[WIP] Debbuguing and performance guide

source/guides/debbuging-performance/cupy_optimal.ipynb

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+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "13f87ff2-5ce9-4954-918d-be5d3eea36b1",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import time\n",
+    "\n",
+    "import cupy as cp\n",
+    "import numpy as np\n",
+    "import xarray as xr"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "1eb0759a-0a92-423d-9c4b-264507e1283a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ds = xr.open_dataset(\"air.sig995.2025.nc\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "15b6a0c9-4206-4702-9580-05a1c37b4869",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "t0 = time.perf_counter()\n",
+    "\n",
+    "air = ds[\"air\"].cupy.as_cupy()\n",
+    "T = air.data\n",
+    "ntime, nlat, nlon = T.shape\n",
+    "\n",
+    "# --- Build X = anomalies (time × space) ---\n",
+    "X = T.reshape(ntime, nlat * nlon)\n",
+    "X = X - X.mean(axis=0, keepdims=True)  # remove 2025 mean at each grid point\n",
+    "\n",
+    "# --- EOF via SVD ---\n",
+    "U, S, Vt = np.linalg.svd(X, full_matrices=False)\n",
+    "\n",
+    "# First mode\n",
+    "eof1 = Vt[0, :].reshape(nlat, nlon)  # spatial pattern\n",
+    "pc1 = U[:, 0] * S[0]  # time series\n",
+    "var_frac1 = (S[0] ** 2) / np.sum(S**2)  # variance fraction (0–1)\n",
+    "\n",
+    "cp.cuda.Stream.null.synchronize()  # wait for cupy to finish the computation\n",
+    "\n",
+    "elapsed = time.perf_counter() - t0"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "3b965656-ddc6-4117-b025-04ca8b8ce017",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Time for EOF/PC calculation: 1.081 s\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(f\"Time for EOF/PC calculation: {elapsed:.3f} s\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "30e67178-7273-4e36-acde-a80d3de65943",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# noticed memory usage and utilization"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.13.12"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

source/guides/debbuging-performance/env.yaml

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+name: xarray-example
+channels:
+  - conda-forge
+  - rapidsai
+dependencies:
+  - python>=3.12
+  - xarray
+  - netCDF4
+  - bottleneck
+  - numpy
+  - cupy-xarray
+  - ipykernel # needed on brev to enable kernel
+  # - matplotlib
+  # - cartopy