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The Theory: CUDA from the Hardware Point of View

Nvidia's CUDA: The End of the CPU?
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If you’re a faithful reader of Tom’s Hardware, the architecture of the latest Nvidia GPUs won’t be unfamiliar to you. If not, we advise you to do a little homework. With CUDA, Nvidia presents its architecture in a slightly different way and exposes certain details that hadn’t been revealed before now.

nvidia CUDA

As you can see above, Nvidia’s Shader Core is made up of several clusters Nvidia calls Texture Processor Clusters. An 8800GTX, for example, has eight clusters, an 8800GTS six, and so on. Each cluster, in fact, is made up of a texture unit and two streaming multiprocessors. These processors consist of a front end that reads/decodes and launches instructions and a backend made up of a group of eight calculating units and two SFUs (Super Function Units) where the instructions are executed in SIMD fashion: The same instruction is applied to all the threads in the warp. Nvidia calls this mode of execution SIMT (for single instruction multiple threads). It’s important to point out that the backend operates at double the frequency of the front end. In practice, then, the part that executes the instructions appears to be twice as “wide” as it actually is (that is, as a 16-way SIMD unit instead of an eight-way one). The streaming multiprocessors’ operating mode is as follows: At each cycle, a warp ready for execution is selected by the front end, which launches execution of an instruction. To apply the instruction to all 32 threads in the warp, the backend will take four cycles, but since it operates at double the frequency of the front end, from its point of view only two cycles will be executed. So, to avoid having the front end remain unused for one cycle and to maximize the use of the hardware, the ideal is to alternate types of instructions every cycle – a classic instruction for one cycle and an SFU instruction for the other.

Each multiprocessor also has certain amount of resources that should be understood in order to make the best use of them. They have a small memory area called Shared Memory with a size of 16 KB per multiprocessor. This is not a cache memory – the programmer has a free hand in its management. As such, it’s like the Local Store of the SPUs on Cell processors. This detail is particularly interesting, and demonstrates the fact that CUDA is indeed a set of software and hardware technologies. This memory area is not used for pixel shaders – as Nvidia says, tongue in cheek, “We dislike pixels talking to each other.”

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  • 0 Hide
    Anonymous , June 18, 2008 5:03 AM
    CUDA software enables GPUs to do tasks normally reserved for CPUs. We look at how it works and its real and potential performance advantages.

    Nvidia's CUDA: The End of the CPU? : Read more
  • 8 Hide
    Anonymous , June 18, 2008 8:31 AM
    Well if the technology was used just to play games yes, it would be crap tech, spending billions just so we can play quake doesnt make much sense ;) 
  • -5 Hide
    dariushro , June 18, 2008 9:59 AM
    The Best thing that could happen is for M$ to release an API similar to DirextX for developers. That way both ATI and NVidia can support the API.
  • 0 Hide
    dmuir , June 18, 2008 10:44 AM
    And no mention of OpenCL? I guess there's not a lot of details about it yet, but I find it surprising that you look to M$ for a unified API (who have no plans to do so that we know of), when Apple has already announced that they'll be releasing one next year. (unless I've totally misunderstood things...)
  • 1 Hide
    neodude007 , June 18, 2008 12:56 PM
    Im not gonna bother reading this article, I just thought the title was funny seeing as how Nvidia claims CUDA in NO way replaces the CPU and that is simply not their goal.
  • -3 Hide
    LazyGarfield , June 18, 2008 1:44 PM
    I´d like it better if DirectX wouldnt be used.

    Anyways, NV wants to sell cuda, so why would they change to DX ,-)
  • -3 Hide
    Anonymous , June 18, 2008 1:57 PM
    I think the best way to go for MS is announce to support OpenCL like Apple. That way it will make things a lot easier for the developers and it makes MS look good to support the oen standard.
  • 1 Hide
    Shadow703793 , June 18, 2008 1:58 PM
    Mr RobotoVery interesting. I'm anxiously awaiting the RapiHD video encoder. Everyone knows how long it takes to encode a standard definition video, let alone an HD or multiple HD videos. If a 10x speedup can materialize from the CUDA API, lets just say it's more than welcome.I understand from the launch if the GTX280 and GTX260 that Nvidia has a broader outlook for the use of these GPU's. However I don't buy it fully especially when they cost so much to manufacture and use so much power. The GTX http://en.wikipedia.org/wiki/Gore-Tex 280 has been reported as using upwards of 300w. That doesn't translate to that much money in electrical bills over a span of a year but never the less it's still moving backwards. Also don't expect the GTX series to come down in price anytime soon. The 8800GTX and it's 384 Bit bus is a prime example of how much these devices cost to make. Unless CUDA becomes standardized it's just another niche product fighting against other niche products from ATI and Intel.On the other hand though, I was reading on Anand Tech that Nvidia is sticking 4 of these cards (each with 4GB RAM) in a 1U formfactor using CUDA to create ultra cheap Super Computers. For the scientific community this may be just what they're looking for. Maybe I was misled into believing that these cards were for gaming and anything else would be an added benefit. With the price and power consumption this makes much more sense now.

