Much of NVIDIA's recent marketing has centered around the notion that GPUs aren't just for gaming any longer, which you'd expect considering they've got a GPU architecture in their arsenal capable of 933 GFlops. Of course, we've known this to be true for quite some time, but there definitely seems to be more happening in the GPGPU arena as of late. During our briefing for the GeForce GTX 200 series architecture, for example, NVIDIA showed off a number of applications that all benefited from the power of a GPU, and none of them were games.
The application you see pictured above is a beta, pre-release version of Elemental Technologies’ BadaBOOM. BadaBOOM takes advantage of ETI’s GPU-powered RapiHD Video Platform to offload video encoding duties from the CPU, onto the GPU, to accelerate the process of converting standard-definition video from any format to H.264 for portable media devices, like an iPod, Zune, or iPhone. Using BadaBOOM and a GeForce GTX 280, we were able to encode an MPG of the digital short "The Plush Life" in only 24 seconds, at a rate of about 140 - 150 FPS. To give you a point a reference, it took an 8-Core Skulltrail rig almost twice as long to complete a similar encoding process using Nero Recode, at a rate of about 85 - 95 FPS.
NVIDIA, along with representatives from Stanford University, also took the opportunity to showcase a brand new version of the Folding @ Home client which used the GPU for its calculation. This version of the Folding @ Home client running on a GeForce GTX 280 can processes roughly 500ns / day. That is a massive speed increase compared to existing CPU and previous GPU architectures. A typical CPU can do about 4ns / day, a PS3 about 100, and Radeon HD 3870 approximately 170.
Of course we can't forget PhysX. If you remebmer, NVIDIA acquired AGEIA not too long ago and plans to incorporate PhysX support into all CUDA capable (GeForce 8, 9, and GTX 200 series) graphics card. While out an NVIDIA's Editor's Day even, we saw numerous demos in action and heard from representatives from NVIDIA and AGEIA. By all accounts, the relationship is going well and according to information given to us at the event, having NVIDIA's marketing muscle behind the technology has resulted in a number of new developers signing on to use the technology. Support for PhysX should be coming in a future driver revision, due out in a few weeks time.
Many other types of complex mathematical calculations are also well suited to GPU acceleration. To further demonstrate, we enlisted the help of a small application dubbed "GPUQuant" that performs Black & Scholes or Monte Carlo calculations on either a CPU or GPU. The results above speak for themselves. The new GeForce GTX 200 series architecture offers significantly more compute performance than any existing CPU or GPU for this type of calculation. We should point out, however, this application was NOT multi-threaded when running on a CPU, so theoretically similar calculations could perform at approximately 4x the rate shown above on a quad-core CPU, but even then it would still offer only a fraction of the throughput of the GPUs.