daily update

research/tests/ray_test.ipynb

@@ -0,0 +1,126 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-10-03 09:43:41,741\tINFO worker.py:1786 -- Started a local Ray instance.\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "waiting for ray\n",
+      "ray returned all\n",
+      "ray finsihed 0.4031927839969285\n",
+      "worker 0 started\n",
+      "worker 0 finsihed\n",
+      "worker 1 started\n",
+      "worker 1 finsihed\n",
+      "worker 2 started\n",
+      "worker 2 finsihed\n",
+      "worker 3 started\n",
+      "worker 3 finsihed\n",
+      "serial function finsihed 0.21200023603159934\n",
+      "Ray with 4 parts: 0.4031927839969285 seconds\n",
+      "Serial: 0.21200023603159934 seconds\n",
+      "Serial computation is faster than Ray with 4 parts\n"
+     ]
+    }
+   ],
+   "source": [
+    "import numpy as np\n",
+    "import timeit\n",
+    "import ray\n",
+    "\n",
+    "# Define the expensive function\n",
+    "@ray.remote\n",
+    "def expensive_function(n):\n",
+    "    # Generate a large random matrix\n",
+    "    A = np.random.rand(1000, 1000)\n",
+    "    B = np.random.rand(1000, 1000)\n",
+    "\n",
+    "    # Perform the matrix multiplication\n",
+    "    C = np.dot(A, B)\n",
+    "    # Return the result\n",
+    "    return C\n",
+    "\n",
+    "def expensive_function_serial(n):\n",
+    "    print(f\"worker {n} started\")\n",
+    "    # Generate a large random matrix\n",
+    "    A = np.random.rand(1000, 1000)\n",
+    "    B = np.random.rand(1000, 1000)\n",
+    "\n",
+    "    # Perform the matrix multiplication\n",
+    "    C = np.dot(A, B)\n",
+    "\n",
+    "    # Return the result\n",
+    "    print(f\"worker {n} finsihed\")\n",
+    "    return C\n",
+    "\n",
+    "# Initialize Ray\n",
+    "ray.init()\n",
+    "\n",
+    "# Create 4 remote actors to distribute the work\n",
+    "futures = [expensive_function.remote(_) for _ in range(4)]\n",
+    "\n",
+    "# Time the function using Ray with 4 parts\n",
+    "start_time = timeit.default_timer()\n",
+    "print(\"waiting for ray\")\n",
+    "results = ray.get(futures)\n",
+    "print(\"ray returned all\")\n",
+    "end_time = timeit.default_timer()\n",
+    "ray_time = end_time - start_time\n",
+    "print(\"ray finsihed\", ray_time)\n",
+    "\n",
+    "# Time the function serially\n",
+    "start_time = timeit.default_timer()\n",
+    "results = [expensive_function_serial(_) for _ in range(4)]\n",
+    "end_time = timeit.default_timer()\n",
+    "serial_time = end_time - start_time\n",
+    "print(\"serial function finsihed\", serial_time)\n",
+    "\n",
+    "\n",
+    "# Print the results\n",
+    "print(f\"Ray with 4 parts: {ray_time} seconds\")\n",
+    "print(f\"Serial: {serial_time} seconds\")\n",
+    "\n",
+    "# Compare the results\n",
+    "if ray_time < serial_time:\n",
+    "    print(\"Ray with 4 parts is faster than serial computation\")\n",
+    "else:\n",
+    "    print(\"Serial computation is faster than Ray with 4 parts\")\n",
+    "\n",
+    "# Shutdown Ray\n",
+    "ray.shutdown()\n"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": ".venv",
+   "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": "3.10.11"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}