Draft: Fesom26 rc1 scripts

.gitignore

@@ -0,0 +1 @@
+Results

job_levante

@@ -0,0 +1,22 @@
+#!/bin/bash
+#SBATCH --job-name=ref
+#SBATCH -p compute
+#SBATCH --ntasks-per-node=128
+#SBATCH --ntasks=128
+#SBATCH --time=08:00:00
+#SBATCH -o slurm-%j.log
+#SBATCH -e slurm-%j.log
+#SBATCH -A ba0989
+
+source /home/a/a270092/loadconda.sh
+conda activate py39
+
+ulimit -s 102400
+ulimit -n 1000000
+
+echo Submitted job: $jobid
+squeue -u $USER
+
+date
+tripyrun  tripyrun_fesom26rc_bugfix_hnode.yml> "tripyrun.out"
+date

job_levante_addDVDsergeyandknut

@@ -0,0 +1,22 @@
+#!/bin/bash
+#SBATCH --job-name=ref
+#SBATCH -p compute
+#SBATCH --ntasks-per-node=128
+#SBATCH --ntasks=128
+#SBATCH --time=08:00:00
+#SBATCH -o slurm-%j.log
+#SBATCH -e slurm-%j.log
+#SBATCH -A ba0989
+
+source /home/a/a270092/loadconda.sh
+conda activate py39
+
+ulimit -s 102400
+ulimit -n 1000000
+
+echo Submitted job: $jobid
+squeue -u $USER
+
+date
+tripyrun  tripyrun_fesom26rc_addDVDsergeyandknut.yaml> "addDVDsergeyandknut.log"
+date

job_levante_bugfix_hnode

@@ -0,0 +1,22 @@
+#!/bin/bash
+#SBATCH --job-name=ref
+#SBATCH -p compute
+#SBATCH --ntasks-per-node=128
+#SBATCH --ntasks=128
+#SBATCH --time=08:00:00
+#SBATCH -o slurm-%j.log
+#SBATCH -e slurm-%j.log
+#SBATCH -A ba0989
+
+source /home/a/a270092/loadconda.sh
+conda activate py39
+
+ulimit -s 102400
+ulimit -n 1000000
+
+echo Submitted job: $jobid
+squeue -u $USER
+
+date
+tripyrun  tripyrun_fesom26rc_bugfix_hnode.yaml> "bugfix_hnode.log"
+date

job_levante_bugfix_ice_cutoff

@@ -0,0 +1,22 @@
+#!/bin/bash
+#SBATCH --job-name=ref
+#SBATCH -p compute
+#SBATCH --ntasks-per-node=128
+#SBATCH --ntasks=128
+#SBATCH --time=08:00:00
+#SBATCH -o slurm-%j.log
+#SBATCH -e slurm-%j.log
+#SBATCH -A ba0989
+
+source /home/a/a270092/loadconda.sh
+conda activate py39
+
+ulimit -s 102400
+ulimit -n 1000000
+
+echo Submitted job: $jobid
+squeue -u $USER
+
+date
+tripyrun  tripyrun_fesom26rc_bugfix_ice_cutoff.yaml> "bugfix_ice_cutoff.log"
+date

job_levante_fixsrfstress

@@ -0,0 +1,22 @@
+#!/bin/bash
+#SBATCH --job-name=ref
+#SBATCH -p compute
+#SBATCH --ntasks-per-node=128
+#SBATCH --ntasks=128
+#SBATCH --time=08:00:00
+#SBATCH -o slurm-%j.log
+#SBATCH -e slurm-%j.log
+#SBATCH -A ba0989
+
+source /home/a/a270092/loadconda.sh
+conda activate py39
+
+ulimit -s 102400
+ulimit -n 1000000
+
+echo Submitted job: $jobid
+squeue -u $USER
+
+date
+tripyrun  tripyrun_fesom26rc_fixsrfstress.yaml> "fixsrfstress.log"
+date

