View the Arena documentation.
Arena is a command-line interface for the data scientists to run and monitor the machine learning training jobs and check their results in an easy way. Currently it supports solo/distributed TensorFlow training. In the backend, it is based on Kubernetes, helm and Kubeflow. But the data scientists can have very little knowledge about kubernetes.
Meanwhile, the end users require GPU resource and node management. Arena also provides top command to check available GPU resources in the Kubernetes cluster.
In one word, Arena's goal is to make the data scientists feel like to work on a single machine but with the Power of GPU clusters indeed.
For the Chinese version, please refer to 中文文档
You can follow up the Installation guide
Arena is a command-line interface to run and monitor the machine learning training jobs and check their results in an easy way. Please refer the User Guide to manage your training jobs.
Prerequisites:
- Go >= 1.8
mkdir -p $(go env GOPATH)/src/github.com/kubeflow
cd $(go env GOPATH)/src/github.com/kubeflow
git clone https://github.com/kubeflow/arena.git
cd arena
makearena binary is located in directory arena/bin. You may want to add the directory to $PATH.
Then you can follow Installation guide for developer
# set profile rate (HZ)
export PROFILE_RATE=1000
# arena {command} --pprof
arena list --pprof
INFO[0000] Dump cpu profile file into /tmp/cpu_profileThen you can analyze the profile by following Go CPU profiling: pprof and speedscope
If you are intrested in Arena and would like to share your experiences with others, you are warmly welcome to add your information on ADOPTERS.md page. We will continuousely discuss new requirements and feature design with you in advance.
Please refer to FAQ.
Please refer to arena.md.
See RoadMap.