replace notebooks with cpu and gpu variants

apache · Dec 18, 2024 · 25afabe · 25afabe
1 parent a7a3d70
commit 25afabe
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Showing 2 changed files with 36 additions and 25 deletions.
diff --git a/...nt/jupyterhub/user-container/MD/poc.ipynb → ...upyterhub/user-container/MD/smd_cpu.ipynb b/...nt/jupyterhub/user-container/MD/poc.ipynb → ...upyterhub/user-container/MD/smd_cpu.ipynb
@@ -177,9 +177,8 @@
     "      \"data/b4pull.restart.xsc\",\n",
     "    ],\n",
     "    parallelism=\"CPU\",\n",
-    "    num_replicas=1,\n",
     ")\n",
-    "exp.add_replica(*ae.list_runtimes(cluster=\"login.expanse.sdsc.edu\", category=\"cpu\"))\n",
+    "exp.add_replica(*ae.list_runtimes(cluster=\"login.expanse.sdsc.edu\", category=\"cpu\", walltime=60))\n",
     "ae.display(exp)"
    ]
   },
@@ -360,8 +359,8 @@
    "outputs": [],
    "source": [
     "plan.wait_for_completion()                                # wait for plan to complete\n",
-    "for task in plan.tasks:\n",
-    "  task.download_all(f\"./results_{task.name}\")             # download plan outputs"
+    "# for task in plan.tasks:\n",
+    "#   task.download_all(f\"./results_{task.name}\")             # download plan outputs"
    ]
   },
   {
@@ -386,17 +385,24 @@
     "    @task.context(packages=[\"numpy\", \"pandas\"])\n",
     "    def analyze() -> None:\n",
     "        import numpy as np\n",
-    "        with open(\"pull.conf\", \"r\") as f:\n",
+    "        with open(\"pull_cpu.conf\", \"r\") as f:\n",
     "            data = f.read()\n",
-    "        print(\"pull.conf has\", len(data), \"chars\")\n",
+    "        print(\"pull_cpu.conf has\", len(data), \"chars\")\n",
     "        print(np.arange(10))\n",
     "    analyze()"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "airavata",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
    "name": "python3"
   },
@@ -410,9 +416,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.7"
+   "version": "3.11.6"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 2
+ "nbformat_minor": 4
 }
diff --git a/...upyterhub/user-container/MD/poc_dev.ipynb → ...upyterhub/user-container/MD/smd_gpu.ipynb b/...upyterhub/user-container/MD/poc_dev.ipynb → ...upyterhub/user-container/MD/smd_gpu.ipynb
@@ -41,7 +41,6 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "%cd dev-tools/deployment/jupyterhub/user-container/MD\n",
     "import airavata_experiments as ae\n",
     "from airavata_experiments import md"
    ]
@@ -145,8 +144,8 @@
    "outputs": [],
    "source": [
     "exp = md.NAMD.initialize(\n",
-    "    name=\"yasith_namd_experiment\",\n",
-    "    config_file=\"data/pull_cpu.conf\",\n",
+    "    name=\"SMD\",\n",
+    "    config_file=\"data/pull_gpu.conf\",\n",
     "    pdb_file=\"data/structure.pdb\",\n",
     "    psf_file=\"data/structure.psf\",\n",
     "    ffp_files=[\n",
@@ -159,10 +158,9 @@
     "      \"data/b4pull.restart.vel\",\n",
     "      \"data/b4pull.restart.xsc\",\n",
     "    ],\n",
-    "    parallelism=\"CPU\",\n",
-    "    num_replicas=1,\n",
+    "    parallelism=\"GPU\",\n",
     ")\n",
-    "exp.add_replica(*ae.list_runtimes(cluster=\"login.expanse.sdsc.edu\", category=\"cpu\"))\n",
+    "exp.add_replica(*ae.list_runtimes(cluster=\"login.expanse.sdsc.edu\", category=\"gpu\", walltime=180))\n",
     "ae.display(exp)"
    ]
   },
@@ -201,7 +199,7 @@
    "outputs": [],
    "source": [
     "plan.save()                   # this will save the plan in DB\n",
-    "plan.save_json(\"plan.json\")   # save the plan state locally"
+    "plan.save_json(\"plan_gpu.json\")   # save the plan state locally"
    ]
   },
   {
@@ -222,7 +220,7 @@
    "outputs": [],
    "source": [
     "plan.launch()\n",
-    "plan.save_json(\"plan.json\")"
+    "plan.save_json(\"plan_gpu.json\")"
    ]
   },
   {
@@ -257,7 +255,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "plan = ae.plan.load_json(\"plan.json\")\n",
+    "plan = ae.plan.load_json(\"plan_gpu.json\")\n",
     "plan = ae.plan.load(plan.id)\n",
     "plan.status()\n",
     "ae.display(plan)"
@@ -338,8 +336,8 @@
    "outputs": [],
    "source": [
     "plan.wait_for_completion()                                # wait for plan to complete\n",
-    "for task in plan.tasks:\n",
-    "  task.download_all(f\"./results_{task.name}\")             # download plan outputs"
+    "# for task in plan.tasks:\n",
+    "#   task.download_all(f\"./results_{task.name}\")             # download plan outputs"
    ]
   },
   {
@@ -364,17 +362,24 @@
     "    @task.context(packages=[\"numpy\", \"pandas\"])\n",
     "    def analyze() -> None:\n",
     "        import numpy as np\n",
-    "        with open(\"pull.conf\", \"r\") as f:\n",
+    "        with open(\"pull_gpu.conf\", \"r\") as f:\n",
     "            data = f.read()\n",
-    "        print(\"pull.conf has\", len(data), \"chars\")\n",
+    "        print(\"pull_gpu.conf has\", len(data), \"chars\")\n",
     "        print(np.arange(10))\n",
     "    analyze()"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "airavata",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
    "name": "python3"
   },
@@ -388,9 +393,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.7"
+   "version": "3.11.6"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 2
+ "nbformat_minor": 4
 }