EVGA GeForce GTX 260 Core 216 Superclocked review - 15 - Compute Unified Device Architecture (CUDA) | Video transcoding

Compute Unified Device Architecture (CUDA)

As you guys know, ever since GeForce series 8 NVIDIA is getting pretty keen on is utilizing the GPU for functions other than rendering your games. Face it, the floating point parallel processing power of GPUs as shown today are humongous. There's a lot of potential doing other things rather than just gaming with your graphics cards.

So there's more to the GeForce GTX 200 series than playing games. More and more non-gaming related features are and can be offloaded towards the GPU. Roughly a year or two ago NVIDIA introduced CUDA. CUDA is a software layer that allows software developers to to 'speak' with the GPU and have it process data using your graphics card. This really is the most simple & basic description I can give it.

Taking it up a notch; still a very simplified explanation: if you can program in C++, chances are pretty good you'll be able to 'speak' to that GPU and get it to return data to you. Here's where we dive into what NVIDIA refers to as 'GPU Beyond' - The GPU evolving beyond graphics applications, beyond gaming. Some dry examples of what you can use the GPU for.

• Physics simulation
• Signal processing
• Computation
• Computational geometry, biology, chemistry, physics, finance.
• Data management

Now I know this all is very abstract, especially to explain. But for the years to come we'll start to see some pretty interesting applications that run over or get assisted by your GeForce GPU. The biggest problem with CUDA is that 99% of the CUDA application are specific to a company or internal projects, therefore that 99% of the software we never get to see. So it's very hard to understand for the end user, specifically the consumer, what CUDA can achieve with your graphics card. To keep it understandable I need to keep it real simple. And I will do so with explaining some examples of where CUDA can help.

Example 1: Transcoding Video on the GPU

Let's go to a more practical consumer application. Most of us have an iPhone, iTouch or iPod, right? I don't know about you but whenever I need to catch a flight, train or just traveling in general, I like to have some movies on my iTouch. My flights are sometimes inter-continental, and 10+ hour flights have to be the most boring thing ever. So to kill time I like to watch some hand-picked movies or tv-series on my iTouch.

Now if you know what I'm talking about, and do that on a regular basis too then you'll share my pain of transcoding video files. For example if you have a nice high-def movie you like to transcode towards an iPod (MP4) compatible format the PC with any modern processor will crunch that data for hours (depending on the source material of course) Example for my last trip I transcoded high-definition files towards an MP4 compatible format for my iTouch. My PC has been transcoding 10 GB of content and I think it took like 15 hours to do so. There's only one word for this, and that's nauseating.

So the problem at hand: if you like to fill that iPod with video content, your PC could be at work for a day easily. Quite annoying.

We recently got in contact with a company called Elimental. Among the applications they are working on, they have a piece of software called 'Badaboom media converter'. This company is working right now on several software applications that will manage the transcoding process over the GPU, and it does so with CUDA. Now here's the point I'm slowly working towards.

We've seen what it can do, and it's really interesting. Where a PC with a modern processor would take, say five hours to transcode. With the CUDA based Badaboom media converter (badabing? Sopranos? or is that my twisted mind?) you can cut down that time massively.

Fact is that once you transcode over the GPU instead of over the CPU, the speedup is significant. The software still is in development stages, but once released and 100% stable .. it'll rock your GPU.

Badaboom software ladies and gents. Keep an eye on them -  elementaltechnologies.com