GraphicsMagick 的 OpenCL 开发记录（三十一）

<2022-04-27 周三>

如何写ScaleImage()的硬件加速函数（五）

晚上做梦都在一直想这事儿，早上花了一个多小时，小有成果。

这里是参考ResizeHorizontalFilter()，居然把之前没有想明白的一些代码整清楚了：

1. accelerate.c:resizeHorizontalFilter()中传参gsize和lsize的地方，是拿目标宽高进行计算的，我的脑海中却一直用原始宽高去理解。

gsize[0]=(resizedColumns+pixelPerWorkgroup-1)/pixelPerWorkgroup*
  workgroupSize;
gsize[1]=resizedRows;
lsize[0]=workgroupSize;
lsize[1]=1;
outputReady=EnqueueOpenCLKernel(queue,horizontalKernel,2,
  (const size_t *) NULL,gsize,lsize,image,filteredImage,MagickFalse,
  exception);

2. 这里的用意是在kernel函数ResizeHorizontalFilter()中可以方便的使用get_global_id(0)和get_local_id(0)，不用像我在“如何写ScaleImage()的硬件加速函数（四）”中那样去计算dst_local_w和filtered_x了。
3. 但是似乎这里引出了另外一个问题，那原始宽高怎么用于计算呢？答案就是get_group_id(0)。

贴上目前开发一半的代码，效果是：

1. 原图缩小一倍，水平方向显示原图全部，但被压缩一半；垂直方向显示原图上半部。
2. 原图放大一倍，垂直方向显示原图全部，但被压缩一半；水平方向显示原图全部，但被拉长一倍。

附scaleFilter()和ScaleFilter()代码：

static MagickBooleanType scaleFilter(MagickCLDevice device,
  cl_command_queue queue,const Image *image,Image *filteredImage,
  cl_mem imageBuffer,cl_uint matte_or_cmyk,cl_uint columns,cl_uint rows,
  cl_mem scaledImageBuffer,cl_uint scaledColumns,cl_uint scaledRows,
  ExceptionInfo *exception)
{
  cl_kernel
    scaleKernel;

  cl_int
    status;

  const unsigned int
    workgroupSize = 256;

  float
    scale=1.0;

  int
    numCachedPixels;

  MagickBooleanType
    outputReady;

  size_t
    gammaAccumulatorLocalMemorySize,
    gsize[2],
    i,
    imageCacheLocalMemorySize,
    pixelAccumulatorLocalMemorySize,
    lsize[2],
    totalLocalMemorySize,
    weightAccumulatorLocalMemorySize;

  unsigned int
    chunkSize,
    pixelPerWorkgroup;

  int
    scale_ratio = 8; // related to the upper limit of zoom in?

  scaleKernel=NULL;
  outputReady=MagickFalse;

  scale=1.0/scale; // TODO(ocl)

  if (scaledColumns < workgroupSize)
  {
    chunkSize=32;
    pixelPerWorkgroup=32;
  }
  else
  {
    chunkSize=workgroupSize;
    pixelPerWorkgroup=workgroupSize;
  }

DisableMSCWarning(4127)
  while(1)
RestoreMSCWarning
  {
    /* calculate the local memory size needed per workgroup */
    numCachedPixels=(int) pixelPerWorkgroup;
    imageCacheLocalMemorySize=numCachedPixels*sizeof(CLQuantum)*4;
    totalLocalMemorySize=imageCacheLocalMemorySize;

    /* local size for the pixel accumulator */
    pixelAccumulatorLocalMemorySize=chunkSize*sizeof(cl_float4);
    totalLocalMemorySize+=pixelAccumulatorLocalMemorySize;

    /* local memory size for the weight accumulator */
    weightAccumulatorLocalMemorySize=chunkSize*sizeof(float);
    totalLocalMemorySize+=weightAccumulatorLocalMemorySize;

