{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numba\n",
    "from numba import cuda\n",
    "import cv2 \n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "imgrows = 2**7\n",
    "imgcols = 2**7\n",
    "BATCH = 32"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "## Average\n",
    "KERNEL = 15\n",
    "KERNEL_CONSTANT = np.ones((KERNEL,KERNEL))\n",
    "KERNEL_CONSTANT /= KERNEL*KERNEL\n",
    "\n",
    "\n",
    "### Laplacian\n",
    "# kernel = np.array([[-1,-1,-1], [-1, 8 ,-1],[-1,-1,-1]]) \n",
    "\n",
    "### sharpen\n",
    "# kernel = np.array([[0,-1,0], [-1,5,-1], [0,-1,0]]) \n",
    "\n",
    "# Edge detection\n",
    "# kernel = np.array([[0,1,0], [1,-4,1], [0,1,0]]) \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "@cuda.jit\n",
    "def slow_kernel(inputImage, kernel, outputImage, channels, w, h):\n",
    "    '''\n",
    "    Implementation of convolution through repeated access from global memory.\n",
    "    [BATCH_SIZE, IMG_ROWS, IMG_COLS, CHANNELS] = inputImage, outputImage sizes\n",
    "    TODO: Add constant memory for kernel\n",
    "    '''\n",
    "    r, c = cuda.grid(2) # Finding the global position of the thread\n",
    "    \n",
    "    ty = cuda.threadIdx.y\n",
    "    \n",
    "    kernel_c = cuda.const.array_like(KERNEL_CONSTANT)\n",
    "    \n",
    "    kernelRowsRadius = KERNEL//2\n",
    "    kernelColsRadius = KERNEL//2\n",
    "    for b in range(BATCH):\n",
    "        for ch in range(channels):\n",
    "            opPixel = 0\n",
    "            if r < h and c < w:\n",
    "                startRow = r - kernelRowsRadius\n",
    "                startCol = c - kernelColsRadius\n",
    "                for i in range(KERNEL):\n",
    "                    for j in range(KERNEL):\n",
    "                        currentRow = startRow + i\n",
    "                        currentCol = startCol + j\n",
    "                        if currentRow >= 0 and currentRow < h and currentCol >= 0 and currentCol < w:\n",
    "                            opPixel += inputImage[b, currentRow, currentCol, ch]*kernel_c[i][j]\n",
    "            outputImage[b,r,c,ch] = opPixel"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(16, 16)\n",
      "(8, 8)\n"
     ]
    }
   ],
   "source": [
    "img_batch = []\n",
    "for i in range(BATCH)[0::2]:\n",
    "    img = cv2.imread('peacock.jpg')\n",
    "    img = cv2.resize(img, (imgrows, imgcols))\n",
    "    img_batch.append(img)\n",
    "for i in range(BATCH)[1::2]:\n",
    "    img = cv2.imread('chess.jpg')\n",
    "    img = cv2.resize(img, (imgrows, imgcols))\n",
    "    img_batch.append(img)\n",
    "threadsperblock = (16, 16)\n",
    "blockspergrid = (np.ceil(imgrows/threadsperblock[0]).astype('int'), np.ceil(imgcols/threadsperblock[1]).astype('int'))\n",
    "print (threadsperblock)\n",
    "print (blockspergrid)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "channels = 3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "# stream = cuda.stream()\n",
    "# start = time.time()\n",
    "# with stream.auto_synchronize():\n",
    "channels = 3\n",
    "start = cuda.event(timing = True)\n",
    "stop = cuda.event(timing = True)\n",
    "inputImageGlobalMemory = cuda.to_device(img_batch)\n",
    "kernelGlobalMemory = cuda.to_device(KERNEL_CONSTANT)\n",
    "\n",
    "\n",
    "outputImageGlobalMemory = cuda.device_array((BATCH ,imgrows, imgcols, channels))\n",
    "\n",
    "# slow_kernel[blockspergrid, threadsperblock](inputImageGlobalMemory, outputImageGlobalMemory,channels, imgrows, imgcols)\n",
    "slow_kernel[blockspergrid, threadsperblock](inputImageGlobalMemory, kernelGlobalMemory,  outputImageGlobalMemory,channels, imgrows, imgcols)\n",
    "\n",
    "outputImage = outputImageGlobalMemory.copy_to_host()\n",
    "# To make executions async and when python exits the context\n",
    "# syncronization happens"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.001985152006149292\n"
     ]
    }
   ],
   "source": [
    "start.record()\n",
    "# slow_kernel[blockspergrid, threadsperblock](inputImageGlobalMemory, outputImageGlobalMemory,1, imgrows, imgcols)\n",
    "slow_kernel[blockspergrid, threadsperblock](inputImageGlobalMemory, kernelGlobalMemory, outputImageGlobalMemory,1, imgrows, imgcols)\n",
    "stop.record()\n",
    "\n",
    "outputImage = outputImageGlobalMemory.copy_to_host()\n",
    "print (start.elapsed_time(stop)*1e-3)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,10))\n",
    "plt.subplot(1,2,1)\n",
    "plt.imshow(img_batch[17][:,:,::-1])\n",
    "plt.title(\"Input Image\")\n",
    "\n",
    "plt.subplot(1,2,2)\n",
    "plt.imshow(outputImage[17][:,:,::-1].astype('uint8'))\n",
    "plt.title(\"Processed in GPU\")\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.042449235916137695\n"
     ]
    }
   ],
   "source": [
