triton-ascend-example-double-kernel

To call two Triton Ascend kernels sequentially in a forward pass, you allocate an intermediate buffer and launch stage1 and stage2 kernels in order. This staged computation pattern ensures correct data passing between sequential Triton Ascend kernel executions within the forward function.

Staged computation with multiple kernels is needed for fusion operators requiring intermediate results and pipelined tasks. It solves the challenge of multi-step computations on Atlas Ascend A2/A3 hardware by dividing complex forward operations into sequential Triton kernel executions with intermediate buffer allocation.

Yes, you can use Triton Ascend with Torch for multi-step operator fusion on Atlas A2 and A3 hardware. The implementation requires explicit frontmatter configuration with backend ascend, dsl triton_ascend, and framework torch to execute staged kernel computations correctly.

To allocate intermediate buffers for two-stage Triton kernel execution, follow the standard pattern of creating a buffer between stage1 and stage2 kernel launches. This intermediate buffer holds the output from the first kernel and passes it as input to the second kernel for sequential data processing.

Sequential two-kernel execution in Triton Ascend is limited to Atlas Ascend A2/A3 hardware and requires the Torch framework. It specifically addresses staged computation needs for fusion operators and may not suit single-kernel operations or alternative hardware platforms outside the Ascend ecosystem.

Yes, the Triton Ascend two-kernel pattern supports pipelined task optimization by dividing operations into stage1 and stage2. This staged computation approach allows developers to optimize multi-step fusion operators by explicitly managing intermediate data flow between sequential kernel launches.