Final Words

Both AMD and NVIDIA have touted the fact that as soon as they are able they will support OpenCL. Even though the specification has been released, it is not yet possible to claim OpenCL support because we don't yet have any qualification tests. NVIDIA and AMD will need to be able to correctly compile and execute OpenCL code and programs, and match results for calculations within certain tolerances. OpenCL drivers should start trickling out some time next quarter. Until then, developers do have access to the specification and header files so they can start playing with it as well.

Unfortunately, even if we had final drivers today we would have to wait for a quite some time before we see the first real apps trickle out. We expect a higher volume of consumer level applications than we've seen with CUDA, as there is greater incentive to develop using OpenCL. The fact that the vast majority of modern graphics cards will support OpenCL and the fact that the vast majority of computers have modern graphics cards installed means that once OpenCL drivers arrive developers will instantly have standardized and easy access to hundreds of times more compute power for general purpose processing of data parallel algorithms.

While AMD and NVIDIA will likely cary on their efforts with ATI Stream and CUDA, unless and until there is a language that can target all GPUs we are more likely to see OpenCL thrive. No matter how much easier it might be to leave all the overhead and management to the system or the driver, putting the power in the hands of the developer will always enable higher performance and more innovative usage of the hardware.

OpenCL Extending OpenGL
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  • v12v12 - Wednesday, January 07, 2009 - link

    Testing123, ignore plz Reply
  • corporategoon - Tuesday, January 06, 2009 - link

    Did this article go through an editor? Reply
  • chizow - Friday, January 02, 2009 - link

    Kind of surprising you didn't directly address this given the amount of FUD being thrown around with regards to PhysX, particularly from AMD and its supporters. You indirectly answered what I had already suspected however, that given Nvidia has stated they plan CUDA to be fully portable to both OpenCL and DX11 there should also be no portability issues for AMD and Brook+:

    quote:

    AMD could make an investment in the CUDA for C language and create either their own compiler (nothing is stopping them). But then you still have the same problem of interoperability as if NVIDIA implemented Brook+. If NVIDIA or AMD want to make their solution work with the other guy, they would need to write a wrapper to translate CAL to PTX or PTX to CAL.


    I'm guessing the unfinished thought from the first sentence should read something like "or write a CUDA to Brook+ wrapper" as thats essentially what the last part suggests. Since both vendors will write wrappers for their code to OpenCL, perhaps this wrapper could pull double duty, although it would double the amount of transcoding needed. Less than efficient for sure, but certainly better than a complete impasse due to incompatibility.


    Reply
  • ltcommanderdata - Friday, January 02, 2009 - link

    Are you suggesting that hardware PhysX acceleration will come to AMD GPUs as soon as nVidia and AMD enable hardware OpenCL support? Because I don't think it's that simple.

    nVidia seems to have rebranded the meaning of CUDA. Maybe it's all just marketing speak, but CUDA before seemed to mean using nVidia GPUs for GPGPUs operation in general. But now since OpenCL, CUDA seems to more specifically related to the GPGPU interface to nVidia GPUs with languages being separate on top, namely OpenCL, DX11 and C for CUDA. If PhysX is written in C for CUDA, which it no doubt is seeing there wasn't anything else available up to now, then adding support for the OpenCL language in the CUDA interface layer won't help get PhysX supported on AMD GPUs. PhysX will still be written in nVidia's proprietary language which AMD GPUs can't understand. To support AMD GPUs, either nVidia will have to rewrite PhysX from C for CUDA to OpenCL, which would be awfully generous of them or AMD will have to make a C for CUDA to CAL translator and hope PhysX doesn't have any nVidia hardware specific optimizations, which it no doubt has, to mess things up.
    Reply
  • apanloco - Friday, January 02, 2009 - link


    Anyone knows if multiple applications can take advantage of OpenCL at the same time? I think OpenGL is exclusive to one application, but if OpenCL is used by regular applications this could be a problem?
    Reply
  • yyrkoon - Thursday, January 01, 2009 - link

