{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "opposed-recycling",
   "metadata": {},
   "source": [
    "# Dask-jobqueue in Action"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "similar-writer",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<dask.config.set at 0x2b7e89a7a520>"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from dask_jobqueue import PBSCluster\n",
    "\n",
    "import dask\n",
    "\n",
    "dask.config.set(\n",
    "    {\n",
    "        'distributed.dashboard.link': 'https://jupyterhub.hpc.ucar.edu/stable/user/{USER}/dav-compute/proxy/{port}/status'\n",
    "    }\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "assisted-vocabulary",
   "metadata": {},
   "source": [
    "## Instatiate a cluster object"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "unavailable-comment",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "8e4fb40b26b54a1ca44ee3366f472f33",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "VBox(children=(HTML(value='<h2>PBSCluster</h2>'), HBox(children=(HTML(value='\\n<div>\\n  <style scoped>\\n    .d…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cluster = PBSCluster(\n",
    "    cores=1,\n",
    "    processes=1,\n",
    "    memory=\"10GB\",\n",
    "    queue=\"casper\",\n",
    "    project=\"NTDD0005\",\n",
    "    walltime=\"00:30:00\",\n",
    "    resource_spec=\"select=1:ncpus=1:mem=10GB:ngpus=1\",\n",
    "    extra=[\n",
    "        '--resources GPU=1'\n",
    "    ],  # tag dask-workers: # specify special hardware availability that the scheduler is not aware of\n",
    "    job_extra=['-l gpu_type=v100'],\n",
    "    env_extra=['module load cuda/11.0.3'],  # ensure cuda is loaded\n",
    ")\n",
    "\n",
    "cluster"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "naughty-fellowship",
   "metadata": {},
   "source": [
    "## Batch Job Script"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "foreign-implementation",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "#!/usr/bin/env bash\n",
      "\n",
      "#PBS -N dask-worker\n",
      "#PBS -q casper\n",
      "#PBS -A NTDD0005\n",
      "#PBS -l select=1:ncpus=1:mem=10GB:ngpus=1\n",
      "#PBS -l walltime=00:30:00\n",
      "#PBS -e /glade/scratch/abanihi/\n",
      "#PBS -o /glade/scratch/abanihi/\n",
      "#PBS -l gpu_type=v100\n",
      "module load cuda/11.0.3\n",
      "/glade/work/abanihi/opt/miniconda/envs/dask-gpu/bin/python -m distributed.cli.dask_worker tcp://10.12.205.17:41700 --nthreads 1 --memory-limit 9.31GiB --name dummy-name --nanny --death-timeout 60 --local-directory /glade/scratch/abanihi --resources GPU=1 --interface ib0 --protocol tcp://\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(cluster.job_script())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "voluntary-lover",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                                                            Req'd  Req'd   Elap\n",
      "Job ID          Username Queue    Jobname    SessID NDS TSK Memory Time  S Time\n",
      "--------------- -------- -------- ---------- ------ --- --- ------ ----- - -----\n",
      "240546.casper-* abanihi  jhublog* STDIN      217212   1   1    4gb 720:0 R 226:0\n",
      "251037.casper-* abanihi  jhublog* STDIN      238092   1   1    4gb 720:0 R 149:3\n",
      "282298.casper-* abanihi  tdd      STDIN       10906   1   1   10gb 00:30 R 00:01\n",
      "282301.casper-* abanihi  tdd      dask-work*  31679   1   1   10gb 00:30 R 00:00\n",
      "282302.casper-* abanihi  tdd      dask-work*    --    1   1   10gb 00:30 R   -- \n"
     ]
    }
   ],
   "source": [
    "!qstat -u abanihi"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "tough-syntax",
   "metadata": {},
   "source": [
    "## Cluster Scaling APIs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "widespread-montgomery",
   "metadata": {},
   "outputs": [],
   "source": [
    "cluster.scale(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "amino-poker",
   "metadata": {},
   "outputs": [],
   "source": [
    "cluster.scale(jobs=2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "differential-ranch",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<distributed.deploy.adaptive.Adaptive at 0x2b7e8985eac0>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cluster.adapt(minimum=2, maximum=4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "hydraulic-greeting",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<distributed.deploy.adaptive.Adaptive at 0x2b7eacd3f400>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cluster.adapt(minimum_jobs=2, maximum_jobs=4)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dressed-ethernet",
   "metadata": {},
   "source": [
    "## Connect created cluster to a client"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "sustained-simple",
   "metadata": {},
   "outputs": [],
   "source": [
    "from distributed import Client\n",
    "\n",
    "client = Client(cluster)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "documented-ecology",
   "metadata": {},
   "source": [
    "## Confirm that our dask workers have access to GPUs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "twelve-guatemala",
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_nvidia_smi_info():\n",
    "    import subprocess\n",
    "\n",
    "    p = subprocess.check_output('nvidia-smi').strip().decode('utf-8')\n",
    "    return p\n",
    "\n",
    "\n",
    "def nvidia_smi(on='workers'):\n",
    "    if on == 'workers':\n",
    "        x = client.run(get_nvidia_smi_info)\n",
    "        print(\" ***** NVIDIA-SMI info on Workers *****\")\n",
    "        for key, value in x.items():\n",
    "            print(\"*\" * 80)\n",
    "            print(key)\n",
    "            print(value, end=\"\\n\\n\")\n",
    "\n",
    "    elif on == 'scheduler':\n",
    "        print(\"***** NVIDIA-SMI info on Scheduler *****\")\n",
