Hacker News Board Hacker News, browsed like a classic message board
Live data from Hacker News

Ask HN: How to learn OpenCL

news.ycombinator.com

Post reply on HN
Print view View original

11–17 of 17 posts

Re: Ask HN: How to learn OpenCL

#11

Post by jhdevos »

jaffee wrote: post #6

If you're a complete beginner in data parallel programming, and you're having trouble finding good intro material for OpenCL, it might almost be worthwhile to check out CUDA instead. In terms of the programming model, OpenCL and CUDA are identical - significant differences don't come about until you start optimizing for specific devices. I learned CUDA first on my own, and then took an OpenCL class and found that the…

To add some reasons why you'd want to learn CUDA first: It turns out that simple things are a lot simpler, and take a lot less code, in Cuda than OpenCL. With Cuda, your kernel and host code will be close together in the same file. You'll need a /lot/ less boilerplate than are needed in OpenCL to accomplish even the most simple things. OpenCL exposes you to a lot more concepts, and a lot more extrinsic complexity, than Cuda. All this means just playing around a lot easier to do in Cuda.

Just take a look at some simple examples in both, and you'll quickly see what I mean. Even though I'm a fan of OpenCL because it is available on more platforms, Cuda is a lot better suited as a learning platform.

Re: Ask HN: How to learn OpenCL

#12

Post by exDM69 »

A word of warning: OpenCL, and heterogeneous computing in general, is very very difficult. It will take a lot of effort to get even the simplest hello world application working.

And when writing OpenCL, even you are using a single API to write code, if you want to get high performance you will need to rewrite parts of your application for each hardware you intend to run on if you want good performance. This is obvious since the code may end up running on Intel x86's or Intel, AMD or Nvidia GPU architectures which are all very different. If you're lucky, it's enough to rewrite your kernel code (the code running on the device). But you might also need changes to the host side code (running on the cpu) and make changes to the way you manage the memory and DMA transfers, etc.

Finally, when it comes to the basics, OpenCL is not too different from CUDA and there's a lot more material available on CUDA (because it's been around longer and is perhaps used a bit more). You should be able to pick up a book or a tutorial on CUDA and translate it to OpenCL without too much effort.

Finally, even though it may take quite a lot of learning to get started, parallel programming on GPUs is quite fun and it is very rewarding to see your code run with very high performance.

Re: Ask HN: How to learn OpenCL

#13

Post by pflanze »

I've started with this[1] blog post, then worked quite a bit on adding proper error checking to the example code to figure out why it failed :), now the author has merged my changes. So perhaps it's a worthwhile example to start from now. I haven't done much with OpenCL yet, though, in the end I figured out that my ~7-8 year old laptop ran SIMD optimized C code faster on the host CPU than on the GPU (I wrote this[2] with heavy SIMD optimization work, not sure anymore whether this was what I tested against OpenCL though), which is a reason why.

[1] http://www.thebigblob.com/getting-started-with-opencl-and-gp... [2] https://github.com/pflanze/mandelbrot/tree/master/c

Re: Ask HN: How to learn OpenCL

#14

Post by tjaerv »

You might wish to check out the University of Illinois's "Heterogeneous Parallel Programming" course, offered through Coursera:

https://www.coursera.org/course/hetero

The course is already currently ongoing, but it's not too late to enroll. The course is mainly focused on CUDA (since it's easier to learn, the professor believes), but covers OpenCL as well.

Re: Ask HN: How to learn OpenCL

#15

Post by melonakos »

One great way to start is to use OpenCL libraries. We work on clMath (https://github.com/clMathLibraries) and ArrayFire (http://arrayfire.com) which are both easy to pick up. Once you get comfortable with libraries, you can start trying to write your own kernels, and you'll know which things you'll need to write that aren't already in a freely available library. Good luck!

Re: Ask HN: How to learn OpenCL

#16

Post by letzjuc »

Disclaimer: this is a rant, it is obvious that I don't like OpenCL and that I think that it was designed by monkeys so take it with a grain of salt.

In short: don't learn OpenCL. Both CUDA and C++AMP are good languages for programming heterogeneous machines and nVidia's Thrust and Microsoft's PPL are both excellent libraries to write efficient and reusable code. These language extensions are also strongly typed and come with really good tools. My advice is: learn any of them instead.

Why not OpenCL? AMD's Bolt library is the live proof that OpenCL is fxxxxx up beyond all repair. It is not meant for humans to write, nor for machines to understand.

Kernels are just character strings!!! This is just so wrong! Forget about using functors and lambdas as kernels, and forget about mixing kernels with templates. You will be better off using Python and PyOpenCL (which is great) that using C and C++. In C++ generating kernels is really hard, and generating kernels from expression templates is insanely hard.

Furthermore, this also means that the language is not typed at all!! Forgetting a semicolon in C results in a runtime error! Do you want syntax highlighting? Write your kernels in separate files! This is even worse than the way people used to write functors far away from the call site in C++03, at least they were in the same file!

As stated above my advice is don't learn it. Let it die. Your time is better spent learning CUDA/C++AMP and their libraries. The design rules for OpenCL have been "let's not learn anything from OpenGL" + "we need something, this is something, let's standarize this". This of course has resulted in an hilarious language that came after CUDA and was worse in every possible way.

Re: Ask HN: How to learn OpenCL

#17

Post by kylelutz »

If you're using C++, check out Boost.Compute [1]. It provides a high-level STL-like API for OpenCL (without preventing you from directly using the low-level OpenCL APIs). It simplifies common tasks such as copying data to/from the device and also provides a number of built-in algorithms (e.g. sorting/reducing/transforming, etc).

[1] https://github.com/kylelutz/compute

Post reply on HN