0.0_launch_cluster.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 0.0 Launch Cluster\n",
    "\n",
    "---\n",
    "\n",
    "Use this to start your `dask` cluster of workers. Uncomment `Cheyenne` if you're using Cheyenne. You can then open the `dask` tab in JupyterLab and type `proxy/####` where `####` is the proxy number from the Dashboard link under Client. Then you can drag tabs like Dask Workers, Dask Progress, etc. to the sidebar. You'll copy and paste the Scheduler tcp number into subsequent notebooks."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from ncar_jobqueue import NCARCluster\n",
    "from dask.distributed import Client"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Casper\n",
    "NUMNODES = 3\n",
    "num_processes = 9\n",
    "num_threads = 18\n",
    "MEM = \"200GB\"\n",
    "\n",
    "# Cheyenne\n",
    "# NUMNODES = 5\n",
    "# num_processes = 18\n",
    "# num_threads = 36\n",
    "# MEM = \"100GB\"\n",
    "\n",
    "cluster = NCARCluster(cores=num_threads,\n",
    "                      processes=num_processes,\n",
    "                      memory=MEM,\n",
    "                      walltime=\"02:00:00\",\n",
    "                     )\n",
    "cluster.scale(NUMNODES * num_processes)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "client = Client(cluster)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "8ecbcef14ee540ccb3b4be85b42b3511",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "VBox(children=(HTML(value='<h2>NCARCluster</h2>'), HBox(children=(HTML(value='\\n<div>\\n  <style scoped>\\n    .…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cluster"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table style=\"border: 2px solid white;\">\n",
       "<tr>\n",
       "<td style=\"vertical-align: top; border: 0px solid white\">\n",
       "<h3 style=\"text-align: left;\">Client</h3>\n",
       "<ul style=\"text-align: left; list-style: none; margin: 0; padding: 0;\">\n",
       "  <li><b>Scheduler: </b>tcp://10.12.205.11:42722</li>\n",
       "  <li><b>Dashboard: </b><a href='https://jupyterhub.ucar.edu/dav/user/rbrady/proxy/8787/status' target='_blank'>https://jupyterhub.ucar.edu/dav/user/rbrady/proxy/8787/status</a></li>\n",
       "</ul>\n",
       "</td>\n",
       "<td style=\"vertical-align: top; border: 0px solid white\">\n",
       "<h3 style=\"text-align: left;\">Cluster</h3>\n",
       "<ul style=\"text-align: left; list-style:none; margin: 0; padding: 0;\">\n",
       "  <li><b>Workers: </b>0</li>\n",
       "  <li><b>Cores: </b>0</li>\n",
       "  <li><b>Memory: </b>0 B</li>\n",
       "</ul>\n",
       "</td>\n",
       "</tr>\n",
       "</table>"
      ],
      "text/plain": [
       "<Client: 'tcp://10.12.205.11:42722' processes=0 threads=0, memory=0 B>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "client"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python [conda env:miniconda3-s2s]",
   "language": "python",
   "name": "conda-env-miniconda3-s2s-py"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}