CUDA _TEST_Fahim2.ipynb

{
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    {
     "name": "stdout",
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     "text": [
      "using cuda device\n"
     ]
    }
   ],
   "source": [
    "import torch\n",
    "\n",
    "if torch.cuda.is_available():\n",
    "    device = torch.device(\"cuda\")\n",
    "else:\n",
    "    device = torch.device(\"cpu\")\n",
    "print(\"using\", device, \"device\") "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "a8abcad4",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
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     "text": [
      "************* CPU SPEED *******************\n",
      "33.14937138557434\n",
      "verify device: cpu\n",
      "************* GPU SPEED *******************\n",
      "6.775448560714722\n",
      "verify device: cuda:0\n",
      "************* GPU SPEED *******************\n",
      "1.5217978954315186\n",
      "verify device: cuda:0\n",
      "************* GPU SPEED *******************\n",
      "1.49261474609375\n",
      "verify device: cuda:0\n"
     ]
    }
   ],
   "source": [
    "import time\n",
    "\n",
    "matrix_size = 32*512\n",
    "\n",
    "x = torch.randn(matrix_size, matrix_size)\n",
    "y = torch.randn(matrix_size, matrix_size)\n",
    "\n",
    "print(\"************* CPU SPEED *******************\")\n",
    "start = time.time()\n",
    "result = torch.matmul(x, y)\n",
    "print(time.time() - start)\n",
    "print(\"verify device:\", result.device)\n",
    "\n",
    "x_gpu = x.to(device)\n",
    "y_gpu = y.to(device)\n",
    "torch.cuda.synchronize()\n",
    "\n",
    "for i in range(3):\n",
    "    print(\"************* GPU SPEED *******************\")\n",
    "    start = time.time()\n",
    "    result_gpu = torch.matmul(x_gpu, y_gpu)\n",
    "    torch.cuda.synchronize()\n",
    "    print(time.time() - start)\n",
    "    print(\"verify device:\", result_gpu.device)"
   ]
  }
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