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Jupyter Notebook

This directory contains the Jupyter notebook support for the Python binding of Legion as well as the derived libraries including Legate, cuNumeric and Pygion. It provides the capability of running these libraries using the jupyter notebook from any browers.

Quick Start

Pre-requisite

Install the Legion IPython kernel

python ./install.py --(configurations)

Please refer to the IPython Kernel Configurations section for the configuration details.

If the installation is successed, the following log will be printed to the terminal. The legion_kernel_nocr is the IPython kernel name, and the Legate_SM_GPU is the display name of the kernel, which can be modified by the configuration json file. Legate is the name entry in the json file, SM means the IPython kernel is only for shared memory machine, and GPU means GPU execution is enabled.

IPython kernel: legion_kernel_nocr(Legate_SM_GPU) has been installed

The installed IPython kernel can be also seen by using the following command:

jupyter kernelspec list

Create a turnel (Optional)

If you want to run the jupyter notebook server on a remote compute node instead of localhost, you can create a turnel from localhost to the compute node.

ssh -4 -t -L 8888:localhost:8002 username@login-node-hostname ssh -t -L 8002:localhost:8888 computing_node

Start the Jupyter Notebook server

Launch jupyter notebook server on the compute node or localhost if the turnel is not created

jupyter notebook --port=8888 --no-browser

Use the Jupyter Notebook in the browser

  • Open the browser, type the addredd http://localhost:8888/?token=xxx, the token will be displayed in the terminal once the server is started.
  • Once the webpage is loaded, click "New" on the right top corner, and click the kernel just installed. It is shown as the display name of the kernel, e.g. Legate_SM_GPU.

Uninstall the IPython kernel

jupyter kernelspec uninstall legion_kernel_nocr

If the IPython kernel is re-installed, the old one will be automatically uninstalled by the install.py

IPython Kernel Configurations

The IPython kernel can be configured by either passing arguments to install.py or using a json file. The accepted arguments can be listed with

python ./install_jupyter.py --help

It is always preferred to use a json file. The legate.json and legion_python.json are two templates respect to the legate wrapper and legion_python. Most entries are using the following format:

"cpus": {
    "cmd": "--cpus",
    "value": 1
}

  • cpus is the name of the field.

  • cmd is used to tell how to pass the value to the field. For example, the legate wrapper uses --cpus to set the number of cpus, so the cmd in legate.json is --cpus, while legion takes -ll:cpu, so the cmd in legion_python.json is -ll:cpu.

  • value is the value of the field. It can be set to null. In this case, the value is read from the command line arguments.

Other configuration options can be added by either appending them to the command line arguments or using the other_options field of the json file.

Magic Command

We provide a Jupyter magic command to display the IPython kernel configuration.

%load_ext legate.info
%legate_info
Number of CPUs to use per rank: 4
Number of GPUs to use per rank: 1
Number of OpenMP groups to use per rank: 0
Number of threads per OpenMP group: 4
Number of Utility processors per rank: 2
Amount of DRAM memory per rank (in MBs): 4000
Amount of DRAM memory per NUMA domain per rank (in MBs): 0
Amount of framebuffer memory per GPU (in MBs): 4000
Amount of zero-copy memory per rank (in MBs): 32
Amount of registered CPU-side pinned memory per rank (in MBs): 0
Number of nodes to use: 1