“ CPU OpenCL Project”和“ GPU OpenCL Project”之间的差异

问题描述 投票:6回答:1

我安装了Intel OpenCL SDK,我想创建一个项目。 Visual Studio 2017向我展示了这两个选项和第三个“空OpenCL项目”。我不知道两者之间有什么区别。我试图浏览模板代码,但由于我(至今)对OpenCL一无所知,所以我无法理解它们之间的区别。

许可证标题:

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我按照建议跑了一个比较:

625,629c625,626
<     // Create new OpenCL buffer objects
<     // As these buffer are used only for read by the kernel, you are recommended to create it with flag CL_MEM_READ_ONLY.
<     // Always set minimal read/write flags for buffers, it may lead to better performance because it allows runtime
<     // to better organize data copying.
<     // You use CL_MEM_COPY_HOST_PTR here, because the buffers should be populated with bytes at inputA and inputB.
---
>     cl_image_format format;
>     cl_image_desc desc;
631c628,650
<     ocl->srcA = clCreateBuffer(ocl->context, CL_MEM_READ_ONLY | CL_MEM_USE_HOST_PTR, sizeof(cl_uint) * arrayWidth * arrayHeight, inputA, &err);
---
>     // Define the image data-type and order -
>     // one channel (R) with unit values
>     format.image_channel_data_type = CL_UNSIGNED_INT32;
>     format.image_channel_order     = CL_R;
> 
>     // Define the image properties (descriptor)
>     desc.image_type        = CL_MEM_OBJECT_IMAGE2D;
>     desc.image_width       = arrayWidth;
>     desc.image_height      = arrayHeight;
>     desc.image_depth       = 0;
>     desc.image_array_size  = 1;
>     desc.image_row_pitch   = 0;
>     desc.image_slice_pitch = 0;
>     desc.num_mip_levels    = 0;
>     desc.num_samples       = 0;
> #ifdef CL_VERSION_2_0
>     desc.mem_object        = NULL;
> #else
>     desc.buffer            = NULL;
> #endif
> 
>     // Create first image based on host memory inputA
>     ocl->srcA = clCreateImage(ocl->context, CL_MEM_READ_ONLY | CL_MEM_USE_HOST_PTR, &format, &desc, inputA, &err);
634c653
<         LogError("Error: clCreateBuffer for srcA returned %s\n", TranslateOpenCLError(err));
---
>         LogError("Error: clCreateImage for srcA returned %s\n", TranslateOpenCLError(err));
638c657,658
<     ocl->srcB = clCreateBuffer(ocl->context, CL_MEM_READ_ONLY | CL_MEM_USE_HOST_PTR, sizeof(cl_uint) * arrayWidth * arrayHeight, inputB, &err);
---
>     // Create second image based on host memory inputB
>     ocl->srcB = clCreateImage(ocl->context, CL_MEM_READ_ONLY | CL_MEM_USE_HOST_PTR, &format, &desc, inputB, &err);
641c661
<         LogError("Error: clCreateBuffer for srcB returned %s\n", TranslateOpenCLError(err));
---
>         LogError("Error: clCreateImage for srcB returned %s\n", TranslateOpenCLError(err));
645,649c665,666
<     // If the output buffer is created directly on top of output buffer using CL_MEM_USE_HOST_PTR,
<     // then, depending on the OpenCL runtime implementation and hardware capabilities, 
<     // it may save you not necessary data copying.
<     // As it is known that output buffer will be write only, you explicitly declare it using CL_MEM_WRITE_ONLY.
<     ocl->dstMem = clCreateBuffer(ocl->context, CL_MEM_WRITE_ONLY | CL_MEM_USE_HOST_PTR, sizeof(cl_uint) * arrayWidth * arrayHeight, outputC, &err);
---
>     // Create third (output) image based on host memory outputC
>     ocl->dstMem = clCreateImage(ocl->context, CL_MEM_WRITE_ONLY | CL_MEM_USE_HOST_PTR, &format, &desc, outputC, &err);
652c669
<         LogError("Error: clCreateBuffer for dstMem returned %s\n", TranslateOpenCLError(err));
---
>         LogError("Error: clCreateImage for dstMem returned %s\n", TranslateOpenCLError(err));
734c751,755
<     cl_int *resultPtr = (cl_int *)clEnqueueMapBuffer(ocl->commandQueue, ocl->dstMem, true, CL_MAP_READ, 0, sizeof(cl_uint) * width * height, 0, NULL, NULL, &err);
---
>     size_t origin[] = {0, 0, 0};
>     size_t region[] = {width, height, 1};
>     size_t image_row_pitch;
>     size_t image_slice_pitch;
>     cl_int *resultPtr = (cl_int *)clEnqueueMapImage(ocl->commandQueue, ocl->dstMem, true, CL_MAP_READ, origin, region, &image_row_pitch, &image_slice_pitch, 0, NULL, NULL, &err);
783c804
<     cl_device_type deviceType = CL_DEVICE_TYPE_CPU;
---
>     cl_device_type deviceType = CL_DEVICE_TYPE_GPU;

我也可以将两个完整的源文件粘贴为int,但是它们很长(900行)。

c++ opencl
1个回答
2
投票

您已经用差异回答了自己。在diff输出中,您可以看到一个项目使用clBuffer对象,而另一个项目使用clImage。

图像支持在OpenCL标准中是可选的,因此它取决于设备和驱动程序。 GPU设备在图像类型上可能具有更好的性能,并且大多数(如果不是全部)英特尔集成GPU支持图像类型(AFAIK)。

两种代码都使用主机指针,该主机指针在Intel设备上运行良好,因为iGPU和CPU可以寻址相同的内存,或者至少以这种方式运行。但是,这对于离散GPU可能并不总是最佳的。

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