job_levante_ice_fct_screening

@@ -0,0 +1,22 @@
+#!/bin/bash
+#SBATCH --job-name=ref
+#SBATCH -p compute
+#SBATCH --ntasks-per-node=128
+#SBATCH --ntasks=128
+#SBATCH --time=08:00:00
+#SBATCH -o slurm-%j.log
+#SBATCH -e slurm-%j.log
+#SBATCH -A ba0989
+
+source /home/a/a270092/loadconda.sh
+conda activate py39
+
+ulimit -s 102400
+ulimit -n 1000000
+
+echo Submitted job: $jobid
+squeue -u $USER
+
+date
+tripyrun  tripyrun_fesom26rc_ice_fct_screening.yaml> "ice_fct_screening.log"
+date

job_levante_ifs_thermo

@@ -0,0 +1,22 @@
+#!/bin/bash
+#SBATCH --job-name=ref
+#SBATCH -p compute
+#SBATCH --ntasks-per-node=128
+#SBATCH --ntasks=128
+#SBATCH --time=08:00:00
+#SBATCH -o slurm-%j.log
+#SBATCH -e slurm-%j.log
+#SBATCH -A ba0989
+
+source /home/a/a270092/loadconda.sh
+conda activate py39
+
+ulimit -s 102400
+ulimit -n 1000000
+
+echo Submitted job: $jobid
+squeue -u $USER
+
+date
+tripyrun  tripyrun_fesom26rc_ifs_thermo.yaml> "ifs_thermo.log"
+date

job_levante_remove_PARMS

@@ -0,0 +1,22 @@
+#!/bin/bash
+#SBATCH --job-name=ref
+#SBATCH -p compute
+#SBATCH --ntasks-per-node=128
+#SBATCH --ntasks=128
+#SBATCH --time=08:00:00
+#SBATCH -o slurm-%j.log
+#SBATCH -e slurm-%j.log
+#SBATCH -A ba0989
+
+source /home/a/a270092/loadconda.sh
+conda activate py39
+
+ulimit -s 102400
+ulimit -n 1000000
+
+echo Submitted job: $jobid
+squeue -u $USER
+
+date
+tripyrun  tripyrun_fesom26rc_remove_PARMS.yaml> "remove_PARMS.log"
+date

templates_notebooks/template_2dmesh.ipynb

@@ -162,6 +162,8 @@
     "    from dask.distributed import Client\n",
     "    # from dask.diagnostics import ProgressBar\n",
     "    import dask\n",
+    "    from dask import config as cfg\n",
+    "    cfg.set({'distributed.scheduler.worker-ttl': None})\n",
     "    print(' --> memory_limit: {:3.3f} GB'.format(parallel_tmem/(parallel_nprc)))\n",
     "    ## dask.config.config.get('distributed').get('dashboard').update({'link':'{JUPYTERHUB_SERVICE_PREFIX}/proxy/{port}/status'})\n",
     "    client = Client(n_workers=parallel_nprc, threads_per_worker=1, memory_limit='{:3.3f} GB'.format(parallel_tmem/parallel_nprc))\n",
@@ -291,7 +293,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.19"
+   "version": "3.9.19"
   }
  },
  "nbformat": 4,

templates_notebooks/template_hmesh.ipynb

@@ -177,6 +177,8 @@
     "# start parallel dask client\n",
     "if do_parallel and not client_runs:\n",
     "    from dask.distributed import Client\n",
+    "    from dask import config as cfg\n",
+    "    cfg.set({'distributed.scheduler.worker-ttl': None})\n",
     "    ##import dask\n",
     "    ## dask.config.config.get('distributed').get('dashboard').update({'link':'{JUPYTERHUB_SERVICE_PREFIX}/proxy/{port}/status'})\n",
     "    print(' --> memory_limit: {:3.3f} GB'.format(parallel_tmem/(parallel_nprc)))\n",
@@ -359,7 +361,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.19"
+   "version": "3.9.19"
   },
   "latex_envs": {
    "LaTeX_envs_menu_present": true,

