TensorRT-LLMs/examples/llm-api/llm_mgmn_llm_distributed.sh
JunyiXu-nv c329f5f78b
[https://nvbugs/5569754][chore] Adjust max batch size to prevent OOM (#8876)
Signed-off-by: Junyi Xu <219237550+JunyiXu-nv@users.noreply.github.com>
2025-11-04 18:34:26 +01:00

57 lines
2.1 KiB
Bash

#!/bin/bash
#SBATCH -A <account> # parameter
#SBATCH -p <partition> # parameter
#SBATCH -t 01:00:00
#SBATCH -N 1
#SBATCH --ntasks-per-node=2
#SBATCH -o logs/llmapi-distributed.out
#SBATCH -e logs/llmapi-distributed.err
#SBATCH -J llmapi-distributed-task
### :section Slurm
### :title Run LLM-API with pytorch backend on Slurm
### :order 0
# NOTE, this feature is experimental and may not work on all systems.
# The trtllm-llmapi-launch is a script that launches the LLM-API code on
# Slurm-like systems, and can support multi-node and multi-GPU setups.
# Note that, the number of MPI processes should be the same as the model world
# size. e.g. For tensor_parallel_size=16, you may use 2 nodes with 8 gpus for
# each, or 4 nodes with 4 gpus for each or other combinations.
# This docker image should have tensorrt_llm installed, or you need to install
# it in the task.
# The following variables are expected to be set in the environment:
# You can set them via --export in the srun/sbatch command.
# CONTAINER_IMAGE: the docker image to use, you'd better install tensorrt_llm in it, or install it in the task.
# MOUNT_DIR: the directory to mount in the container
# MOUNT_DEST: the destination directory in the container
# WORKDIR: the working directory in the container
# SOURCE_ROOT: the path to the TensorRT LLM source
# PROLOGUE: the prologue to run before the script
# LOCAL_MODEL: the local model directory to use, NOTE: downloading from HF is
# not supported in Slurm mode, you need to download the model and put it in
# the LOCAL_MODEL directory.
# Adjust the paths to run
export script=$SOURCE_ROOT/examples/llm-api/quickstart_advanced.py
# Just launch the PyTorch example with trtllm-llmapi-launch command.
srun -l \
--container-image=${CONTAINER_IMAGE} \
--container-mounts=${MOUNT_DIR}:${MOUNT_DEST} \
--container-workdir=${WORKDIR} \
--export=ALL \
--mpi=pmix \
bash -c "
$PROLOGUE
export PATH=$PATH:~/.local/bin
trtllm-llmapi-launch python3 $script \
--model_dir $LOCAL_MODEL \
--prompt 'Hello, how are you?' \
--tp_size 2 \
--max_batch_size 256
"