    "        print(client.run_on_scheduler(get_nvidia_smi_info))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "least-colors",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " ***** NVIDIA-SMI info on Workers *****\n",
      "********************************************************************************\n",
      "tcp://10.12.205.38:40174\n",
      "Wed May 19 22:18:08 2021       \n",
      "+-----------------------------------------------------------------------------+\n",
      "| NVIDIA-SMI 450.51.06    Driver Version: 450.51.06    CUDA Version: 11.0     |\n",
      "|-------------------------------+----------------------+----------------------+\n",
      "| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |\n",
      "| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |\n",
      "|                               |                      |               MIG M. |\n",
      "|===============================+======================+======================|\n",
      "|   0  Tesla V100-SXM2...  On   | 00000000:B2:00.0 Off |                    0 |\n",
      "| N/A   31C    P0    40W / 300W |      0MiB / 32510MiB |      0%      Default |\n",
      "|                               |                      |                  N/A |\n",
      "+-------------------------------+----------------------+----------------------+\n",
      "                                                                               \n",
      "+-----------------------------------------------------------------------------+\n",
      "| Processes:                                                                  |\n",
      "|  GPU   GI   CI        PID   Type   Process name                  GPU Memory |\n",
      "|        ID   ID                                                   Usage      |\n",
      "|=============================================================================|\n",
      "|  No running processes found                                                 |\n",
      "+-----------------------------------------------------------------------------+\n",
      "\n",
      "********************************************************************************\n",
      "tcp://10.12.205.38:41472\n",
      "Wed May 19 22:18:08 2021       \n",
      "+-----------------------------------------------------------------------------+\n",
      "| NVIDIA-SMI 450.51.06    Driver Version: 450.51.06    CUDA Version: 11.0     |\n",
      "|-------------------------------+----------------------+----------------------+\n",
      "| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |\n",
      "| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |\n",
      "|                               |                      |               MIG M. |\n",
      "|===============================+======================+======================|\n",
      "|   0  Tesla V100-SXM2...  On   | 00000000:1B:00.0 Off |                    0 |\n",
      "| N/A   31C    P0    40W / 300W |      0MiB / 32510MiB |      0%      Default |\n",
      "|                               |                      |                  N/A |\n",
      "+-------------------------------+----------------------+----------------------+\n",
      "                                                                               \n",
      "+-----------------------------------------------------------------------------+\n",
      "| Processes:                                                                  |\n",
      "|  GPU   GI   CI        PID   Type   Process name                  GPU Memory |\n",
      "|        ID   ID                                                   Usage      |\n",
      "|=============================================================================|\n",
      "|  No running processes found                                                 |\n",
      "+-----------------------------------------------------------------------------+\n",
      "\n"
     ]
    }
   ],
   "source": [
    "nvidia_smi()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "global-hollywood",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "***** NVIDIA-SMI info on Scheduler *****\n",
      "Wed May 19 22:18:09 2021       \n",
      "+-----------------------------------------------------------------------------+\n",
      "| NVIDIA-SMI 450.51.06    Driver Version: 450.51.06    CUDA Version: 11.0     |\n",
      "|-------------------------------+----------------------+----------------------+\n",
      "| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |\n",
      "| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |\n",
      "|                               |                      |               MIG M. |\n",
      "|===============================+======================+======================|\n",
      "|   0  Tesla V100-SXM2...  On   | 00000000:B3:00.0 Off |                    0 |\n",
      "| N/A   28C    P0    40W / 300W |      0MiB / 32510MiB |      0%      Default |\n",
      "|                               |                      |                  N/A |\n",
      "+-------------------------------+----------------------+----------------------+\n",
      "                                                                               \n",
      "+-----------------------------------------------------------------------------+\n",
      "| Processes:                                                                  |\n",
      "|  GPU   GI   CI        PID   Type   Process name                  GPU Memory |\n",
      "|        ID   ID                                                   Usage      |\n",
      "|=============================================================================|\n",
      "|  No running processes found                                                 |\n",
      "+-----------------------------------------------------------------------------+\n"
     ]
    }
   ],
   "source": [
    "nvidia_smi(on='scheduler')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "found-split",
