Intro to GPU programming

Question

Everyone has this huge massively parallelized supercomputer on their desktop in the form of a graphics card GPU    What is the  hello world  equivalent of the GPU community  What do I do  where do I go  to get started programming the GPU for the major GPU vendors    -Adam

User · Accepted Answer

Check out CUDA by NVidia  IMO it s the easiest platform to do GPU programming  There are tons of cool materials to read  http   www nvidia com object cuda home html   Hello world would be to do any kind of calculation using GPU   Hope that helps

User · Answer

OpenCL is an effort to make a cross-platform library capable of programming code suitable for  among other things  GPUs   It allows one to write the code without knowing what GPU it will run on  thereby making it easier to use some of the GPU s power without targeting several types of GPU specifically   I suspect it s not as performant as native GPU code  or as native as the GPU manufacturers will allow  but the tradeoff can be worth it for some applications   It s still in its relatively early stages  1 1 as of this answer   but has gained some traction in the industry - for instance it is natively supported on OS X 10 5 and above

User · Answer

If you use MATLAB  it becomes pretty simple to use GPU s for technical computing  matrix computations and heavy math number crunching   I find it useful for uses of GPU cards outside of gaming  Check out the link below   http   www mathworks com discovery matlab-gpu html

User · Answer

OpenCL is an effort to make a cross-platform library capable of programming code suitable for  among other things  GPUs   It allows one to write the code without knowing what GPU it will run on  thereby making it easier to use some of the GPU s power without targeting several types of GPU specifically   I suspect it s not as performant as native GPU code  or as native as the GPU manufacturers will allow  but the tradeoff can be worth it for some applications   It s still in its relatively early stages  1 1 as of this answer   but has gained some traction in the industry - for instance it is natively supported on OS X 10 5 and above

User · Answer

Take a look at the ATI Stream Computing SDK  It is based on BrookGPU developed at Stanford   In the future all GPU work will be standardized using OpenCL  It s an Apple-sponsored initiative that will be graphics card vendor neutral

User · Answer

Another easy way to get into GPU programming  without getting into CUDA or OpenCL  is to do it via OpenACC   OpenACC works like OpenMP  with compiler directives  like  pragma acc kernels  to send work to the GPU  For example  if you have a big loop  only larger ones really benefit    int i  float a   2 0  float b 10000    pragma acc kernels for  i   0  i  lt  10000    i  b i    1 0f   pragma acc kernels for  i   0  i  lt  10000    i      b i    b i    a      Edit  unfortunately  only the PGI compiler really supports OpenACC right now  for NVIDIA GPU cards

User · Answer

You get programmable vertex and pixel shaders that allow execution  of code directly on the GPU to manipulate the buffers that are to be drawn  These languages  i e  OpenGL s GL Shader Lang and High Level Shader Lang and DirectX s equivalents    are C style syntax  and really easy to use  Some examples of HLSL can be found here for XNA game studio and Direct X  I don t have any decent GLSL references  but I m sure there are a lot around  These shader languages give an immense amount of power to manipulate what gets drawn at a per-vertex or per-pixel level  directly on the graphics card  making things like shadows  lighting  and bloom really easy to implement   The second thing that comes to mind is using openCL to code for the new lines of general purpose GPU s  I m not sure how to use this  but my understanding is that openCL gives you the beginnings of being able to access processors on both the graphics card and normal cpu  This is not mainstream technology yet  and seems to be driven by Apple  CUDA seems to be a hot topic  CUDA is nVidia s way of accessing the GPU power  Here are some intros

User · Answer

CUDA is an excellent framework to start with  It lets you write GPGPU kernels in C  The compiler will produce GPU microcode from your code and send everything that runs on the CPU to your regular compiler  It is NVIDIA only though and only works on 8-series cards or better  You can check out CUDA zone to see what can be done with it  There are some great demos in the CUDA SDK  The documentation that comes with the SDK is a pretty good starting point for actually writing code  It will walk you through writing a matrix multiplication kernel  which is a great place to begin

