Poseidon on AWS Cluster¶
Training¶
The executable for running Poseidon tasks is psd_run
. Running psd_run -h
should print this:
usage: psd_run [-h] [-c,--cluster_config CLUSTER_CONFIG]
[-o,--out OUTPUT_FOLDER]
cmd
psd_run runs Poseidon for distributed machine learning on a GPU cluster. The following are its command line arguments.
positional arguments:
cmd
optional arguments:
-h, --help show this help message and exit
-c,--cluster_config CLUSTER_CONFIG
configuration file for cluster environment: specify workers in each machine. See example:
{
"virtualenv": "/home/ubuntu/sandbox",
"username": "ubuntu",
"pem_file": "/path/to/pem-file.pem",
"master_node": "localhost",
"worker_nodes": [
"192.168.1.11",
"192.168.1.15"
],
"server_nodes": [
"192.168.1.70",
"192.168.1.80"
]
}
-o,--out OUTPUT_FOLDER
output log folder
Setup¶
We must create a config.json
to specify our cluster configurations. If running a single node on Ubuntu within an AWS instance (with no virtualenv), the configurations are very simple:
Note: replace cluster-key.pem
with a path to your AWS pem file.
{
"pem_file": "cluster-key.pem",
"worker_nodes": [
"127.0.0.1"
],
"server_nodes": [
"127.0.0.1"
]
}
Note: if running on multiple AWS nodes, add each node’s private IP in the worker_nodes and server_nodes lists within config.json.
Execution¶
We can now launch Poseidon with the following command:
psd_run -c config.json -o logs "python $TF_MODEL_HOME/tutorials/image/cifar10/cifar10_train.py --max_steps 1000"
Poseidon Logs¶
After running Poseidon, you can check the execution log poseidon_run.log
in the same path you ran psd_run
. There are also output log files for debugging and monitoring purposes created in poseidon_log_$TIMESTAMP_SUFFIX
folder which will reside in a logs
folder in your current directory (the -o directive).