NVIDIA v.s. ATI in Folding

We all know, that ATI is very good on paper in terms of theoretical TFLOPS and also very good in gaming and 3d graphics in general. Still, in folding, ATI lags badly behind NVIDIA. Many folders, using ATI cards, are looking forward to Directx 11 and new drivers, hoping to increase their performance. Possibly itss wishful thinking and NVIDIA is still be strong due to architecturaal differences. Here are few very good threads, analyzing this issue:



Shortly, ATI doesn’t have memory near GPU shaders to perform more complicated tasks (as folding) than graphics processing. NVIDIA has more sophisticated multi-level memory architecture, allowing to solve more complex tasks at GPU shader level.

If You ignore all the flaming here, the final thought is here:

Vaulter98c [H]ard|Gawd, 1.4 Year:
The problem isn’t that ATI GPUs can’t store “enough” data, it’s that they aren’t storing “any” data at all right now since F@H doesn’t use the LDS. And a single step of a single GPU workunit doesn’t require a particularly large amount of data storage, especially not with the small proteins that are currently being used for most of the workunits that are in the wild right now. Each shader unit (set of 4 standard FPUs and one special-function unit) has a 16KB LDS in RV770 and 32KB in RV870, which is more than enough to give a significant performance boost to overall work production speed.

Also very good (illustrated) blogpost about ATI GPGPU issue:


Please enjoy!


ADM not to improve folding performance with new models

AMD was the first video chip producer , who supported the client part of folding@Home project. It was possible to execute those calculations by AMD video chip since September 2006.  NVIDIA video cards joined the pack only in the summer of 2008.

Associates report that increase in the speed of folding@Home project in proportion to update of radeon model number  almost ceased. In particular, Radeon HD 4870 and Radeon HD 4870 X2 demonstrates close results, and newest video card radeon HD 5870 with 1 Gb  GDDR- 5 memories in this sense differed a little .

As experts explain, problem consists in the fact that the client program for Folding@Home is written in Brook+, and the new generation of AMD video card with directX 11 support counts on OpenCL. Thus developers will not renew the part client Of folding@Home, the use of NVIDIA card will provide higher results. Let us note that in other applications types GPGPU video chip AMD does not demonstrate a similar delay, this only a special case.

from Xtreview.