User · Answer

I think the others have answered your second question  As for the first  the  Hello World  of CUDA  I don t think there is a set standard  but personally  I d recommend a parallel adder  i e  a programme that sums N integers    If you look the  reduction  example in the NVIDIA SDK  the superficially simple task can be extended to demonstrate numerous CUDA considerations such as coalesced reads  memory bank conflicts and loop unrolling   See this presentation for more info   http   www gpgpu org sc2007 SC07 CUDA 5 Optimization Harris pdf

User · Answer

Take a look at the ATI Stream Computing SDK  It is based on BrookGPU developed at Stanford   In the future all GPU work will be standardized using OpenCL  It s an Apple-sponsored initiative that will be graphics card vendor neutral

User · Answer

Try GPU   and libSh  LibSh link has a good description of how they bound the programming language to the graphics primitives  and obviously  the primitives themselves   and GPU   describes what its all about  both with code examples

User · Answer

Another easy way to get into GPU programming  without getting into CUDA or OpenCL  is to do it via OpenACC   OpenACC works like OpenMP  with compiler directives  like  pragma acc kernels  to send work to the GPU  For example  if you have a big loop  only larger ones really benefit    int i  float a   2 0  float b 10000    pragma acc kernels for  i   0  i  lt  10000    i  b i    1 0f   pragma acc kernels for  i   0  i  lt  10000    i      b i    b i    a      Edit  unfortunately  only the PGI compiler really supports OpenACC right now  for NVIDIA GPU cards

User · Answer

CUDA is an excellent framework to start with  It lets you write GPGPU kernels in C  The compiler will produce GPU microcode from your code and send everything that runs on the CPU to your regular compiler  It is NVIDIA only though and only works on 8-series cards or better  You can check out CUDA zone to see what can be done with it  There are some great demos in the CUDA SDK  The documentation that comes with the SDK is a pretty good starting point for actually writing code  It will walk you through writing a matrix multiplication kernel  which is a great place to begin

User · Answer

You get programmable vertex and pixel shaders that allow execution  of code directly on the GPU to manipulate the buffers that are to be drawn  These languages  i e  OpenGL s GL Shader Lang and High Level Shader Lang and DirectX s equivalents    are C style syntax  and really easy to use  Some examples of HLSL can be found here for XNA game studio and Direct X  I don t have any decent GLSL references  but I m sure there are a lot around  These shader languages give an immense amount of power to manipulate what gets drawn at a per-vertex or per-pixel level  directly on the graphics card  making things like shadows  lighting  and bloom really easy to implement   The second thing that comes to mind is using openCL to code for the new lines of general purpose GPU s  I m not sure how to use this  but my understanding is that openCL gives you the beginnings of being able to access processors on both the graphics card and normal cpu  This is not mainstream technology yet  and seems to be driven by Apple  CUDA seems to be a hot topic  CUDA is nVidia s way of accessing the GPU power  Here are some intros

User · Answer

If you use MATLAB  it becomes pretty simple to use GPU s for technical computing  matrix computations and heavy math number crunching   I find it useful for uses of GPU cards outside of gaming  Check out the link below   http   www mathworks com discovery matlab-gpu html

User · Answer

Try GPU   and libSh  LibSh link has a good description of how they bound the programming language to the graphics primitives  and obviously  the primitives themselves   and GPU   describes what its all about  both with code examples

User · Answer

I think the others have answered your second question  As for the first  the  Hello World  of CUDA  I don t think there is a set standard  but personally  I d recommend a parallel adder  i e  a programme that sums N integers    If you look the  reduction  example in the NVIDIA SDK  the superficially simple task can be extended to demonstrate numerous CUDA considerations such as coalesced reads  memory bank conflicts and loop unrolling   See this presentation for more info   http   www gpgpu org sc2007 SC07 CUDA 5 Optimization Harris pdf

User · Answer

Take a look at the ATI Stream Computing SDK  It is based on BrookGPU developed at Stanford   In the future all GPU work will be standardized using OpenCL  It s an Apple-sponsored initiative that will be graphics card vendor neutral

