILU operation for all the MLPs in the EP MoE module. We need to manually implement the kernel here is because after the EP dispatch phase, the actual number of received tokens is not known to the host. This kernel will read the row offsets to determine the actual number of received tokens in the input tensor.

Once the SILU operation is performed, the output tensor will be quantized to the FP8 format. The scales tensor will be stored in a transposed way.

Arguments: output_tensor: The output tensor to store the result. scales_tensor: The tensor to store the scales. input_tensor: The input tensor to perform the SILU operation. row_offsets: The row offsets to determine the actual number of received tokens.