76 lines
3.2 KiB
Markdown
76 lines
3.2 KiB
Markdown
# OpenCL basic examples
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here is my feeble attempt at learning OpenCL, please don't make fun of me too much :hamburger:
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## Configuration
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This code uses OpenCL 1.1 on a NVIDIA GPU.
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### Linux
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(Only tested on Ubuntu). For NVIDIA GPUs, I've installed the following packages: `nvidia-346 nvidia-346-dev nvidia-346-uvm nvidia-libopencl1-346 nvidia-modprobe nvidia-opencl-icd-346 nvidia-settings`. Since the `opencl-headers` package in the main repository is for OpenCL 1.2, you can get the OpenCL 1.1 header files from [here](http://packages.ubuntu.com/precise/opencl-headers).
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Then to compile the C++ code:
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```
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g++ -std=c++0x main.cpp -o main.out -lOpenCL
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```
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To compile the C code:
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```
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gcc main.c -o main.out -lOpenCL
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```
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For examples 04 and 05, you can run
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```bash
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make ex04 # executable is ./example04/bin/Example
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make ex05 # executable is ./example05/bin/Example
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make # makes both!
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```
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### OS X
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OpenCL is installed on OS X by default, but since this code uses the C++ bindings, you'll need to get that too. Get the [official C++ bindings from the OpenCL registr](https://www.khronos.org/registry/cl/api/1.1/cl.hpp) and copy it to the OpenCL framework directory, or do the following:
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```
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wget https://www.khronos.org/registry/cl/api/1.1/cl.hpp
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sudo cp cl.hpp /System/Library/Frameworks/OpenCL.framework/Headers/
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```
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To compile:
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```
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clang++ -std=c++0x -framework OpenCL main.cpp -o main.out
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```
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## example 00
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this example is based off of [this example](simpleopencl.blogspot.ca/2013/06/tutorial-simple-start-with-opencl-and-c.html) (example-ception), but it goes a bit further. In the blogspot example, two 10-element vectors are created and a thread is used for each pair of elements. In this example, 10 threads are spawned but two 100-element vectors are used, and it is shown how to split up a specific number of elements per thread.
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## example 01
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Measures the duration of adding two vectors. See the README in the folder for more details.
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## example 02
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Demonstrates that one array can be modified several times without having to re-read and re-write data to and from the GPU.
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## example 03
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A simple example using the `cl_khr_fp64` extension which allows for usage of doubles instead of floats.
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## example 04
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An example of the CLFFT library for an in-place complex-planar transform. There is also Python code to check the answer; FFTW code will be added later, probably.
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- clFFT is required; installation instructions can be found inside example04/README.md
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- for Python, numpy and scipy are required
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## example 05
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Another CLFFT example where an in-place real transform is performed. There's also FFTW code and Python code for checking the answer.
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- clFFT is required; installation instructions can be found inside example04/README.md
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- FFTW is required; installation is as simple as extracting FFTW's tar file, then running `./configure && sudo make && sudo make install`
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- for Python, numpy and scipy are required
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## Some Notes
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From the [guide on programming OpenCL for NVIDIA](http://www.nvidia.com/content/cudazone/download/OpenCL/NVIDIA_OpenCL_ProgrammingGuide.pdf):
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- **CUDA streaming multiprocessor** corresponds to an OpenCL compute unit
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- **CUDA thread** corresponds to an OpenCL work-item
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- **CUDA thread block** corresponds to an OpenCL work-group
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