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The estimate_matmul functionality in Triton relies rather heavily on the underlying stats of the GPU. On CUDA platforms, this functionality is realised by calling nvidia-smi and then parsing the results. I see that this code is still present in this fork of Triton:
@joerowell We can add it later after we merge this fork with upstream.
For gemm tuning, we have a dedicated script to tune gemm kernels. You can refer to this README for more info and let me know if you have more questions.
Problem Description
The
estimate_matmul
functionality in Triton relies rather heavily on the underlying stats of the GPU. On CUDA platforms, this functionality is realised by callingnvidia-smi
and then parsing the results. I see that this code is still present in this fork of Triton:triton/python/triton/testing.py
Line 12 in 35edd6a
Would it be possible to get support added for
rocm-smi
here instead? This makes autotuning Triton kernels for GEMM etc much easier.Operating System
CPU
GPU
AMD Instinct MI300X
ROCm Version
ROCm 6.0.0
ROCm Component
No response
Steps to Reproduce
No response
(Optional for Linux users) Output of /opt/rocm/bin/rocminfo --support
No response
Additional Information
No response
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