    "With R580 AMD (then ATI) actually published part of their ISA and called the initiative CTM (for Close to Metal). Before we had a beta version of CUDA, we had folding@home GPU accelerated on R520 and R580"

    I also read an interview through gamedev.net where ATI was emulating Direct 3D 10 calls in hardware on one of their x1900xtx's ( Direct 3D 9 hardware )long before I heard about folding@home on the GPU. I remember being so impressed with the technology, that I could not wait until Vista + Directx 10 titles became available. Too bad that there are so few ( if any ) titles that currently take advantage of this technology in the ways I had hoped. Hopefully that will change soon.
    Reply
  • ltcommanderdata - Thursday, January 01, 2009 - link

    http://www.tgdaily.com/content/view/38764/140/">http://www.tgdaily.com/content/view/38764/140/

    It's interesting that you mentioned that AMD and nVidia look to be continuing to push their proprietary GPGPU solutions, but AMD has actually made statements they are abandoning their proprietary CTM GPGPU implementation and are moving fully to OpenCL. Admittedly, its probably just a realization that CTM isn't taking off as fast as CUDA and it's in their best interest to push OpenCL. In comparison, nVidia will continue to develop their own CUDA implementation alongside OpenCL.

    I wonder if you can get a statement from nVidia whether they will move PhysX to OpenCL? Right now I believe PhysX is written in C for CUDA and of course requires nVidia GPUs for hardware acceleration. If they moved to OpenCL, then AMD GPUs would support it as well. Although perhaps nVidia prefers to keep PhysX to themselves as a product differentiator.

    It'd also be interesting if you could ask AMD whether older GPUs like the X1600, X1800, and X1900 will be supported in OpenCL? You already pointed out in your article that the RV530, R520, and R580 had GPGPU folding@home clients so they are certainly capable of GPGPU operation. It'd probably be in ATI's own interest to have as large an OpenCL base as possible and ATI's original FireStream dedicated GPGPU card was R580 based as well. Apple could probably help them as well seeing the number of X1600 and X1900 used in various iMac, MacBook Pro, and Mac Pro generations that could use support for OpenCL in Snow Leopard.

    And I agree with melgross that it's strange Apple got no mention in the article seeing that they pretty much developed OpenCL, then submitted it to Khronos, and was no doubt a major driving force behind the quick ratification in order to get it ready for Snow Leopard. And I believe Apple's Aaftab Munshi was the chair of the OpenCL working group.
    Reply
  • danger22 - Thursday, January 01, 2009 - link

    i am looking forward to the day when I can run my finite element simulations on my GPU. come on Ansys its time for a GPGPU Multiphysics! Reply
  • Amiga500 - Thursday, January 01, 2009 - link

    Same boat, same boat... with both CFD and FEA.

    Have you heard of FEAST-GPU (from Dortmund university)?

    Its a GPU accelerated FE package - unfortunately it isn't out in the public domain yet.



    Anyhow - from my own digging, I'm not sure if the CPU is a major bottleneck for FE simulations - a lot of what I see tends to point towards the hard-drive and I/O performance.
    Reply
  • Sheep100 - Sunday, January 04, 2009 - link

    If you provide enough RAM to the analysis you definitely end up CPU limited for single core runs. We have 24 - 32 GB per node for Abaqus and Nastran analyses. The nodes get RAM - bandwidth limited when stepping up the number of cores used or the number of concurrent runs on a node. We are looking forward to the core i7/Nehalem Xeon systems coming soon that will provide a big improvement here. (These codes run slower on Opteron cores.)

    GPGPU versions of Abaqus, Nastran & Ansys would be very interesting given the large memory bandwidth available on the high end cards. I suspect that re-writing & validating the various solver algorithms to target OpenCL would be a long process. I'm also unsure how possible it is to get data parallelism out of them since the scaling rate of Abaqus, for example, on multi-core systems, even with good bandwidth, is not anywhere near linear. Although this might just highlight the deficiency of the current method of extracting parallelism.
    Reply

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