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.
Use the Spark kernel for Scala applications, PySpark kernel for Python2 applications, and PySpark3 kernel for Python3 applications. Note For Spark 3.1, only PySpark3, or Spark will be available. A notebook opens with the kernel you selected. Benefits of using the kernels Here are a few ...
, simply exiting the notebooks doesn't kill the context. And so the cluster resources continue to be in use. A good practice is to use theClose and Haltoption from the notebook'sFilemenu when you're finished using the notebook. The closure kills the context and then exits the notebook....
notebook-executionKernels issues (start/restart/switch/execution, install ipykernel)perfPerformance issues Type No type Projects No projects Milestone No milestone Relationships None yet Development No branches or pull requests Participants Issue actions...
The NVIDIA NGC team is hosting a webinar with live Q&A to dive into this Jupyter notebook available from the NGC catalog. Learn how to use these resources to…
Use this command to start a Jupyter notebook inside the container: jupyter notebook --ip 0.0.0.0 --port 8888 --allow-root Move the dataset to the /data directory inside the container.Download the notebookwith the following command:
4. Install IPython and Jupyter Notebook Next, we will install IPython. IPython or Interactive Python is a command shell for interactive computing in multiple programming languages. It is available in the Debian repository and it can be easily installed using the apt package manager. To install IP...
With JupyterHub, you can create a multi-user Hub that spawns, manages, and proxies multiple instances of the single-user Jupyter Notebook server. The setup we plan on using for the TSS event consists of one HPE ProLiant DL360 Gen 10 with 2x Intel Xeon Silver 4114 CPUs running at 2.2GHz...
So, even if you selected PySpark3 or Spark kernels while creating the notebook, if you use the %%local magic in a cell, that cell must only have valid Python2 code. logs %%logs Outputs the logs for the current Livy session. delete %%delete -f -s <session number> Deletes a specific...
So, even if you selected PySpark3 or Spark kernels while creating the notebook, if you use the %%local magic in a cell, that cell must only have valid Python2 code. logs %%logs Outputs the logs for the current Livy session. delete %%delete -f -s <session number> Deletes a specific...