User · Answer

You get programmable vertex and pixel shaders that allow execution  of code directly on the GPU to manipulate the buffers that are to be drawn  These languages  i e  OpenGL s GL Shader Lang and High Level Shader Lang and DirectX s equivalents    are C style syntax  and really easy to use  Some examples of HLSL can be found here for XNA game studio and Direct X  I don t have any decent GLSL references  but I m sure there are a lot around  These shader languages give an immense amount of power to manipulate what gets drawn at a per-vertex or per-pixel level  directly on the graphics card  making things like shadows  lighting  and bloom really easy to implement   The second thing that comes to mind is using openCL to code for the new lines of general purpose GPU s  I m not sure how to use this  but my understanding is that openCL gives you the beginnings of being able to access processors on both the graphics card and normal cpu  This is not mainstream technology yet  and seems to be driven by Apple  CUDA seems to be a hot topic  CUDA is nVidia s way of accessing the GPU power  Here are some intros

User · Answer

Take a look at the ATI Stream Computing SDK  It is based on BrookGPU developed at Stanford   In the future all GPU work will be standardized using OpenCL  It s an Apple-sponsored initiative that will be graphics card vendor neutral

User · Answer

You get programmable vertex and pixel shaders that allow execution  of code directly on the GPU to manipulate the buffers that are to be drawn  These languages  i e  OpenGL s GL Shader Lang and High Level Shader Lang and DirectX s equivalents    are C style syntax  and really easy to use  Some examples of HLSL can be found here for XNA game studio and Direct X  I don t have any decent GLSL references  but I m sure there are a lot around  These shader languages give an immense amount of power to manipulate what gets drawn at a per-vertex or per-pixel level  directly on the graphics card  making things like shadows  lighting  and bloom really easy to implement   The second thing that comes to mind is using openCL to code for the new lines of general purpose GPU s  I m not sure how to use this  but my understanding is that openCL gives you the beginnings of being able to access processors on both the graphics card and normal cpu  This is not mainstream technology yet  and seems to be driven by Apple  CUDA seems to be a hot topic  CUDA is nVidia s way of accessing the GPU power  Here are some intros

User · Answer

Try GPU   and libSh  LibSh link has a good description of how they bound the programming language to the graphics primitives  and obviously  the primitives themselves   and GPU   describes what its all about  both with code examples

User · Answer

I think the others have answered your second question  As for the first  the  Hello World  of CUDA  I don t think there is a set standard  but personally  I d recommend a parallel adder  i e  a programme that sums N integers    If you look the  reduction  example in the NVIDIA SDK  the superficially simple task can be extended to demonstrate numerous CUDA considerations such as coalesced reads  memory bank conflicts and loop unrolling   See this presentation for more info   http   www gpgpu org sc2007 SC07 CUDA 5 Optimization Harris pdf

User · Answer

CUDA is an excellent framework to start with  It lets you write GPGPU kernels in C  The compiler will produce GPU microcode from your code and send everything that runs on the CPU to your regular compiler  It is NVIDIA only though and only works on 8-series cards or better  You can check out CUDA zone to see what can be done with it  There are some great demos in the CUDA SDK  The documentation that comes with the SDK is a pretty good starting point for actually writing code  It will walk you through writing a matrix multiplication kernel  which is a great place to begin

User · Answer

I think the others have answered your second question  As for the first  the  Hello World  of CUDA  I don t think there is a set standard  but personally  I d recommend a parallel adder  i e  a programme that sums N integers    If you look the  reduction  example in the NVIDIA SDK  the superficially simple task can be extended to demonstrate numerous CUDA considerations such as coalesced reads  memory bank conflicts and loop unrolling   See this presentation for more info   http   www gpgpu org sc2007 SC07 CUDA 5 Optimization Harris pdf

User · Answer

Try GPU   and libSh  LibSh link has a good description of how they bound the programming language to the graphics primitives  and obviously  the primitives themselves   and GPU   describes what its all about  both with code examples

User · Answer

CUDA is an excellent framework to start with  It lets you write GPGPU kernels in C  The compiler will produce GPU microcode from your code and send everything that runs on the CPU to your regular compiler  It is NVIDIA only though and only works on 8-series cards or better  You can check out CUDA zone to see what can be done with it  There are some great demos in the CUDA SDK  The documentation that comes with the SDK is a pretty good starting point for actually writing code  It will walk you through writing a matrix multiplication kernel  which is a great place to begin

[gpu] Intro to GPU programming

Examples related to gpu