imported>Uberfukken: Uberfukken moved page User:DNJACK/OpenCL to OpenCL

2019-03-14T00:56:35Z

Uberfukken moved page User:DNJACK/OpenCL to OpenCL

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So you've written your software in [[C]] but it's still too slow. Your next optimization step is to include [[Assembly| SIMD instructions]] but you are to lazy to learn to do it yourself, or you are looking for an excuse to blow several grands on a graphic card and you hate [[Nvidia]]? OpenCL might be right for you !
==How it works==
[[file:opencl_password_cracker.jpg|260px|thumb|1337 haxors can use it to [http://www.geeks3d.com/20121206/a-25-gpu-monster-cracks-passwords-in-opencl crack passwords] ]]

While [[Nvidia]]'s CUDA is made to be used by computer illiterate scientists, OpenCL forces you to tell it exactly what you want, so you'll need this. Both CUDA and OpenCL are lower-level than [[C]], so you better know what kind of hardware you expect it to run on or check it at runtime and write the code for the different hardware.

# Environment variables are initiated. - This is were the program learn what device will execute the code, like which of your numerous GPU it will use if you are overcompensating for your [[women|lack of dick]], etc...
# Memory initialization. - If you want to use the GPU, this is where you reserve memory on it. Special allocations also exists for CPU. Can also be done later.
# Reading and building the program. - The code have to be built at runtime to allow prior code to determine where the kernels will execute.
# Extracting the kernels. - Getting the different kernels functions from the compiled program.
# Write data to GPU memory, if program for GPU.
# Use them! aka enqueue a kernel in a command queue - You didn't do all that for nothing, didn't you.
# Read data from GPU memory if program for GPU, or unmap for CPU.
# Release Kernels, memory, and environment variables.

==Best Practices==

* Limit data transfers. They take important computer time.
* 256 work-item per GPU work-group will give good results most of the time.
* Error-check continuously, or you'll only get them when freeing memory.
* Make sure to create a fuckloads of threads. It is normal to sometime have more than one thread per data.

==See also==
* [[AMD]]
* [[Intel]]
* [[Nvidia]]
* [[OpenGL]]

==External Links==
* [http://www.khronos.org/opencl/ OpenCL]
* [http://developer.amd.com/tools-and-sdks/opencl-zone/ OpenCL - AMD]
* [http://software.intel.com/en-us/intel-opencl OpenCL - Intel]
* [http://developer.nvidia.com/opencl/ OpenCL - Nvidia]

{{Softwarez}}
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OpenCL - Revision history

imported>Uberfukken: Uberfukken moved page User:DNJACK/OpenCL to OpenCL