we found GT200 to be 41% faster per GFLOP than G9x, so the BOINC benchmark underestimates this influence (it could not possibly reflect it correctly unless it used the actual GPU-Grid code) we have a comparable list here, including prices (somewhat outdated) and some power consumption numbers That's quite some work you put into collecting this. If you want more details about an NVIDIA card look here, Even if it is already on the list, it will confirm the ratings, and help other people decide what graphics card they want to get. Include Card Name, Compute Capability (1.0, 1.1 or 1.3 for example), RAM and est. You can find them here Open Boinc (Advanced View), select the Messages Tab, about the 12th line down it will say CUDA Device. Please post your NATIVELY CLOCKED Boinc GFLOPS Ratings here, or any errors, to create a more complete list. Even with a 9600 GT (about 35GFLOPS) your computer would need to be on most of the time to get a good success/failure ratio. With a 20GFLOPS card most tasks will probably timeout. You may wish to attach to another project that uses a longer return deadline (Aqua-GPU for example). If you have a slower card (say under 10GFLOPS) don’t attach it to the GPU-Grid you are unlikely to finish any tasks in time, so you will not produce any results or get any points. If you overclock your Graphics card, you will probably get more performance, but you might get more errors and you will reduce the life expectancy of the card, motherboard and PSU - you probably know this already )
Mismatched pairs of PCIE cards will likely underperform. Some older cards may be PCI, Not PCI-E (PCI-E is faster)! The amount of RAM (typically 256MB, 384MB, 512MB, 768MB, 896MB and 1GB) will significantly affect performance (more is better)! Some older cards use DDR2 while newer cards predominately use DDR3 (DDR3 is about 20% to 50% faster but varies, faster is better)! You should also note the following if you’re buying a new card or thinking about attaching it to a CUDA project:ĭifferent cards have different numbers of shaders (the more the better)!ĭifferent speeds of shader and RAM will effect performance (these are sometimes factory over clocked and different manufacturers using the same GPU chipset and speed can tweak out slightly different performances)! The following are mostly compute capability 1.1: These are hopefully ALL Native scores only!ĬUDA card list with Boinc ratings in GFLOPS For those interested in buying a CUDA card or adding one to a GPU project, I collected some reported Boinc GPU ratings, added some I tested and create a Boinc GFLOPS performance list.
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