templates_notebooks/template_hovm.ipynb

@@ -175,6 +175,8 @@
     "# start parallel dask client\n",
     "if do_parallel and not client_runs:\n",
     "    from dask.distributed import Client\n",
+    "    from dask import config as cfg\n",
+    "    cfg.set({'distributed.scheduler.worker-ttl': None})\n",
     "    ##import dask\n",
     "    ## dask.config.config.get('distributed').get('dashboard').update({'link':'{JUPYTERHUB_SERVICE_PREFIX}/proxy/{port}/status'})\n",
     "    print(' --> memory_limit: {:3.3f} GB'.format(parallel_tmem/(parallel_nprc)))\n",

templates_notebooks/template_hovm_clim.ipynb

@@ -173,6 +173,8 @@
     "# start parallel dask client\n",
     "if do_parallel and not client_runs:\n",
     "    from dask.distributed import Client\n",
+    "    from dask import config as cfg\n",
+    "    cfg.set({'distributed.scheduler.worker-ttl': None})\n",
     "    ##import dask\n",
     "    ## dask.config.config.get('distributed').get('dashboard').update({'link':'{JUPYTERHUB_SERVICE_PREFIX}/proxy/{port}/status'})\n",
     "    client = Client(n_workers=parallel_nprc, threads_per_worker=1, memory_limit='{:3.3f} GB'.format(parallel_tmem/parallel_nprc))\n",

templates_notebooks/template_hquiver.ipynb

@@ -185,6 +185,8 @@
     "# start parallel dask client\n",
     "if do_parallel and not client_runs:\n",
     "    from dask.distributed import Client\n",
+    "    from dask import config as cfg\n",
+    "    cfg.set({'distributed.scheduler.worker-ttl': None})\n",
     "    ##import dask\n",
     "    ## dask.config.config.get('distributed').get('dashboard').update({'link':'{JUPYTERHUB_SERVICE_PREFIX}/proxy/{port}/status'})\n",
     "    print(' --> memory_limit: {:3.3f} GB'.format(parallel_tmem/(parallel_nprc)))\n",

templates_notebooks/template_hslice.ipynb

@@ -177,10 +177,8 @@
     "# start parallel dask client\n",
     "if do_parallel and not client_runs:\n",
     "    from dask.distributed import Client\n",
-    "    \n",
-    "#     # disable dask worker heartbeat --> prevent error ?\n",
-    "#     from dask import config as cfg\n",
-    "#     cfg.set({'distributed.scheduler.worker-ttl': None})\n",
+    "    from dask import config as cfg\n",
+    "    cfg.set({'distributed.scheduler.worker-ttl': None})\n",
     "    \n",
     "    ##import dask\n",
     "    ## dask.config.config.get('distributed').get('dashboard').update({'link':'{JUPYTERHUB_SERVICE_PREFIX}/proxy/{port}/status'})\n",

templates_notebooks/template_hslice_clim.ipynb

@@ -159,6 +159,8 @@
     "# start parallel dask client\n",
     "if do_parallel and not client_runs:\n",
     "    from dask.distributed import Client\n",
+    "    from dask import config as cfg\n",
+    "    cfg.set({'distributed.scheduler.worker-ttl': None})\n",
     "    ##import dask\n",
     "    ## dask.config.config.get('distributed').get('dashboard').update({'link':'{JUPYTERHUB_SERVICE_PREFIX}/proxy/{port}/status'})\n",
     "    client = Client(n_workers=parallel_nprc, threads_per_worker=1, memory_limit='{:3.3f} GB'.format(parallel_tmem/parallel_nprc))\n",

templates_notebooks/template_hslice_isotdep.ipynb

@@ -179,6 +179,8 @@
     "# start parallel dask client\n",
     "if do_parallel and not client_runs:\n",
     "    from dask.distributed import Client\n",
+    "    from dask import config as cfg\n",
+    "    cfg.set({'distributed.scheduler.worker-ttl': None})\n",
     "    ##import dask\n",
     "    ## dask.config.config.get('distributed').get('dashboard').update({'link':'{JUPYTERHUB_SERVICE_PREFIX}/proxy/{port}/status'})\n",
     "    print(' --> memory_limit: {:3.3f} GB'.format(parallel_tmem/(parallel_nprc)))\n",

