Description
Horovod is a distributed training framework for TensorFlow.
More information
- Homepage: https://github.com/uber/horovod
Available Versions of Horovod
Version | Module | Available on |
|---|---|---|
0.28.1-foss-2022a-CUDA-11.7.0-TensorFlow-2.11.0 | tools/Horovod/0.28.1-foss-2022a-CUDA-11.7.0-TensorFlow-2.11.0 | Noctua 2 |
This table is generated automatically. If you need other versions please click pc2-support@uni-paderborn.de.
Usage Hints for Horovod
If you need support in using this software or example job scripts please click pc2-support@uni-paderborn.de.
Multi-GPU Training with Horovod and DeepMD
Installation as a Python virtual environment (one time)
We recommend installing Python virtual environments in the group directory on permanent storage of your project (/pc2/groups/[project name]) instead of the home directory or the parallel file system (/scratch/[project name]). Please replace [project name] with the name of your compute time project, i.e. hpc-prf-…
module reset module load toolchain/foss/2022a module load lang/Python/3.10.4-GCCcore-11.3.0 module load system/CUDA/12.6.0 rm -rf venv python3 -m venv venv source /pc2/groups/[project name]/venv_deepmd_horovod/bin/activate pip install cmake pip install mpi4py pip install tensorflow pip install deepmd-kit[gpu,cu12] export HOROVOD_WITH_TENSORFLOW=1 export HOROVOD_WITH_MPI=1 pip install horovod[tensorflow]
Usage in a compute job
#!/bin/bash #SBATCH -N 1 #SBATCH -t 2:00:00 #SBATCH --ntasks-per-node=1 #SBATCH --cpus-per-task=32 #SBATCH --gres=gpu:a100:2 #SBATCH -p gpu #alternatively for testing in small/short jobs, see https://upb-pc2.atlassian.net/wiki/spaces/PC2DOK/pages/1902952/Running+Compute+Jobs#Using-GPUs-for-Development-and-Testing-Purposes ##SBATCH -p dgx ##SBATCH -q devel export OMP_NUM_THREADS=$SLURM_CPUS_PER_TASK export OMP_PLACES=cores export OMP_PROC_BIND=true module reset module load toolchain/foss/2022a module load lang/Python/3.10.4-GCCcore-11.3.0 module load system/CUDA/12.6.0 source /pc2/groups/[project name]/venv_deepmd_horovod/bin/activate srun horovodrun -np 2 dp train input.json