Getting started on GPU programming (opencl)

In summary: If you're willing to work in C++ (or better, C++11), there are a lot of options. Three of them, in alphabetical order, are ArrayFire, Boost.Compute, and VexCL. I'm sure there are others.
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fluidistic
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I'd like to know how to get started to write a program for the GPU. Say I want to let the GPU calculate 4*2.
I have an intel integrated HD4000 graphics card so I'd be better to use opencl I believe.
I'm not really finding any tutorial on how to do this. Any help or comment is welcome.
 
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  • #2
fluidistic said:
I'd like to know how to get started to write a program for the GPU. Say I want to let the GPU calculate 4*2.
I have an intel integrated HD4000 graphics card so I'd be better to use opencl I believe.
I'm not really finding any tutorial on how to do this. Any help or comment is welcome.
Do you have the opencl SDK for the Intel HD4000? If so, have you looked at the information in https://software.intel.com/en-us/intel-opencl ?

PS. I am not familiar with it, so I can't say for sure that the information there will answer your questions. But it may let you focus in on more specific issues.
 
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  • #3
FactChecker said:
Do you have the opencl SDK for the Intel HD4000? If so, have you looked at the information in https://software.intel.com/en-us/intel-opencl ?

PS. I am not familiar with it, so I can't say for sure that the information there will answer your questions. But it may let you focus in on more specific issues.
Thanks, I wasn't aware I'd need specific packages. I use arch linux so I'm reading https://wiki.archlinux.org/index.php/GPGPU.
Apparently I need the AUR package intel-opencl-runtime to execute code and [URL='https://www.archlinux.org/packages/?name=ocl-icd']ocl-icd, as well as [URL='https://www.archlinux.org/packages/?name=opencl-headers']opencl-headers.[/URL]
[URL='https://www.archlinux.org/packages/?name=ocl-icd']
I also see a Python language binding package called python-pyopencl.
Programming in python would be nice, to say the least.
 
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fluidistic said:
I also see a Python language binding package called python-pyopencl.
Programming in python would be nice, to say the least.
Python is not the first thing I would think of in this context. Python is so slow, and PyOpenCL is a very thin wrapper on top of the very verbose and rather hard to use OpenCL framework. You'll get all of the pain of OpenCL and all of the slowness of Python.

If you're willing to work in C++ (or better, C++11), there are a lot of options. Three of them, in alphabetical order, are ArrayFire, Boost.Compute, and VexCL. I'm sure there are others.
 
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Related to Getting started on GPU programming (opencl)

1. What is GPU programming and how does it differ from traditional programming?

GPU programming, or general-purpose computing on graphics processing units, is a way of utilizing the parallel processing power of GPUs to perform complex computations. It differs from traditional programming in that it requires a different approach to writing code and optimizing for the massively parallel architecture of GPUs.

2. What is OpenCL and why is it used for GPU programming?

OpenCL, or Open Computing Language, is an open standard for parallel programming across different types of hardware, including GPUs. It allows developers to write code that can be executed on a variety of platforms, making it a popular choice for GPU programming.

3. Do I need specialized hardware or software to get started with GPU programming?

While having a dedicated GPU is necessary for GPU programming, most modern computers already have a GPU that can be used. Additionally, there are a variety of software development kits and frameworks available that make it easier to get started with GPU programming, such as CUDA for NVIDIA GPUs and AMD APP SDK for AMD GPUs.

4. What kind of applications can benefit from GPU programming?

GPU programming is particularly useful for applications that require a lot of data processing and can be broken down into smaller, parallel tasks. This includes tasks such as image and video processing, machine learning, and scientific simulations. However, not all applications will see a significant performance boost from using GPU programming.

5. How can I learn and improve my skills in GPU programming?

There are many resources available online for learning GPU programming, including tutorials, courses, and forums. It is also helpful to practice and experiment with different algorithms and techniques to improve your skills. Additionally, staying up-to-date with the latest advancements in GPU technology and programming languages can also help in improving your skills in this field.

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