templates_notebooks/template_transect.ipynb

@@ -170,6 +170,8 @@
     "# start parallel dask client\n",
     "if do_parallel and not client_runs:\n",
     "    from dask.distributed import Client\n",
+    "    from dask import config as cfg\n",
+    "    cfg.set({'distributed.scheduler.worker-ttl': None})\n",
     "    ##import dask\n",
     "    ## dask.config.config.get('distributed').get('dashboard').update({'link':'{JUPYTERHUB_SERVICE_PREFIX}/proxy/{port}/status'})\n",
     "    client = Client(n_workers=parallel_nprc, threads_per_worker=1, memory_limit='{:3.3f} GB'.format(parallel_tmem/parallel_nprc))\n",

templates_notebooks/template_transect_clim.ipynb

@@ -168,6 +168,8 @@
     "# start parallel dask client\n",
     "if do_parallel and not client_runs:\n",
     "    from dask.distributed import Client\n",
+    "    from dask import config as cfg\n",
+    "    cfg.set({'distributed.scheduler.worker-ttl': None})\n",
     "    ##import dask\n",
     "    ## dask.config.config.get('distributed').get('dashboard').update({'link':'{JUPYTERHUB_SERVICE_PREFIX}/proxy/{port}/status'})\n",
     "    client = Client(n_workers=parallel_nprc, threads_per_worker=1, memory_limit='{:3.3f} GB'.format(parallel_tmem/parallel_nprc))\n",

templates_notebooks/template_transect_transp.ipynb

@@ -173,6 +173,8 @@
     "# start parallel dask client\n",
     "if do_parallel and not client_runs:\n",
     "    from dask.distributed import Client\n",
+    "    from dask import config as cfg\n",
+    "    cfg.set({'distributed.scheduler.worker-ttl': None})\n",
     "    ##import dask\n",
     "    ## dask.config.config.get('distributed').get('dashboard').update({'link':'{JUPYTERHUB_SERVICE_PREFIX}/proxy/{port}/status'})\n",
     "    client = Client(n_workers=parallel_nprc, threads_per_worker=1, memory_limit='{:3.3f} GB'.format(parallel_tmem/parallel_nprc))\n",

templates_notebooks/template_transect_transp_t.ipynb

@@ -2,14 +2,15 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "/albedo/home/pscholz/tripyview\n"
+      "The autoreload extension is already loaded. To reload it, use:\n",
+      "  %reload_ext autoreload\n"
      ]
     }
    ],
@@ -194,6 +195,8 @@
     "# start parallel dask client\n",
     "if do_parallel and not client_runs:\n",
     "    from dask.distributed import Client\n",
+    "    from dask import config as cfg\n",
+    "    cfg.set({'distributed.scheduler.worker-ttl': None})\n",
     "    ##import dask\n",
     "    ## dask.config.config.get('distributed').get('dashboard').update({'link':'{JUPYTERHUB_SERVICE_PREFIX}/proxy/{port}/status'})\n",
     "    client = Client(n_workers=parallel_nprc, threads_per_worker=1, memory_limit='{:3.3f} GB'.format(parallel_tmem/parallel_nprc))\n",

templates_notebooks/template_transect_zmean.ipynb

@@ -176,6 +176,8 @@
     "# start parallel dask client\n",
     "if do_parallel and not client_runs:\n",
     "    from dask.distributed import Client\n",
+    "    from dask import config as cfg\n",
+    "    cfg.set({'distributed.scheduler.worker-ttl': None})\n",
     "    ##import dask\n",
     "    ## dask.config.config.get('distributed').get('dashboard').update({'link':'{JUPYTERHUB_SERVICE_PREFIX}/proxy/{port}/status'})\n",
     "    client = Client(n_workers=parallel_nprc, threads_per_worker=1, memory_limit='{:3.3f} GB'.format(parallel_tmem/parallel_nprc))\n",