    "start = time.time()\n",
    "op_image = []\n",
    "for i in range(BATCH):\n",
    "    op_image.append(cv2.filter2D(img_batch[i],-1,KERNEL_CONSTANT))\n",
    "print (time.time() - start)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cv2.imwrite(\"output.jpg\", outputImage.astype('int'))\n",
    "cv2.imwrite(\"input.jpg\", img)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "O_TILE_WIDTH = 1\n",
    "BLOCK_WIDTH =  O_TILE_WIDTH + KERNEL - 1\n",
    "CHANNEL = 3\n",
    "DEPTH_TILE = 8\n",
    "NO_TILES_DEPTH = np.ceil(BATCH/DEPTH_TILE).astype('int32')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "@cuda.jit\n",
    "def shared_conv(inputImage, kernel, outputImage, channels, w, h):\n",
    "    \n",
    "    Ns = cuda.shared.array(shape=(BLOCK_WIDTH, BLOCK_WIDTH), dtype=numba.uint8)\n",
    "    \n",
    "    r, c  = cuda.grid(2)\n",
    "    KERNEL_RADIUS = KERNEL//2\n",
    "    \n",
    "    # Need to load cooperatively [blockDim.x + Kernelrowradius , blockDim.y + Kernelcolsradius]\n",
    "    tx = cuda.threadIdx.x\n",
    "    ty = cuda.threadIdx.y\n",
    "    \n",
    "    # Calculating the output tile's row and col coordinates\n",
    "    row_o = cuda.blockIdx.y*O_TILE_WIDTH + ty\n",
    "    col_o = cuda.blockIdx.x*O_TILE_WIDTH + tx\n",
    "    \n",
    "    # Shifting the coordinate system to corresponding input tile \n",
    "    row_i = row_o - KERNEL_RADIUS\n",
    "    col_i = col_o - KERNEL_RADIUS\n",
    "    \n",
    "    output = 0.0\n",
    "    \n",
    "    # Taking care of boundaries\n",
    "    if (row_i >= 0 and row_i < h and col_i >=0  and col_i < w):\n",
    "        Ns[ty][tx] = inputImage[row_i, col_i]\n",
    "    else:\n",
    "        Ns[ty][tx] = 0\n",
    "    \n",
    "    # Some threads do not participate in calclating the output\n",
    "    if (ty < O_TILE_WIDTH and tx < O_TILE_WIDTH):\n",
    "        for i in range(KERNEL):\n",
    "            for j in range(KERNEL):\n",
    "                output+= Ns[i+ty][j+tx]*kernel[i][j]\n",
    "        if row_o < w and col_o < h:\n",
    "            outputImage[row_o, col_o] = output\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "@cuda.jit\n",
    "def shared_conv_color(inputImage, kernel, outputImage, channels, w, h):\n",
    "    \n",
    "    Ns = cuda.shared.array(shape=(BATCH, BLOCK_WIDTH, BLOCK_WIDTH, CHANNEL), dtype=numba.uint8)\n",
    "    \n",
    "    r, c  = cuda.grid(2)\n",
    "    KERNEL_RADIUS = KERNEL//2\n",
    "    \n",
    "    # Pushing the kernel to constant memory for more speedup\n",
    "    kernel_c = cuda.const.array_like(KERNEL_CONSTANT)\n",
    "    \n",
    "    # Need to load cooperatively [blockDim.x + Kernelrowradius , blockDim.y + Kernelcolsradius]\n",
    "    tx = cuda.threadIdx.x\n",
    "    ty = cuda.threadIdx.y\n",
    "    \n",
    "    # Calculating the output tile's row and col coordinates\n",
    "    row_o = cuda.blockIdx.y*O_TILE_WIDTH + ty\n",
    "    col_o = cuda.blockIdx.x*O_TILE_WIDTH + tx\n",
    "    \n",
    "    # Shifting the coordinate system to corresponding input tile \n",
    "    row_i = row_o - KERNEL_RADIUS\n",
    "    col_i = col_o - KERNEL_RADIUS\n",
    "    \n",
    "    output = 0.0\n",
    "    \n",
    "    # Taking care of boundaries\n",
    "    if (row_i >= 0 and row_i < h and col_i >=0  and col_i < w):\n",
    "        for b in range(BATCH):\n",
    "            for ch in range(CHANNEL):\n",
    "                Ns[b, ty, tx, ch] = inputImage[b, row_i, col_i, ch]\n",
    "    else:\n",
    "        for b in range(BATCH):\n",
    "            for ch in range(CHANNEL):\n",
    "                Ns[b, ty, tx, ch] = 0\n",
    "    \n",
    "    # Synchronizing all the threads after loading the data into the shared memory\n",
    "    cuda.syncthreads()\n",
    "    \n",
    "    # Some threads do not participate in calclating the output\n",
    "    for b in range(BATCH):\n",
    "        for ch in range(CHANNEL):\n",
    "            output = 0.0\n",
    "            if (ty < O_TILE_WIDTH and tx < O_TILE_WIDTH):\n",
    "                for i in range(KERNEL):\n",
    "                    for j in range(KERNEL):\n",
    "                        output+= Ns[b, i+ty, j+tx, ch]*kernel[i][j]\n",
    "                if row_o < w and col_o < h:\n",
    "                    outputImage[b, row_o, col_o, ch] = output"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(15, 15)\n",
      "(128, 128)\n"
     ]
    }
   ],
   "source": [
    "img = cv2.imread('peacock.jpg')\n",
    "img = cv2.resize(img, (imgrows, imgcols))\n",
    "threadsperblock = (BLOCK_WIDTH , BLOCK_WIDTH)\n",
    "blockspergrid = (np.ceil(imgrows/O_TILE_WIDTH).astype('int'), np.ceil(imgcols/O_TILE_WIDTH).astype('int'))\n",
    "print (threadsperblock)\n",
    "print (blockspergrid)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.4574412841796875\n"
