If you thought video conversion was time-intensive, wait until you look for aliens. Simply processing a single 373K file with a modern dual-core CPU took me nearly an hour and a half, a source:transcode time ratio of approximately 1:50. By default, the SETI@home benchmark only throws one work unit at a processor. With a dual-core chip, each core handles 50% of the load; with a quad-core, expect 25 percent. However, we want to see full utilization, so using the command benchcpu.bat 2 throws two instances at the processor, filling both cores.
You’ll notice that the CPU-only score on the 9800 GTX config is slightly lower than on the 9600 GT. This is merely within the statistical margin of variance. Additional runs show numbers that, averaged out, put the results about even.
There are two important take-aways here. First, check out the incredible runtime benefit CUDA delivers over CPU-only processing, requiring only 17% of the work time on a 9600 GT and only 11% of the time on a 9800 GTX. Consider how many years it typically takes to see such application performance leaps through CPU evolution alone.
Second, we clearly see the benefit of those extra stream processors in the 9800 GTX at play here. The 9800 GTX turns in a 50% superior performance over its cousin in the GPU-only tests. For $20, that’s one heck of a boost.
Since this was a synthetic benchmark, we weren’t as concerned about tracking CPU utilization during the GPU tests. If you’re curious, running our SETI@home tests on the CPU resulted, of course, in 100% use. The GPU test kept the CPU running around 50% to 60% utilization.
If you’d rather pursue disease cures than alien civilizations, we recommend running Folding@home. If you want to benchmark Folding@home, Nvidia recommends starting with the new OpenMM tool available right here.
As a fan of science and technology, I feel bound to point out that the SETI@home effort is under imminent threat of closure. The Arecibo radio telescope, the world’s largest single-dish telescope, is located in Puerto Rico and has been the source of all the data processed by the SETI@home project since 1999. Arecibo is run by Cornell University and receives funding from several sources, both public and private. Unfortunately, though, budget shortfalls have led the National Science Foundation to declare that Arecibo will close in 2011, possibly taking SETI@home offline with it, unless funding improves.