templates_notebooks/template_transect_zmean_clim.ipynb

@@ -176,6 +176,8 @@
     "# start parallel dask client\n",
     "if do_parallel and not client_runs:\n",
     "    from dask.distributed import Client\n",
+    "    from dask import config as cfg\n",
+    "    cfg.set({'distributed.scheduler.worker-ttl': None})\n",
     "    ##import dask\n",
     "    ## dask.config.config.get('distributed').get('dashboard').update({'link':'{JUPYTERHUB_SERVICE_PREFIX}/proxy/{port}/status'})\n",
     "    print(' --> memory_limit: {:3.3f} GB'.format(parallel_tmem/(parallel_nprc)))\n",

templates_notebooks/template_transp_dmoc.ipynb

@@ -187,6 +187,8 @@
     "# start parallel dask client\n",
     "if do_parallel and not client_runs:\n",
     "    from dask.distributed import Client\n",
+    "    from dask import config as cfg\n",
+    "    cfg.set({'distributed.scheduler.worker-ttl': None})\n",
     "    ##import dask\n",
     "    ## dask.config.config.get('distributed').get('dashboard').update({'link':'{JUPYTERHUB_SERVICE_PREFIX}/proxy/{port}/status'})\n",
     "    print(' --> memory_limit: {:3.3f} GB'.format(parallel_tmem/(parallel_nprc)))\n",

templates_notebooks/template_transp_dmoc_srfcbflx.ipynb

@@ -178,6 +178,8 @@
     "# start parallel dask client\n",
     "if do_parallel and not client_runs:\n",
     "    from dask.distributed import Client\n",
+    "    from dask import config as cfg\n",
+    "    cfg.set({'distributed.scheduler.worker-ttl': None})\n",
     "    ##import dask\n",
     "    ## dask.config.config.get('distributed').get('dashboard').update({'link':'{JUPYTERHUB_SERVICE_PREFIX}/proxy/{port}/status'})\n",
     "    client = Client(n_workers=parallel_nprc, threads_per_worker=1, memory_limit='{:3.3f} GB'.format(parallel_tmem/parallel_nprc))\n",

templates_notebooks/template_transp_dmoc_t.ipynb

@@ -194,6 +194,8 @@
     "# start parallel dask client\n",
     "if do_parallel and not client_runs:\n",
     "    from dask.distributed import Client\n",
+    "    from dask import config as cfg\n",
+    "    cfg.set({'distributed.scheduler.worker-ttl': None})\n",
     "    ##import dask\n",
     "    ## dask.config.config.get('distributed').get('dashboard').update({'link':'{JUPYTERHUB_SERVICE_PREFIX}/proxy/{port}/status'})\n",
     "    print(' --> memory_limit: {:3.3f} GB'.format(parallel_tmem/(parallel_nprc)))\n",

templates_notebooks/template_transp_dmoc_wdiap.ipynb

@@ -169,6 +169,8 @@
     "# start parallel dask client\n",
     "if do_parallel and not client_runs:\n",
     "    from dask.distributed import Client\n",
+    "    from dask import config as cfg\n",
+    "    cfg.set({'distributed.scheduler.worker-ttl': None})\n",
     "    ##import dask\n",
     "    ## dask.config.config.get('distributed').get('dashboard').update({'link':'{JUPYTERHUB_SERVICE_PREFIX}/proxy/{port}/status'})\n",
     "    client = Client(n_workers=parallel_nprc, threads_per_worker=1, memory_limit='{:3.3f} GB'.format(parallel_tmem/parallel_nprc))\n",

templates_notebooks/template_transp_ghflx.ipynb

@@ -172,6 +172,8 @@
     "# start parallel dask client\n",
     "if do_parallel and not client_runs:\n",
     "    from dask.distributed import Client\n",
+    "    from dask import config as cfg\n",
+    "    cfg.set({'distributed.scheduler.worker-ttl': None})\n",
     "    ##import dask\n",
     "    ## dask.config.config.get('distributed').get('dashboard').update({'link':'{JUPYTERHUB_SERVICE_PREFIX}/proxy/{port}/status'})\n",
     "    print(' --> memory_limit: {:3.3f} GB'.format(parallel_tmem/(parallel_nprc)))\n",