     ]
    }
   ],
   "source": [
    "start = cuda.event(timing = True)\n",
    "stop = cuda.event(timing = True)\n",
    "inputImageGlobalMemory = cuda.to_device(img_batch)\n",
    "kernelGlobalMemory = cuda.to_device(KERNEL_CONSTANT)\n",
    "outputImageGlobalMemory = cuda.device_array((BATCH, imgrows, imgcols, CHANNEL))\n",
    "\n",
    "start.record()\n",
    "# shared_conv[blockspergrid, threadsperblock](inputImageGlobalMemory, kernelGlobalMemory, outputImageGlobalMemory,1, imgrows, imgcols)\n",
    "shared_conv_color[blockspergrid, threadsperblock](inputImageGlobalMemory, kernelGlobalMemory, outputImageGlobalMemory,CHANNEL, imgrows, imgcols)\n",
    "stop.record()\n",
    "\n",
    "outputImage = outputImageGlobalMemory.copy_to_host()\n",
    "print (start.elapsed_time(stop)*1e-3)\n",
    "# To make executions async and when python exits the context\n",
    "# syncronization happens"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,10))\n",
    "plt.subplot(1,2,1)\n",
    "plt.imshow(img[:,:,::-1], cmap='gray')\n",
    "plt.title(\"Input Image\")\n",
    "\n",
    "plt.subplot(1,2,2)\n",
    "plt.imshow(outputImage[0][:,:,::-1].astype('uint8'), cmap='gray')\n",
    "plt.title(\"Processed in GPU\")\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### When you get the output to be black check the shared memory size!!!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "ename": "CudaAPIError",
     "evalue": "[700] Call to cuMemcpyDtoHAsync results in UNKNOWN_CUDA_ERROR",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mCudaAPIError\u001b[0m                              Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-18-42c488d30342>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m     25\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     26\u001b[0m \u001b[0;31m# Getting data back to GPU from CPU\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 27\u001b[0;31m \u001b[0moutputImage\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0moutputImageGlobalMemory\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcopy_to_host\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     28\u001b[0m \u001b[0mprint\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mstart\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0melapsed_time\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mstop\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0;36m1e-3\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/anaconda3/lib/python3.7/site-packages/numba/cuda/cudadrv/devices.py\u001b[0m in \u001b[0;36m_require_cuda_context\u001b[0;34m(*args, **kws)\u001b[0m\n\u001b[1;32m    210\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m_require_cuda_context\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkws\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    211\u001b[0m         \u001b[0mget_context\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 212\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mfn\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkws\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    213\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    214\u001b[0m     \u001b[0;32mreturn\u001b[0m \u001b[0m_require_cuda_context\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/anaconda3/lib/python3.7/site-packages/numba/cuda/cudadrv/devicearray.py\u001b[0m in \u001b[0;36mcopy_to_host\u001b[0;34m(self, ary, stream)\u001b[0m\n\u001b[1;32m    250\u001b[0m         \u001b[0;32massert\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0malloc_size\u001b[0m \u001b[0;34m>=\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m\"Negative memory size\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    251\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0malloc_size\u001b[0m \u001b[0;34m!=\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 252\u001b[0;31m             \u001b[0m_driver\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdevice_to_host\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mhostary\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0malloc_size\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstream\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mstream\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    253\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    254\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mary\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/anaconda3/lib/python3.7/site-packages/numba/cuda/cudadrv/driver.py\u001b[0m in \u001b[0;36mdevice_to_host\u001b[0;34m(dst, src, size, stream)\u001b[0m\n\u001b[1;32m   1774\u001b[0m         \u001b[0mfn\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdriver\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcuMemcpyDtoH\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1775\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1776\u001b[0;31m     \u001b[0mfn\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mhost_pointer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdst\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdevice_pointer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msrc\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msize\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0mvarargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1777\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1778\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/anaconda3/lib/python3.7/site-packages/numba/cuda/cudadrv/driver.py\u001b[0m in \u001b[0;36msafe_cuda_api_call\u001b[0;34m(*args)\u001b[0m\n\u001b[1;32m    286\u001b[0m             \u001b[0m_logger\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdebug\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'call driver api: %s'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlibfn\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__name__\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    287\u001b[0m             \u001b[0mretcode\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlibfn\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 288\u001b[0;31m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_check_error\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfname\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mretcode\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    289\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0msafe_cuda_api_call\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    290\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/anaconda3/lib/python3.7/site-packages/numba/cuda/cudadrv/driver.py\u001b[0m in \u001b[0;36m_check_error\u001b[0;34m(self, fname, retcode)\u001b[0m\n\u001b[1;32m    321\u001b[0m                     \u001b[0m_logger\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcritical\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmsg\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0m_getpid\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpid\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    322\u001b[0m                     \u001b[0;32mraise\u001b[0m \u001b[0mCudaDriverError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"CUDA initialized before forking\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 323\u001b[0;31m             \u001b[0;32mraise\u001b[0m \u001b[0mCudaAPIError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mretcode\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmsg\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    324\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    325\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mget_device\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdevnum\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mCudaAPIError\u001b[0m: [700] Call to cuMemcpyDtoHAsync results in UNKNOWN_CUDA_ERROR"
     ]
    }
   ],
   "source": [
    "n_streams = 4\n",
    "streams = []\n",
    "CHANNEL = 3\n",
    "\n",
    "# Creating a list of streams for Spatio Temporal parallelism\n",
    "for i in range(n_streams):\n",
    "    streams.append(cuda.stream())\n",
    "\n",
    "\n",
    "start = cuda.event(timing = True)\n",
    "stop = cuda.event(timing = True)\n",
    "\n",
    "# Pumping data from CPU to GPU\n",
    "for i in streams:\n",
    "    inputImageGlobalMemory = cuda.to_device(img_batch,stream=i)\n",
    "\n",
    "start.record()\n",
    "# Starting kernel Calls in CUDA streams \n",
    "for k in streams:\n",
    "    kernelGlobalMemory = cuda.to_device(KERNEL_CONSTANT,stream=k)\n",
    "    outputImageGlobalMemory = cuda.device_array((BATCH, imgrows, imgcols, CHANNEL),stream=k)\n",
    "    # shared_conv[blockspergrid, threadsperblock](inputImageGlobalMemory, kernelGlobalMemory, outputImageGlobalMemory,1, imgrows, imgcols)\n",
    "    slow_kernel[blockspergrid, threadsperblock](inputImageGlobalMemory, kernelGlobalMemory, outputImageGlobalMemory,CHANNEL, imgrows, imgcols)\n",
    "stop.record()\n",
    "\n",
    "# Getting data back to GPU from CPU\n",
    "outputImage = outputImageGlobalMemory.copy_to_host()\n",
    "print (start.elapsed_time(stop)*1e-3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.figure(figsize=(10,10))\n",
    "plt.subplot(1,2,1)\n",
    "plt.imshow(img_batch[15][:,:,::-1], cmap='gray')\n",
    "plt.title(\"Input Image\")\n",
    "\n",
    "plt.subplot(1,2,2)\n",
    "plt.imshow(outputImage[15][:,:,::-1].astype('uint8'), cmap='gray')\n",
    "plt.title(\"Processed in GPU\")\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.7.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
