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#!/bin/bash
#SBATCH --job-name=all_reduce_bench-a100-n4
#SBATCH --partition=gpu_p5
#SBATCH --constraint=a100
#SBATCH --nodes=4
#SBATCH --ntasks-per-node=1 # crucial - only 1 task per dist per node!
#SBATCH --cpus-per-task=64 # number of cores per tasks
#SBATCH --hint=nomultithread # we get physical cores not logical
#SBATCH --gres=gpu:8 # number of gpus
#SBATCH --time 0:05:00 # maximum execution time (HH:MM:SS)
#SBATCH --output=%x-%j.out # output file name
#SBATCH --account=six@a100
source $six_ALL_CCFRWORK/code/tr11-176B-ml/bigscience/train/tr11-176B-ml/start-tr11-176B-ml
export NNODES=$SLURM_NNODES
export GPUS_PER_NODE=8
export NCCL_DEBUG=info
export LOG_FILE=all_reduce_bench-a100-$NNODES.txt
export MASTER_ADDR=$(scontrol show hostnames $SLURM_JOB_NODELIST | head -n 1)
srun --jobid $SLURM_JOBID bash -c 'python -m torch.distributed.launch --nnodes $NNODES --nproc_per_node $GPUS_PER_NODE --node_rank $SLURM_PROCID --master_addr $MASTER_ADDR --master_port 12345 all_reduce_bench.py' 2>&1 | tee $LOG_FILE
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