Cuda Challenge for x264 ... ?

[Sagittaire]

http://www.nvidia.fr/object/cuda_con...il2008_fr.html
http://www.nvidia.fr/content/EMEAI/C..._terms_fr.html

[Dark Shikari]

Avail Media is already working on CUDA for x264

[Yoshiyuki Blade]

I cant wait to see how that turns out. I hope my aging 8800GTX will have even more lasting value than it has already given me.

[lexor]

Originally Posted by Yoshiyuki Blade

I hope my aging 8800GTX

I hate you so much right now...

/me looks at his 6600gt with it's poor crackling fan and sighs

[Shinigami-Sama]

Originally Posted by lexor

I hate you so much right now...

/me looks at his 6600gt with it's poor crackling fan and sighs

I got all of you beat!
5200fx
first gen dx9!

it will be nice to see this nice looking stuff make it in x264
its definitely growing fast these days, kinda sad big commercial companies can't even compete still

[Inventive Software]

Yeah, Shinigami, except it cheated with DX9 and fell back to DX8.1 when it felt like it!

[DarkZell666]

Too bad, I switched from a Geforce 8600 GTS to a Radeon HD 3870 and I'm regretting I chose ATI, not only because of it's poor drivers and performance, but now even more so because of CUDA *Looks at his HD 3870 with an evil grin mwahahahaha*

[lucassp]

I think an ATi fanboy will make the same thing using CTM...it's just a matter of time.

[Sulik]

IIRC, CTM has been discontinued and is no longer officially supported.

[bob0r]

What is CUDA, I can't read french!
(And dont say google/wikpedia, doom9 is my bibble)

[lexor]

Originally Posted by bob0r

What is CUDA, I can't read french!
(And dont say google/wikpedia, doom9 is my bibble)

http://www.nvidia.com/object/cuda_learn.html

[Shinigami-Sama]

Originally Posted by lexor

http://www.nvidia.com/object/cuda_learn.html

so basicly C/++ CPU-GPU interaction/offloading for parallel computing no?

[lexor]

Originally Posted by Shinigami-Sama

so basicly C/++ CPU-GPU interaction/offloading for parallel computing no?

Yeah, from the example code they have on their site it seems they just provide an abstraction layer to programmers that unifies CPU and GPU. So you don't need to learn OpenGL or Direct3D, and worry about switching between CPU and GPU targets for your code, you just write what appears to be normal C++ with some new coding conventions (function and variable names), and compiler does the rest. And if it does it well enough you get profit

I think Sh commercialized by RapidMind (same developers) are the cross platform as well as CPU and GPU independent version of this (even supports PS3's Cell + GPU combo). Since last I checked RapidMind still offered their stuff for free for non-commercial use, maybe it will be a better code investment than CUDA? Especially since Sh devs have been at it longer than Nvidia.

[MfA]

Rapidmind is higher level ... with abstraction comes loss of performance, more severe with these kind of architectures than on a desktop processor which bristle with technology to make bad code run fast. I don't think you can freely download it anymore.

[BlackSharkfr]

I was curious so i read through a cuda introduction tutorial they have on their website. It's well written and easy to understand even for programming noobs like me.
i'd really like to see this technology being used in x264

Apprently they use the GPU as a giant SIMD co-processor :
.so it should be very usefull for video, since you often have to execute the same algorighm on a huge amount of pixels and/or macroblocks (especially in HD) simultaneously, but i don't know much about the x264 code so i can't really say which parts of the encoding process would benefit the most from the gpu.

using the cuda api (C/c++) seems simple, but in order to get the computations done "10/20/30/40/50/100+ times faster" (which is what they claim), you need to have massively parallelizable code without divergent branching, and then avoid bottlenecks caused by memory latency and the PCI-express bandwidth.

[MfA]

Highly irregular branching patterns (skip modes) and bit manipulation (quantization/entropy coding) don't suit present GPUs. IMO the only really good application at the moment are full search ME algorithms, in the end though accelerated full search is still slow even if it's faster than on the CPU. Because it has to do everything at single precision floating point it won't usually have 10x+ the performance of modern processors when you can use 8 or 16 bit on the CPU BTW. In pure arithmetic at usual precisions in x.264 it probably ties with a quad core ... it does have a lot more bandwidth though.

[Dark Shikari]

Originally Posted by MfA

Highly irregular branching patterns (skip modes) and bit manipulation (quantization/entropy coding) don't suit present GPUs. IMO the only really good application at the moment are full search ME algorithms, in the end though accelerated full search is still slow even if it's faster than on the CPU.

Actually, basically everything can be reasonably done on the GPU except CABAC (which could be done, it just couldn't be parallelized).

x264 CUDA will implement a fullpel and subpel ME algorithm initially; later on we could do something like RDO with a bit-cost approximation instead of CABAC.

Originally Posted by MfA

Because it has to do everything at single precision floating point

Wrong, CUDA supports integer math.

[MfA]

It supports integer math, but it doesn't support SIMD ... it's basically just not doing the renormalization.

[Dark Shikari]

Originally Posted by MfA

It supports integer math, but it doesn't support SIMD ... it's basically just not doing the renormalization.

Yes it does support SIMD. CUDA on an 8800GTX, for example, has 16 stream processors, each of which can perform 8 of the same arithmetic operation at the same time.

[MfA]

Seriously? Hmm, didn't notice that before ... I stand corrected.

PS. are you quite certain it can operate on uchar4 at 4 times the throughput as fp? (I don't have a g80 unfortunately.) I would have thought they would have made a bigger deal out of that if they could do it.

PPS. I think I worded it poorly the first time, I meant they can't do SIMD inside a "thread" (operations on vectors are simply iterated over the components) everything from 8 bits to 24 bits operations run on the same arithmetic units and at the same throughput. Whereas a CPU will get significant increase in throughput of arithmetic ops when using lower precision.