    /* local memory size for the gamma accumulator */
    gammaAccumulatorLocalMemorySize=chunkSize*sizeof(float);
    totalLocalMemorySize+=gammaAccumulatorLocalMemorySize;

    if (totalLocalMemorySize <= device->local_memory_size)
      break;
    else
    {
      pixelPerWorkgroup=pixelPerWorkgroup/2;
      chunkSize=chunkSize/2;
      if ((pixelPerWorkgroup == 0) || (chunkSize == 0))
      {
        /* quit, fallback to CPU */
        goto cleanup;
      }
    }
  }

  scaleKernel=AcquireOpenCLKernel(device,"ScaleFilter");
  if (scaleKernel == (cl_kernel) NULL)
  {
    (void) OpenCLThrowMagickException(device,exception,GetMagickModule(),
      ResourceLimitWarning,"AcquireOpenCLKernel failed.", ".");
    goto cleanup;
  }

  i=0;
  status =SetOpenCLKernelArg(scaleKernel,i++,sizeof(cl_mem),(void*)&imageBuffer);
  status|=SetOpenCLKernelArg(scaleKernel,i++,sizeof(cl_uint),(void*)&matte_or_cmyk);
  status|=SetOpenCLKernelArg(scaleKernel,i++,sizeof(cl_uint),(void*)&columns);
  status|=SetOpenCLKernelArg(scaleKernel,i++,sizeof(cl_uint),(void*)&rows);
  status|=SetOpenCLKernelArg(scaleKernel,i++,sizeof(cl_mem),(void*)&scaledImageBuffer);
  status|=SetOpenCLKernelArg(scaleKernel,i++,sizeof(cl_uint),(void*)&scaledColumns);
  status|=SetOpenCLKernelArg(scaleKernel,i++,sizeof(cl_uint),(void*)&scaledRows);
  status|=SetOpenCLKernelArg(scaleKernel,i++,sizeof(float),(void*)&scale);
  status|=SetOpenCLKernelArg(scaleKernel,i++,imageCacheLocalMemorySize,NULL);
  status|=SetOpenCLKernelArg(scaleKernel,i++,sizeof(int),&numCachedPixels);
  status|=SetOpenCLKernelArg(scaleKernel,i++,sizeof(unsigned int),&pixelPerWorkgroup);
  status|=SetOpenCLKernelArg(scaleKernel,i++,sizeof(unsigned int),&chunkSize);
  status|=SetOpenCLKernelArg(scaleKernel,i++,pixelAccumulatorLocalMemorySize,NULL);
  status|=SetOpenCLKernelArg(scaleKernel,i++,weightAccumulatorLocalMemorySize,NULL);
  status|=SetOpenCLKernelArg(scaleKernel,i++,gammaAccumulatorLocalMemorySize,NULL);
  status|=SetOpenCLKernelArg(scaleKernel,i++,sizeof(int),&scale_ratio);

  if (status != CL_SUCCESS)
  {
    (void) OpenCLThrowMagickException(device,exception,GetMagickModule(),
      ResourceLimitWarning,"SetOpenCLKernelArg failed.",".");
    goto cleanup;
  }

  gsize[0] = (scaledColumns + pixelPerWorkgroup - 1) / pixelPerWorkgroup *
    workgroupSize;
  gsize[1] = scaledRows;
  lsize[0] = workgroupSize;
  lsize[1] = 1;
  outputReady=EnqueueOpenCLKernel(queue,scaleKernel,2,
    (const size_t *) NULL,gsize,(Image *)NULL,image,filteredImage,MagickFalse,
    exception);

cleanup:

  if (scaleKernel != (cl_kernel) NULL)
    ReleaseOpenCLKernel(scaleKernel);

