Nvidia to Hit the x86 CPUs With CUDA Capability

[Guest]

for crying out loud will they just kill CUDA off and adopt OpenCL, then we can truly see nvidia vs AMD GPGPU

 

[liveonc]

Maybe this is just the easiest way to kill OpenCL, so ARM doesn't get too keen on selling everything non-Tegra...

 

[mister g]

Aren't today's CPUs mostly based on the x64 architecture? Pure x86 CPUs died off a few years ago.The x86 instructions will run but I don't think efficiently on todays CPUs (from both AMD and Intel, maybe even VIA).

 

[matt_b]

[citation][nom]LORD_ORION[/nom]OpenCL is owned by apple.[/citation]
Key word here being "open". Hence, no one company may "own" it. It is for all purposes, a collective effort by many of the top companies in the field to further create something that should be standardized rather than owned, licensed, controlled, and profited by one entity only. If I'm not mistaken though, Nvidia is already a participant anyway and has been, strange if they are in fact trying to compete against it now.

 

[Guest]

Could it possibly increase performance of a netbook with intel graphics?
Or is the program too heavy to load on these machines?

 

[megamanx00]

Oh, Cuda can be recompiled to run on different architectures? How exciting, wait, we already have something like that

IT'S CALLED C++!!!!!!!!!!!!

 

[jonnyboyC]

this is probably a great move for nvidia, now it's cuda programming language will become more widespread since it can be run on any system. Then with more programs using cuda, it will really give someone a reason to buy an nvidia gpu

 

[agnickolov]

[citation][nom]tu_illegalamigo[/nom]Do you still use IA64? I remember that netburst era stuff was awful on cpu intensive workloads. Hell, I can`t even find the ia64 version of 2003 server anymore.[/citation]
Microsoft just released Windows HPC Server 2008, but they no longer support Itanium. It's an executive decision, if they are wildly successful with HPC Server they may decide to try to aim for the bigger servers market again in the future.

 

[liveonc]

A great way of getting a bunch of Indian programmer w/o GeForce 8+ to make stuff, even though they can't use it very well on what they've got. As for OpenCL & NVIDIA not having anything against something they get to share with ARM, Apple, Ati, etc, etc... Why not help to let others help them with CUDA instead?

 

[DjEaZy]

... when?

 

[tu_illegalamigo]

Possibly, but Ia64 in my opinion is at the bottom with x86. ARM is a better choice for most server workloads now, except for cpu intensive, then it`s Opteron, or if you have the money Xeon.

 

[theoutbound]

I don't see this being all that useful unless x86 processor manufacturer star implementing CUDA on the cpu. Given that would cut into Nvidia's market I don't see it happening which means this won't make a big impact on DirectCompute or OpenCL.

 

[rohitbaran]

This sounds great, unless it is not a trick to make people believe that CPUs work slower on CUDA than GPUs (which they can do by making the software run slower on CPUs).

 

[danwat1234]

[citation][nom]bmadd[/nom]Whats the point of CUDA without a GPU? Multi core or not.[/citation]

Portability.

 

[Guest]

Forget the point about performance on CPUs. This move is very strategic for Nvidia embrace more from the gpgpu plataform, putting ATI (opencl) aside. How many apps do you see using OpenCL? And using CUDA? They're very serious about that.

Anyway, as CUDA can be ported to CPUs, CUDA can be ported to ATIs too. ATI could at least contract a 'outside' developer to create this driver, and give us this feature without need to give in.

 

[feeddagoat]

Physx running on CPU....properly!!! Seems completely backward from what Nvidia have been preaching but Im glad to see it. CUDA has a lot of potential and with CPU and GPU's being integrated this could be Nvidia's attempt at making CUDA survive until (if ever) they get a licence to build x86 processors.

 

[Gin Fushicho]

Awesome, Nvidia can spread CUDA out more, and hopefully they will improve it more often as well.

 

[dEAne]

It's quite a great chip for mission critical applications.

 

[coltnrg420]

GPU running a computer good idea that will send us in to the nest are of IT,im talking about running tare flops with a good os , like a cpu running windows xp where it is in the giga flops ,we need to invalve to a higher speed then maby we can work on that stupid lan line crap we by something thats a 10/100/1000 speed Ethernet that only gos maby 50 mgs top talk about over kill,i wish them luck, i wont something that can type faster then what im typing now ,lol more speed yes

 

[stasdm]

Afraid, the implementation will be same as with PhysX - just to compromise the idea and give more PR to the GPU-based solution

 

[stasdm]

Afraid, the implementation will be same as with PhysX - just to compromise the idea and give more PR to the GPU-based solution

 

[atikkur]

agree, this support is not more than a move to compete with opencl. programming with cuda is easier than with opencl. so, with this support that can run in cpu side, why not use cuda?

 

[eddieroolz]

I think this is a great move by NVidia.

 

[prakash85]

They want to popularize CUDA as much as possible by giving support to CPU as well. There is no advantage doing CUDA on CPU they just want to popularize that platform. So that there GPUs get performance advantage over ATI. NVIDIA is the most Wicked company in the world.

 

[pharrg]

nVidia already supports DirectCompute and OpenCL on thier hardware. They have whole sections of thier website and documentation for that. You can already choose to use either of those, or the CUDA extensions for C++ or Fortran as well, on all nVidia CUDA enabled hardware. It's your choice which you prefer to use, and which is best suited for your application (and skills). Obviously a 4 or 6 core cpu will never give any significant performance compare to hundreds of cores and tons of dedicated memory on a specialized board, or even a consumer class GTX graphics board. But, as previous comments have said, cpu support gives access to developers that otherwise wouldn't be able to use the tech, and allows use in some hardware situations that, while not ideal, at least would enable it. Thier hardware is not exclusive to CUDA, and now CUDA won't be exclusive to thier hardware. A lot also depends on what type of application you're developing and what type of calculations are being performed. Like anything, different things are better suited. But, if you're working with the ideally suited types of software, there is no comparison in performance when designed well. There are many examples where the same type of application and calulations are compiled and run on different hardware and development languages and the difference in speeds is sometimes simply staggering. You just need to choose what best suits your needs.