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Overiew of the optional performance features that are yet to be upstr…
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# Overview of the optional performance features uinque to https://github.com/ROCm/vllm | ||
## Multi-GPU torchrun | ||
On ROCm the default multi GPU executor is `torchrun` as opposed to `ray` on NVIDIA | ||
This can be overriden by the `--worker-use-ray` flag to vllm or its benchmarks | ||
To utilize torchran parallelism, the run command should be midified from | ||
`python <command>` | ||
to | ||
`torchrun --standalone --nnodes=1 --nproc-per-node=<workd-size> <command>` | ||
## Triton attention | ||
The default attention function on ROCm is using triton attention kernel. To fallback to the https://github.com/ROCm/flash-attention implementation set up the following environment symbol: | ||
`VLLM_USE_FLASH_ATTN_TRITON=False` | ||
## Tunable ops | ||
Pytorch tunable ops are supported. | ||
Define the following environment symbol: `PYTORCH_TUNABLEOP_ENABLED=1` in order to enable both the runtime tuning and the subsequent use of tuned results. To only use the tuned results without tuning any newly encountered shapes, also define `PYTORCH_TUNABLEOP_TUNING=1` |