    Agreed. Also I predict in a few years we will have a Linux distro that will run mostly on a GPU.
  • 0 Hide
    kelfen , June 18, 2008 2:40 PM
    Well this is a huge step, hope to see it successful.
  • 0 Hide
    LogicalError , June 18, 2008 2:48 PM
    FYI: Apple has been working with the Khronos group (the people behind OpenGL at the moment) to make an API called OpenCL which should do all the things that Cuda et al can do. Since it's not just Apple that's behind it, but also the Khronos group, it should be cross platform. So who knows.. maybe this is going to be the unifying API for this.. well, until Microsoft comes up with 'DirectC' ofcourse
  • -2 Hide
    Anonymous , June 18, 2008 3:00 PM
    the last page comments on how MS could come in and create a common API, this common API is already in process, its just that MS isn't part of it ;) 
    http://arstechnica.com/journals/apple.ars/2008/06/18/apple-joins-working-group-to-hammer-out-opencl-spec
  • -2 Hide
    Anonymous , June 18, 2008 3:32 PM
    I know that this is not too close to the article, but i hope that it is still not too OFF topic.
    I just have a question, and someone might answer it (the TH is full with smart guys). My problem is that there are too many misconceptions floating around in the net regarding CUDA and overall the whole GPGU businnes.
    I have seen somewhere, that these GPU's are able to do Double Precision floating point calculations, but personally i find this unlikely.
    Others say that you can take directly your parallel code writen in C or Fortran90, and adopt it to CUDA, because the standard stuff can run serial on the CPU and the most computationally expensive part parallel on the GPU. On top of that you can 'adress' or cummunicate with your GPU directly from a Fortran code with sort of system calls (i think this is BS).
    Quiet frankly, i have not found a site on which i can really rely on, where they show an example (source code and explanation) of how something like this could be done.
  • 0 Hide
    bf2gameplaya , June 18, 2008 4:38 PM
    I wish Intel and NVidia would get over themselves and co-operate and finally give total system performance that big ass boost it needs.

    Intel is wasting time ray-tracing on a CPU and NVidia is wasting frames by folding proteins on their GPU.

    "You're doing it wrong!"
  • -1 Hide
    Anonymous , June 18, 2008 5:09 PM
    No, the best would be if we got an open API, like OpenGL. I seriously do not want another DirectX locking me to MS >_
  • 0 Hide
    thr3ddy , June 18, 2008 6:10 PM
    @dariushro: That would quite possibly be the worst thing that could happen to GPGPU. Microsoft equals Windows and GPGPU and super computing is not Windows' strongest point (understatement).

    It would be better for a neutral party composed of GPGPU experts from different IHVs to initiate something like what you propose, more like what the OpenGL ARB creates, a specification.

    IHVs and other companies could then implement this standard on their own hardware, thus decentralizing development from the ISV. If you leave development of this type of technology up to Microsoft (or any other single developer) you'll end up with vendor lock-in, which is a Bad Thing, for all of us.

    Anyway, CUDA is great but not cross-platform compatible (Intel, AMD/ATI, etc.) which makes it impossible to implement in commercial software, unless a CPU-bound alternative is provided, which would defeat the purpose of the architecture.

    On a similar note: think of the choice between the PhysX SDK and Havok Physics. Do you want partial GPU accelerated physics supported by one brand (PhysX, NVIDIA G80+) or do you want to stay CPU-bound but have the same feature set regardless of the hardware (Havok)?
  • 0 Hide
    magnesious , June 18, 2008 6:39 PM
    If you had the patience to read this entire thing, I'd recommend you look at the CUDA programming guide(link) It's the same information, but less terse.

    Tom's also forgot to point out that development is possible via emulation (emuDebug build setting, I think, with the .vcproj they give you), so anyone can get their hands dirty with the API. You don't get the satisfaction of seeing cool speedups, but it's just as educational, and easier to debug. No screen flickers :) 
  • 0 Hide
    MxM , June 18, 2008 7:21 PM
    I wonder if a PC can be build today without processor at all? It probably requires different BIOS for mobo and some kind of x86 emulator for NVIDIA card, but is it possible in principle without any modifications in hardware?
  • 0 Hide
    godmodder , June 18, 2008 8:55 PM
    The end of the CPU is nowhere near. To think the GPU could be used for every task is just absurd. The GPU is only good for tasks which can be massively parallellized. Unfortunately, not that many tasks, apart from graphical processing, can be divided into smaller, completely independent parts.
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