Earlier this month, the OpenCL specification was released by the Khronos group. Khronos is a group made up of representatives from companies in the computing industry. The group focuses on creating and managing standards for graphics, multimedia and parallel computing on everything from mobile devices to desktop and workstation computers. Part of Khronos' charge is OpenGL and all it's relatives with the Open- prefix, so naming also makes sense.



The goal of OpenCL is to make certain types of parallel programming easier and to provide vendor agnostic hardware accelerated parallel execution of code. That's a bit of a mouth full, but the bottom line is that OpenCL will give developers a common set of easy to use tools to use to take advantage of any device with an OpenCL driver (processors, graphics cards, ect.) for the processing of parallel code.

While there are already tools available that enable parallel processing, these tools are largely dedicated to task parallel models. The task parallel model is built around the idea that parallelism can be extracted by constructing threads that each have their own goal or task to complete. While most parallel programming is task parallel, there is another form of parallelism that can greatly benefit from a different model.

In contrast to the task parallel model, data parallel programming runs the same block of code on hundreds (or thousands or millions or ...) of data points. Whereas my video game may have threads for handling AI, physics, audio, game state, rendering, and possibly more finely grained tasks if I'm up to the challenge, a data parallel program to do something like image processing may spawn millions of threads to do the processing on each pixel. The way these threads are actually grouped and handled will depend on both the way the program is written and the hardware the program is running on.



As we've said many times in the past, graphics is almost infinitely parallelizable. Millions of pixels on the screen can all act (mostly) independently of each other. Light weight threads handle the calculation of everything that has to do with a particular pixel. As pixels get smaller and we pack more on screens, there is more opportunity for parallel work. Graphics cards are currently the best data parallel processing engines we have available. And once OpenCL drivers are available, developers will have access to all that horsepower for any other data parallel tasks they see fit.

Now, it won't make sense to run a word processor on your graphics card, as there just isn't enough happening at once to take advantage of the hardware. Single threaded performance on a GPU isn't that great, especially compared to a general purpose CPU, and trying to run code that isn't massively parallel just isn't going to be a great idea. But there are plenty of things that can benefit from the GPU. Basically any multimedia processing can benefit, from video and audio decoding, editing, and encoding, to image manipulation, to helping speed up your math homework (brute force computation ala Maple, Matlab, and Mathematica could certainly benefit from the GPU). There could be some interesting encryption and/or compression techniques that are born out of the data parallel approach as well.

The best applications of data parallel computing have likely not been seriously considered at this point, as it takes time to get from the availability of tools to the finished product, let alone the conception of ideas that have heretofore been precluded by the realities of parallel programming. But OpenCL isn't a miracle that will make everything speed up. Rather it is a vehicle by which developers will be able to make a small subset of tasks orders of magnitude faster using hardware that is already in most people's computers. Which is certainly nice. But let's take a closer look.

Parallel Computing: Why We Need OpenCL


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  • yyrkoon - Saturday, January 03, 2009 - link

    Apparently I *am* more knowledgeable than some here. How you can twist the context of comments to your misguided reasoning ( that I favor Microsoft ) is beyond me. Do I prefer Windows to OSX ? Yes. Why? Because maybe Microsoft is not perfect, but at least they do not force unwanted hardware on me to use their software.

    Windows is the only real gaming OS. Period. And I suppose my comment about Cross platform applications, and other good strong possible uses in a *NIX environment fell on deaf ears too( uses for OpenCL ).

    There is nothing wrong with OSX, it is after all based on BSD. However I will not over pay for hardware *just* to use it either. There are too many free operating systems that are just as good. If I need Windows application compatibility, I will just run Windows. Apple offers me *nothing* I have to have.

    Now, who here is truly blind ?

  • melgross - Saturday, January 03, 2009 - link

    You just want to think you are.

    You have gaming on the brain. I guess you must BE a gamer as that's all they think about anyway.
  • Penti - Saturday, January 03, 2009 - link

    Really who cares about the gaming? This isn't a physics framework or engine.

    It can be used in games, but this isn't really about a discussion on Apple gaming. That's not really why it can "speak" to each other.

    Apple got a lot of professional applications that today uses the open standard OpenGL like photo editing, video editing, VFX and others (scientific apps etc) on their platform, for not only graphics but for gpgpu, from not only them selfs but from vendors such as Adobe and Avid. Most of the apps also use OpenGL for acceleration in Windows too. Besides that, OpenCL will be available for handheld devices such as mobile phones. Even though Microsoft does software for phones you won't see DX11 or GPGPU there. Not that I'm an Apple fanboy, but I can see why Apple builds on what's already around and extends OpenGL and free standards. They can't rely on close standards, most of their apps (other vendors for OS X) are to some degree cross platform as they should be. CUDA is already available on the Mac too. But you can't expect them to run DX. This isn't about Apple as an OEM either. It's about software (Microsoft does hardware too). It's engineered to fit a wider picture and a wider array of devices including Windows, there isn't anything bad about that. There isn't anything bad about getting consumer and professional apps a boost in using GPGPU. It's certainly what some ISVs want. Theres more then gaming in the world. Microsoft are free to do whatever and nobody has said that they aren't best on games, but people are also free to criticizes and complain about Microsoft, just as they are about Apple and there certainly is a lot to be criticizing both about. Apple for certain can't just be catering to it selfs, not when they and their software vendors want something else. Microsoft essentially can. As most are already deeply invested in Microsoft tech and soft. That doesn't mean Windows users can't benefit from the Apple developed OpenCL. Their certainly is Windows only apps that will use it. Even non OpenGL ones. It's not only a cross platform library.
  • Atechie - Friday, January 02, 2009 - link

    Drop the Apple-preaching, it's uninteresting as Apple is neither HPC nor the mainstay platform for CUDA/Brook+/OpenCL.

