Running Legate programs with Jupyter Notebook#
Same as normal Python programs, Legate programs can be run using Jupyter Notebook. Currently we support single node execution with multiple CPUs and GPUs, and plan to support multi-node execution in the future. We leverage Legion’s Jupyter support, so you may want to refer to the relevant section in Legion’s README. To simplify the installation, we provide a script specifically for Legate libraries.
Running with Jupyter Notebook#
You will need to start a Jupyter server, then you can use a Jupyter notebook from any browser. Please refer to the following two sections from the README of the Legion Jupyter Notebook extension.
Start the Jupyter Notebook server
Use the Jupyter Notebook in the browser
Configuring the Jupyter Notebook#
The Legate Jupyter kernel is configured according to the command line
arguments provided at install time. Standard legate options for Core,
Memory, and Multi-node configuration may be provided, as well as a name for
the kernel:
legate-jupyter --name legate_cpus_2 --cpus 2
Other configuration options can be seen by using the --help command line
option.
Magic Command#
We provide a Jupyter magic command to display the IPython kernel configuration.
%load_ext legate.jupyter
%legate_info
results in output:
Kernel 'Legate_SM_GPU' configured for 1 node(s)
Cores:
CPUs to use per rank : 4
GPUs to use per rank : 0
OpenMP groups to use per rank : 0
Threads per OpenMP group : 4
Utility processors per rank : 2
Memory:
DRAM memory per rank (in MBs) : 4000
DRAM memory per NUMA domain per rank (in MBs) : 0
Framebuffer memory per GPU (in MBs) : 4000
Zero-copy memory per rank (in MBs) : 32
Registered CPU-side pinned memory per rank (in MBs) : 0