  return(outputReady);
}

STRINGIFY(
__kernel __attribute__((reqd_work_group_size(256, 1, 1)))
  void ScaleFilter(const __global CLQuantum *inputImage, const unsigned int matte_or_cmyk,
    const unsigned int inputColumns, const unsigned int inputRows, __global CLQuantum *filteredImage,
    const unsigned int filteredColumns, const unsigned int filteredRows,
    const float resizeFilterScale,
    __local CLQuantum *inputImageCache, const int numCachedPixels,
    const unsigned int pixelPerWorkgroup, const unsigned int pixelChunkSize,
    __local float4* outputPixelCache, __local float* densityCache, __local float* gammaCache,
    const int scale_ratio)
{
  // calculate the range of resized image pixels computed by this workgroup
  const unsigned int startX = get_group_id(0) * pixelPerWorkgroup;
  const unsigned int stopX = MagickMin(startX + pixelPerWorkgroup, filteredColumns);
  const unsigned int actualNumPixelToCompute = stopX - startX;

  float xFactor = (float)filteredColumns / inputColumns;

  // calculate the range of input image pixels to cache
  const int cacheRangeStartX = MagickMax((int)((startX + 0.5f) / xFactor), (int)(0));
  const int cacheRangeEndX = MagickMin((int)(cacheRangeStartX + numCachedPixels), (int)inputColumns);

  // cache the input pixels into local memory
  const unsigned int y = get_global_id(1);
  const unsigned int pos = getPixelIndex(4, inputColumns, cacheRangeStartX, y);
  const unsigned int num_elements = (cacheRangeEndX - cacheRangeStartX) * 4 * scale_ratio;
  event_t e = async_work_group_copy(inputImageCache, inputImage + pos, num_elements, 0);
  wait_group_events(1, &e);

  unsigned int totalNumChunks = (actualNumPixelToCompute + pixelChunkSize - 1) / pixelChunkSize;
  for (unsigned int chunk = 0; chunk < totalNumChunks; chunk++)
  {
    const unsigned int chunkStartX = startX + chunk * pixelChunkSize;
    const unsigned int chunkStopX = MagickMin(chunkStartX + pixelChunkSize, stopX);
    const unsigned int actualNumPixelInThisChunk = chunkStopX - chunkStartX;

    // determine which resized pixel computed by this workitem
    const unsigned int itemID = get_local_id(0);
    const unsigned int numItems = getNumWorkItemsPerPixel(actualNumPixelInThisChunk, get_local_size(0));

    const int pixelIndex = pixelToCompute(itemID, actualNumPixelInThisChunk, get_local_size(0));

    float4 filteredPixel = (float4)0.0f;

    // -1 means this workitem doesn't participate in the computation
    if (pixelIndex != -1)
    {
      // x coordinated of the resized pixel computed by this workitem
      const int x = chunkStartX + pixelIndex;

      // calculate how many steps required for this pixel
      const float bisect = (x + 0.5) / xFactor + MagickEpsilon;
      const unsigned int start = (unsigned int)MagickMax(bisect, 0.0f);
      const unsigned int stop = (unsigned int)MagickMin(bisect + 1, (float)inputColumns);
      const unsigned int n = stop - start;

      // calculate how many steps this workitem will contribute
      unsigned int numStepsPerWorkItem = n / numItems;
      numStepsPerWorkItem += ((numItems * numStepsPerWorkItem) == n ? 0 : 1);

      const unsigned int startStep = (itemID % numItems) * numStepsPerWorkItem;
      if (startStep < n)
      {
        const unsigned int stopStep = MagickMin(startStep + numStepsPerWorkItem, n);

        unsigned int cacheIndex = start + startStep - cacheRangeStartX;
        for (unsigned int i = startStep; i < stopStep; i++, cacheIndex++)
        {
          float4 cp = (float4)0.0f;

          __local CLQuantum* p = inputImageCache + (cacheIndex * 4);
          cp.x = (float)*(p);
          cp.y = (float)*(p + 1);
          cp.z = (float)*(p + 2);
          cp.w = (float)*(p + 3);

          filteredPixel += cp;
        }
      }
    }

    if (itemID < actualNumPixelInThisChunk)
    {
      WriteAllChannels(filteredImage, 4, filteredColumns, chunkStartX + itemID, y, filteredPixel);
    }
  }
}
)