    .oO(I swear, Apple-jocks are like religious zealots, they can stop pushing their religion down everbody elses throat...interested or not.)
  • melgross - Saturday, January 03, 2009 - link

    Yeah, just like people like you who do the opposite?

    Why mention the company who did all the work, as long as it's Apple? Right? That' makes people fanboys if we think a proper mention should be made?
  • Shadowself - Friday, January 02, 2009 - link

    So anyone says anything positive about Apple and immediately that equates to being an Apple zealot? It appears more likely that your personal bias is showing.

    It is absolutely true that Apple's Mac has NEVER been a gamer's platform -- and it probably never will be. Additionally, Apple has never fully supported (or even properly supported, IMHO) any development other than their core groups (K-12, Undergraduate to some extent, graphics and motion picture artist communities, and publishing). Thus Apple supports low to mid range graphics card and very high end 3D cards -- but absolutely nothing for the moderate to high end gamer.

    However, Apple did do the vast majority of OpenCL before submitting it to become an open standard. Apple wants to expand its role in the graphics and motion picture communities. The only way to do this was to do something like OpenCL. Additionally, Apple knew that a completely closed set of APIs was not going to gain any traction. Thus they submitted it as an open standard and gave up control of it.

    Not mentioning that Apple did the majority of OpenCL is wrong. For anyone to claim Apple did this altruistically is wrong. To bash Apple for coming up with something that has become a cross platform standard that can utilize both AMD and nVidia cards as well as a host of other hardware is wrong.
  • yyrkoon - Thursday, January 01, 2009 - link

    I never said it wasn't true. Let us just say that I am less than inspired to even bother looking. OpenGL is very low on my personal list of priorities, and I could care less what Apple does( unless perhaps if someday they compete head to head with Microsoft ).

    Still, no matter how much I like or dislike OpenCL, chances are pretty good that on Windows platforms, it is going to be rendered( pun? ) moot. Maybe it will make the next greatest XGL even more powerful, so all those people who like to play with their application windows in linux can spend all day every day bragging/ making youtube videos about how their desktop UI can do *this*, and *that* while remaining even less productive than before ; )

    Yes, the above is sarcasm to some extent, but it also true to an extent as well. OpenCL will help those who prefer and alternative to Windows do similar things without having to own Windows. Scientists who want to use GPGPU(s) to crunch some serious numbers, etc. What it will not do however is make the majority of gamers out there happy. *Unless* the majority of game developers start using OpenGL/CL on the Windows platform( Which is very unlikely ). Certain cross platform applications however could benefit, sure.
  • Penti - Friday, January 02, 2009 - link

    So OpenCL and OpenGL is bad because it's cross platform and open standard? If you look at who's involved you see companies like ARM and embedded computing companies, they can't really use anything like DX11. This isn't just for games but GPGPU in general.

    It's not like there isn't apps using OpenGL on Windows either. But it's rather about a broader spectrum then owning or not owning Windows. It's for a wider category of devices then DX11 is. You won't have DX11 cellphones. But you will have OpenCL on the next gen Sony and Nintendo consoles, handhelds, settopboxes etc. In HPC too, there will be libraries/frameworks to help you out.

    Of course theres professional apps such as Photo-editing, video-editing and encoding, VFX, CAD / GIS, math and other engineering software that could benefit widely from Open CL. And a lot of them are cross-platform. Or at least would need the OpenCL on for example the Mac. Where they might have many customers.
  • kevinkreiser - Wednesday, December 31, 2008 - link

    a while back i published a paper that involved performing an iterative deconvolution on the GPU. the point of the paper was that we could do it in real-time and use it on videos with arbitrary spatially varying blur kernels.

    anyway the largest overhead was copying the render target (single iteration of the algorithm) to initialize the next iteration. if dx11 and opencl allow the gpu and cpu to work with the same memory, without the need to copy between the two, this will speed up gpgpu apps tremendously.
  • has407 - Monday, January 12, 2009 - link

    OpenCL itself is neutral; it provides both explicit copy and map functions, in both synchronous and asynchronous forms. Obviously what works best will depend on platform capabilities and run-time intelligence (e.g., copy/map optimizations based on platform capabilities and program behavior).

    However, that still doesn't necessarily allow for a large mapped/shared memory between the CPU and CPU. That and its efficacy is going to be implementation dependent and OpenCL has simply defined a model that should be portable and useful, even if suboptimal on a given implementation--but if you know enough about the implementation, gives you sufficient optimization choices.

    That requires some constraints on the memory model, in particular the consistency/correctness of various memory regions with respect to computational elements at different points and times, and especially with respect to mapped memory (NB: sec of the spec).

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