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Running on PNNL Systems
Charles Siegel edited this page Jun 14, 2017
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The installation path for DGX-1 is /raid/matex/0.6/
To use MaTEx TensorFlow using GPUs 0,1,2 and 3, run
source /raid/matex/0.6/run_TFEnv_DGX1.sh
export CUDA_VISIBLE_DEVICES=0,1,2,3
Example scripts are located in
/raid/matex/0.6/examples/glibc_before_2.23/
To run a python script example.py
use the following code after sourcing run_TFEnv_DGX1.sh
:
mpirun -n 4 --mca opal_event_include poll $FAKE_SYSTEM_LIBS/lib/x86_64-linux-gnu/ld-linux-x86-64.so.2 --library-path $PNETCDF_INSTALL_DIR/lib:$FAKE_SYSTEM_LIBS/lib/:$FAKE_SYSTEM_LIBS/lib/x86_64-linux-gnu/:$FAKE_SYSTEM_LIBS/usr/lib64/gconv:$FAKE_SYSTEM_LIBS/usr/lib64/audit:$LD_LIBRARY_PATH $PYTHONHOME/bin/python $PWD/example.py
The installation path for Constance is /people/sieg052/matex/src/deeplearning/tensorflow/cpu/py3.x/
MaTEx TensorFlow is currently only configured for CPUs on Constance. To use set up the environment, run
source /people/sieg052/env_matex_cpu.sh
source /people/sieg052/matex/src/deeplearning/tensorflow/cpu/py3.x/run_TFEnv.sh
Example scripts are located in
/people/sieg052/matex/src/deeplearning/tensorflow/examples/glibc_before_2.23
To run a python script example.py
use the following code after sourcing run_TFEnv.sh
and setAlias.sh
:
mpirun -n $nodes --mca opal_event_include poll $FAKE_SYSTEM_LIBS/lib/x86_64-linux-gnu/ld-linux-x86-64.so.2 --library-path $PNETCDF_INSTALL_DIR/lib:$FAKE_SYSTEM_LIBS/lib/:$FAKE_SYSTEM_LIBS/lib/x86_64-linux-gnu/:$FAKE_SYSTEM_LIBS/usr/lib64/gconv:$FAKE_SYSTEM_LIBS/usr/lib64/audit:$LD_LIBRARY_PATH $PYTHONHOME/bin/python $PWD/example.py
Getting Started on MaTEx-TensorFlow
- Required Software
- Installing MaTEx-TensorFlow on CPU Clusters
- Installing MaTEx-TensorFlow on GPU Clusters
- MaTEx-TensorFlow on Older glibc(v<2.19)
- DataSet Reader
- Testing Scripts
- Performance
- Running on PNNL Systems
- Running on NERSC Systems
- Restarting the MaTEx TensorFlow environment