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Nvidia's CUDA: The End of the CPU?
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Table of contents
- 1 – Introduction
- 2 – Meanwhile...
- 3 – Vive le GeForce FX!
- 4 – The advent of GPGPU
- 5 – BrookGPU
- 6 – The CUDA APIs
- 7 – A Few Definitions
- 8 – The Theory: CUDA from the Hardware Point of View
- 9 – Hardware Point of View, Continued
- 10 – The Theory: CUDA from the Software Point of View
- 11 – In Practice
- 12 – Performance
- 13 – Analysis
- 14 – Conclusion
- 15 – Conclusion, Continued
- 16 – More on this topic
Let’s take a trip back in time – way back to 2003 when Intel and AMD became locked in a fierce struggle to offer increasingly powerful processors. In just a few years, clock speeds increased quickly as a result of that competition, especially with Intel’s release of its Pentium 4.
But the clock speed race would soon hit a wall. After riding the wave of sustained clock speed boosts (between 2001 and 2003 the Pentium 4’s clock speed doubled from 1.5 to 3 GHz), users now had to settle for improvements of a few measly megahertz that the chip makers managed to squeeze out (between 2003 and 2005 clock speeds only increased from 3 to 3.8 GHz).
Even architectures optimized for high clock speeds, like the Prescott, ran afoul of the problem, and for good reason: This time the challenge wasn’t simply an industrial one. The chip makers had simply come up against the laws of physics. Some observers were even prophesying the end of Moore’s Law. But that was far from being the case. While its original meaning has often been misinterpreted, the real subject of Moore’s Law was the number of transistors on a given surface area of silicon. And for a long time, the increase in the number of transistors in a CPU was accompanied by a concomitant increase in performance – which no doubt explains the confusion. But then, the situation became complicated. CPU architects had come up against the law of diminishing returns: The number of transistors that had to be added to achieve a given gain in performance was becoming ever greater and was headed for a dead end.
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- GPU Transcoding: Nvidia CUDA vs ATI AVT [Graphic & Displays]
- Badaboom Media Converter 1.1 Trial Now Available (CUDA) [Graphic & Displays]
- Nvidia To abondon Gaming World? [Graphic & Displays]
- Am I "silly" to feel more comfortable sticking w/Nvidia? [Graphic & Displays]
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Very 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 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.
CRAP "TECH"
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
Wow a gaming GFX into a serious work horse LMAO.
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.
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...)
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.
I´d like it better if DirectX wouldnt be used.
Anyways, NV wants to sell cuda, so why would they change to DX ,-)
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.
Very 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.
Well this is a huge step, hope to see it successful.
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
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/ap [...] pencl-spec
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.
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!"
No, the best would be if we got an open API, like OpenGL. I seriously do not want another DirectX locking me to MS >_
@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)?
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
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?
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.