Question: What is needed headers and drivers are needed and where would I get them for compiling open CL on ubuntu using gcc/g++?
Info: for a while now I've been stumbling around trying to figure out how to install open CL on my desktop and if possible my netbook. There are a couple tutorials out there that I've tried but none seem to work. Also, they all just give a step by step with out really explaining why for the what, or even worse they are specific to a particular IDE so you have to learn the IDE to be able to do anything.
So I have an NVIDA GX465 in my desktop and integrated graphics in my netbook. my priority is of course my desktop, the netbook is just a convenience for development purposes(both run ubuntu 11.04 and will be running 11.10 as soon as it comes out). Can some one spell out for me what exactly is needed to get it so I can actually compile code and have it run. and if you could also explain what each piece does so that I can understand it's importance.
In OpenCL, the . cl files that contain device kernel codes are usually being compiled and built at run-time. It means somewhere in your host OpenCL program, you'll have to compile and build your device program to be able to use it. This feature enables maximum portability.
Executing the command clocl --version will display the version of the OpenCL compiler installed. Executing the command ls -l /usr/lib/libOpenCL* will display the OpenCL libraries installed on the device.
To compile and run OpenCL code under Linux, you'll need four things:
1) An NVIDIA Driver which supports OpenCL. The drivers packaged with Ubuntu are somewhat old, but they should still work just fine. Unless you have explicit need for current drivers, you should stick with the ones packaged with Ubuntu. To be clear, these are the same drivers installed through the restricted drivers manager. OpenCL libaries are shipped with driver, so to just run OpenCL programs driver should be enough.
2) The CUDA toolkit. This includes the headers necessary to compile OpenCL code. Install this to the default location.
3) The GPU Computing SDK (optional). This includes various NVIDIA specific support tools, as well as OpenCL code samples.
All three of these items may be found at http://developer.nvidia.com/cuda-toolkit-40.
4) OpenCL C++ bindings (optional). Strangely, they are not included with CUDA Toolkit, but in case you use C++, they could make your code much more redable. You can download them from http://www.khronos.org/registry/cl/api/1.1/cl.hpp, and just put it in /usr/local/cuda/include/CL an you desktop.
Once these are installed, you'll need to perform a few more steps to be able to compile and run OpenCL outside of the NVIDIA SDK.
1) The CUDA toolkit will have included the OpenCL headers (Listed at http://www.khronos.org/registry/cl/), likely they are in the directory /usr/local/cuda/include/CL. To make these headers available system wide, you should link this directory into /usr/include/, such that they may be accessed as /usr/include/CL/[headerfilename]. Instead of creating a symlink, you could add /usr/local/cuda/include to your C_INCLUDE_PATH
and CPLUS_INCLUDE_PATH
environment variables, but this would last for only currest session.
2) Make sure that the OpenCL library (libOpenCL.so) is present in /usr/lib. This should have been put in place by the driver, so you shouldn't have to do anything.
You're ready to write code. Make sure to include CL/cl.h
(or CL/cl.hpp
if you'd like to use C++ version of API) in any C(++) program which makes OpenCL API calls. When you compile, make sure to link against the OpenCL library (pass gcc the -lOpenCL
flag).
As far as your netbook, integrated graphics don't generally support OpenCL. In theory, AMD's APP Acceleration supports running OpenCL on the CPU, but it's not clear that it actually works.
If you love us? You can donate to us via Paypal or buy me a coffee so we can maintain and grow! Thank you!
Donate Us With