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Merge branch 'master' of github.com:setmar/ShallowWaterGPU
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conda_environment_hpc.yml
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conda_environment_hpc.yml
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# Assumes that conda, pip, build-essentials and cuda are installed
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---
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name: ShallowWaterGPU_HPC
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channels:
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- conda-forge
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dependencies:
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- python=3.7
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- numpy
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- mpi4py
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- six
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- pytools
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- netcdf4
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- scipy
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# Install conda environment (one-time operation):
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# $ conda env create -f conda_environment_hpc.yml
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# Activate environment and install the following packages using pip:
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# $ conda activate ShallowWaterGPU
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# - pycuda: $ pip3 install --no-deps -U pycuda
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# on Windows: make sure your visual studio c++ compiler is available in PATH
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# PATH should have something like C:\Program Files (x86)\Microsoft Visual Studio 14.0\VC\bin\
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dgx-2-test.job
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dgx-2-test.job
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#!/bin/bash
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#SBATCH -p dgx2q # partition (GPU queue)
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#SBATCH -N 1 # number of nodes
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#SBATCH -n 4 # number of cores
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#SBATCH -w g001 # DGX-2 node
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#SBATCH --gres=gpu:4 # number of V100's
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#SBATCH --mem 10G # memory pool for all cores
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#SBATCH -t 0-00:10 # time (D-HH:MM)
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#SBATCH -o slurm.%N.%j.out # STDOUT
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#SBATCH -e slurm.%N.%j.err # STDERR
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ulimit -s 10240
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module load slurm
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module load openmpi/4.0.1
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# Check how many gpu's your job got
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#nvidia-smi
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# Run job
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cd /home/martinls/src/ShallowWaterGPU
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mpirun --mca btl_openib_if_include mlx5_0 --mca btl_openib_warn_no_device_params_found 0 /home/martinls/miniconda3/envs/ShallowWaterGPU_HPC/bin/python3 mpiTesting.py
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