AutoRT: the Next Generation of Antares.

AutoRT for Device Runtime:

AutoRT is a compiler solution that helps runtime users to invent, benchmark and optimize operators for Pytorch using your own accelerators.

Recommended Docker Image for AutoRT Setup:

• Docker Image for CUDA: nvidia/cuda:12.8.0-devel-ubuntu24.04
• Docker Image for ROCM: rocm/dev-ubuntu-24.04:7.2.4
• ..

Tutorial of AutoRT:

>>> Agentic Step-1:Please read this SKILL and learn by yourself:
https://raw.githubusercontent.com/microsoft/antares/refs/heads/latest/SKILLS.md>>> Agentic Step-2:Regardless of whether the current environment meets the requirements,
please follow AutoRT kernel examples to write a similar command that computes: output_1d = torch.sum(input_2d, dim=-1)
All syntax for kernel body follows CUDA / HIP C++ 17 standard. No need for deep API consult.

Quick Start:

autort -n hello_world_example --source='@DEF_FUNC: input:float32[B, M] -> output:float32[B, M]@DEF_BIND: ~B~:1, ~%~:1024void main() { if (int(blockIdx.x) == 0 && int(threadIdx.x) == 0) printf("(autort) Hello World!\n");}'

For Earlier Manual Doc (deprecated), please check: Manual and Legacy.

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