   "metadata": {},
   "source": [
    "## Run some computation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "wooden-quarterly",
   "metadata": {},
   "outputs": [],
   "source": [
    "import cupy\n",
    "\n",
    "import dask.array as da"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "bulgarian-point",
   "metadata": {},
   "outputs": [
    {
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     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# generate chunked dask arrays of many cupy random arrays\n",
    "rs = da.random.RandomState(RandomState=cupy.random.RandomState)  # <-- we specify cupy here\n",
    "x = rs.normal(10, 1, size=(200000, 200000), chunks=(10000, 4000), dtype=cupy.float32)\n",
    "x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "historic-shipping",
   "metadata": {},
   "outputs": [
    {
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     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y = (x + 1)[::2, ::2].std(axis=0)\n",
    "y = y.persist()\n",
    "y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "presidential-patio",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 30 ms, sys: 2 ms, total: 32 ms\n",
      "Wall time: 36.7 ms\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "result = y.compute()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "expired-weather",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.9968655 , 0.99782085, 1.0016662 , ..., 1.0015868 , 0.9996461 ,\n",
       "       0.9991475 ], dtype=float32)"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
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  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "matched-greene",
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   "outputs": [
    {
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       "cupy._core.core.ndarray"
      ]
     },
     "execution_count": 25,
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   "cell_type": "code",
   "execution_count": 26,
   "id": "express-mongolia",
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     "text": [
      " ***** NVIDIA-SMI info on Workers *****\n",
      "********************************************************************************\n",
      "tcp://10.12.205.38:40174\n",
      "Wed May 19 22:23:17 2021       \n",
      "+-----------------------------------------------------------------------------+\n",
      "| NVIDIA-SMI 450.51.06    Driver Version: 450.51.06    CUDA Version: 11.0     |\n",
      "|-------------------------------+----------------------+----------------------+\n",
      "| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |\n",
      "| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |\n",
      "|                               |                      |               MIG M. |\n",
      "|===============================+======================+======================|\n",
      "|   0  Tesla V100-SXM2...  On   | 00000000:B2:00.0 Off |                    0 |\n",
      "| N/A   32C    P0    52W / 300W |    926MiB / 32510MiB |      0%      Default |\n",
      "|                               |                      |                  N/A |\n",
      "+-------------------------------+----------------------+----------------------+\n",
      "                                                                               \n",
      "+-----------------------------------------------------------------------------+\n",
      "| Processes:                                                                  |\n",
      "|  GPU   GI   CI        PID   Type   Process name                  GPU Memory |\n",
      "|        ID   ID                                                   Usage      |\n",
      "|=============================================================================|\n",
      "|    0   N/A  N/A     31956      C   .../envs/dask-gpu/bin/python      923MiB |\n",
      "+-----------------------------------------------------------------------------+\n",
      "\n",
      "********************************************************************************\n",
      "tcp://10.12.205.38:41472\n",
      "Wed May 19 22:23:17 2021       \n",
      "+-----------------------------------------------------------------------------+\n",
      "| NVIDIA-SMI 450.51.06    Driver Version: 450.51.06    CUDA Version: 11.0     |\n",
      "|-------------------------------+----------------------+----------------------+\n",
      "| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |\n",
      "| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |\n",
      "|                               |                      |               MIG M. |\n",
      "|===============================+======================+======================|\n",
      "|   0  Tesla V100-SXM2...  On   | 00000000:1B:00.0 Off |                    0 |\n",
      "| N/A   33C    P0    54W / 300W |    926MiB / 32510MiB |      0%      Default |\n",
      "|                               |                      |                  N/A |\n",
      "+-------------------------------+----------------------+----------------------+\n",
      "                                                                               \n",
      "+-----------------------------------------------------------------------------+\n",
      "| Processes:                                                                  |\n",
      "|  GPU   GI   CI        PID   Type   Process name                  GPU Memory |\n",
      "|        ID   ID                                                   Usage      |\n",
      "|=============================================================================|\n",
      "|    0   N/A  N/A     31847      C   .../envs/dask-gpu/bin/python      923MiB |\n",
      "+-----------------------------------------------------------------------------+\n",
      "\n"
     ]
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