GPU Computing Performance

GPUs excel in highly parallel applications. Speedups between 10× and 100× have been observed in real-world applications.

Video Encoding

For video encoding, a 110-second clip encodes in 21 seconds on the GeForce GTX 280. The same clip takes 231 seconds on the fastest CPU.

Folding@Home

Folding@Home, the distributed-computing protein-folding application from Stanford University, runs more than 100× faster on the GPU than on the fastest CPU. Protein folding is measured in nanoseconds per day, or how many nanoseconds of the protein's life can be simulated in a day's worth of computing time. A GeForce GTX 280 can fold at 590 ns/day (up from the 511 ns/day discussed at Editor's Day in May 2008), compared to 4 ns/day on a CPU or 100 ns/day on the Playstation 3.

These results are based on the same protein and equivalent work units. At the time of this writing, a beta release of the GPU F@H client is available for Windows Vista users exclusively from Benchmark Reviews.

GPU Physics

Physics simulations are inherently parallel and run very well on the GPU. The table below shows common problems like cloth, soft bodies and fluid simulation. The GPU is on average is 11× faster than a quad core CPU on a preliminary implementation of the PhysX engine on the GPU.

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