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Is there any existing library for median filtering with kernel size greater then 5 using OpenCL acceleration in python?


Is there any existing library for median filtering with kernel size greater then 5 using OpenCL acceleration in python?

By : user2172806
Date : October 22 2020, 08:10 PM
will be helpful for those in need Have you tried cv::medianBlur (the 8-bit CPU version) yet? It's moving histogram implementation makes it's complexity O(1) with respect to block radius, thus it is very hard to beat at larger radii no matter how many cores you have. The OpenCL version on the other hand, which is embarrassingly parallel, uses sorting network for the median. Unfortunately such algorithm becomes inpractical quickly as the number of comparison operations required grows very fast.
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OpenCL random kernel behaviour when certain system size is exceeded

OpenCL random kernel behaviour when certain system size is exceeded


By : Bill Gianoukos
Date : March 29 2020, 07:55 AM
will be helpful for those in need It looks like a synchronization issue. grid[index] += value with the same index value may be executed concurrently by several work items. This operation is not atomic, and all these work items will load grid[index], add their value, and store it back, possibly losing some increments in the process.
To solve this, you can synchronize these work items using barrier if they are in a single work group, or enqueuing more kernels otherwise.
How to pass a list of arbitrary size to an OpenCL kernel

How to pass a list of arbitrary size to an OpenCL kernel


By : Mohamad farhand
Date : March 29 2020, 07:55 AM
I wish this helpful for you Passing an array of pointers to a kernel does not make sense, because the pointers would point to host memory, which the OpenCL device does not know anything about. You would have to transfer the data to a device buffer and then pass the buffer pointer to the kernel. (There are some more complicated options with mapped/pinned memory and especially in the case of APUs, but they don't change the main fact, that host pointers are invalid on the device).
I can suggest one approach, although I have never actually used it myself. If you have a large device buffer preallocated, you could fill it up with images back to back from the host. Then call the kernel with the buffer and a list of offsets as arguments.
OpenCL: How can I pass parameter with size greater than max_parameter_size?

OpenCL: How can I pass parameter with size greater than max_parameter_size?


By : Ella
Date : March 29 2020, 07:55 AM
wish helps you CL_DEVICE_MAX_PARAMETER_SIZE refers to the max size of a kernel parameter passed to clSetKernelArg. See CL_DEVICE_MAX_MEM_ALLOC_SIZE and CL_DEVICE_GLOBAL_MEM_SIZE in clGetDeviceInfo.
OpenCL kernel work-group size restriction

OpenCL kernel work-group size restriction


By : Michał Skibicki
Date : March 29 2020, 07:55 AM
I wish this help you Apple OpenCL doesn't support work-groups larger than [1, 1, 1] on the CPU. I have no idea why, but that's how it's been at least up to OSX 10.9.2. Larger work-groups are fine on the GPU, though.
Can I call C library functions from OpenCL kernel?

Can I call C library functions from OpenCL kernel?


By : Anish Biswas
Date : March 29 2020, 07:55 AM
seems to work fine No, you are restricted to built-in functions and functions defined by yourself on kernel level. This becomes immediately clear (in case of a GPU), if you see host and device as two separate entitities which can only communicate through a command queue and its associated calls.
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