MilkyWay project has is supplying a client for GeForce processors. Nice, and the credit thruput is incredible. However, they are not providing enough information about the device being used (nvidia, ati or just the cpu) to be able to identify what was used for a particular task. Rather than rehash the problem, here is a link to the thread
http://milkyway.cs.rpi.edu/milkyway/forum_thread.php?id=1090

One consideration for MilkyWay -- their GPU support requires double precision GPU processors. That's a fairly small subset of GPU's.

For CUDA -- we're talking 260GTX and up, (the 250GS or the 9800GTX won't do).

For ATI -- we're talking 38xx, 47xx and 48xx cards only.

MilkyWay project has is supplying a client for GeForce processors. Nice, and the credit thruput is incredible. However, they are not providing enough information about the device being used (nvidia, ati or just the cpu) to be able to identify what was used for a particular task. Rather than rehash the problem, here is a link to the thread
http://milkyway.cs.rpi.edu/milkyway/forum_thread.php?id=1090

MilkyWay project has is supplying a client for GeForce processors. Nice, and the credit thruput is incredible.

It's not so incredible for nvidia GPUs :p

However, they are not providing enough information about the device being used (nvidia, ati or just the cpu) to be able to identify what was used for a particular task.

I have to partially disagree. At least the ATI versions have some quite extensive diagnostic output to the stderr.txt. Just an example (taken from the top host):

[quote<stderr_txt>
Running Milkyway@home ATI GPU application version 0.19g by Gipsel
allowing 4 concurrent WUs per GPU
setting minimum kernel frequency to 1 Hz
CPU: Intel(R) Core(TM) i7 CPU 920 @ 2.67GHz (8 cores/threads) 3.50007 GHz (1160ms)

CAL Runtime: 1.3.158
Found 4 CAL devices

Device 0: ATI Radeon HD 4800 (RV770) 512 MB local RAM (remote 2047 MB cached + 2047 MB uncached)
GPU core clock: 800 MHz, memory clock: 500 MHz
800 shader units organized in 10 SIMDs with 16 VLIW units (5-issue), wavefront size 64 threads
supporting double precision

Device 1: ATI Radeon HD 4800 (RV770) 512 MB local RAM (remote 2047 MB cached + 2047 MB uncached)
GPU core clock: 800 MHz, memory clock: 500 MHz
800 shader units organized in 10 SIMDs with 16 VLIW units (5-issue), wavefront size 64 threads
supporting double precision

Device 2: ATI Radeon HD 4800 (RV770) 512 MB local RAM (remote 2047 MB cached + 2047 MB uncached)
GPU core clock: 800 MHz, memory clock: 500 MHz
800 shader units organized in 10 SIMDs with 16 VLIW units (5-issue), wavefront size 64 threads
supporting double precision

Device 3: ATI Radeon HD 4800 (RV770) 512 MB local RAM (remote 2047 MB cached + 2047 MB uncached)
GPU core clock: 800 MHz, memory clock: 500 MHz
800 shader units organized in 10 SIMDs with 16 VLIW units (5-issue), wavefront size 64 threads
supporting double precision

4 WUs already running on GPU 0
4 WUs already running on GPU 1
3 WUs already running on GPU 2
4 WUs already running on GPU 3
Starting WU on GPU 2

main integral, 320 iterations
predicted runtime per iteration is 179 ms (1000 ms are allowed)
borders of the domains at 0 1600
Calculated about 9.89542e+012 floatingpoint ops on GPU, 1.23583e+008 on FPU. Approximate GPU time 66.5653 seconds.

probability calculation (stars)
Calculated about 3.34818e+009 floatingpoint ops on FPU.

WU completed.
CPU time: 2.65202 seconds, GPU time: 66.5653 seconds, wall clock time: 283.864 seconds, CPU frequency: 3.50007 GHz

</stderr_txt>[/quote]