Wouldn't RFI, both generated and received, be an issue with an open frame?

Faraday cage perhaps? That should not impede airflow too much.

This is weird. My GTX780Ti working on a 75M exponent at 3.5 ms/iter uses 250 watts. According to the CUDALucas performance page, a GTX980 working on a 75M exponent at 7.4 ms/iter uses 165 watts. So my older card is more power efficient than the new GTX980 when running CUDALucas?

[QUOTE=stars10250;391888]This is weird. My GTX780Ti working on a 75M exponent at 3.5 ms/iter uses 250 watts. According to the CUDALucas performance page, a GTX980 working on a 75M exponent at 7.4 ms/iter uses 165 watts. So my older card is more power efficient than the new GTX980 when running CUDALucas?[/QUOTE]

Yep!

Perhaps there are improvements to be made with CUDALucas for the new Maxwell GPUs.

I have noticed that with my 980, when running cudalucas the power consumption is about 71 or 72%. So that is perhaps 120W.
With trial factoring the figure is 99%, so the full 165W.
(I've just run some iterations on 75000047 and I get timings of 7.75ms - I've not tried optimising the ini file settings)

The difference in power consumption is even more striking with my 750ti with cudalucas only using 20 to 30 Watts, ie 50% or less of full power consumption. Trial factoring on the 750ti uses 90%.
(Just for comparison, 75000047 gives an iteration time of 25.5ms)

My experience with a 460 and a 570 suggests that CuLu generates more heat than mfaktc. Your later model cards may be throttling on that account.

[QUOTE=kladner;391898]My experience with a 460 and a 570 suggests that CuLu generates more heat than mfaktc. Your later model cards may be throttling on that account.[/QUOTE]
That is normal, cudaLucas uses the memory, additional, compared with mfaktc which uses the same cores (well...:blush:), but uses no memory (see the GPU-Z, for example, for a quick view/comparison). In this respect, 580's are still in the best cards for LL (price/power/speed).

Roy_Sirl sees more gpu use for TF, LaurV says LL uses more resources. My experience has been both GTX780 and 780Ti use 99% (presumably 100%) gpu on either LL or TF, so maybe I'm optimized.

I still don't understand why the GTX980 efficiency is less though. Even if we consider 120W for 7.75 ms/iter...that's equivalent to 3.72 ms/iter for 250 watts which is slightly worse than the GTX780Ti at 3.5 ms/iter. The whole point of Maxwell was power efficiency, right? It must be a code issue.

[QUOTE=stars10250;392097]Roy_Sirl sees more gpu use for TF, LaurV says LL uses more resources. My experience has been both GTX780 and 780Ti use 99% (presumably 100%) gpu on either LL or TF, so maybe I'm optimized.

I still don't understand why the GTX980 efficiency is less though. Even if we consider 120W for 7.75 ms/iter...that's equivalent to 3.72 ms/iter for 250 watts which is slightly worse than the GTX780Ti at 3.5 ms/iter. The whole point of Maxwell was power efficiency, right? It must be a code issue.[/QUOTE]

No, it could be a hardware-design decision, specifically the relative efficiency of double-precision calculation to single-precision. The new generation may be vastly more power-efficient at single-precision, but no better at double. LL uses more double-precision calculations.

[QUOTE=VBCurtis;392098]No, it could be a hardware-design decision, specifically the relative efficiency of double-precision calculation to single-precision. The new generation may be vastly more power-efficient at single-precision, but no better at double. LL uses more double-precision calculations.[/QUOTE]

That makes sense. Maxwell has 1/32 FP64/FP32 performance versus Kepler's 1/16.

Perhaps code changes could be made to reduce CUDALucas's FP64 usage.

[QUOTE=stars10250;392097]Roy_Sirl sees more gpu use for TF, LaurV says LL uses more resources. My experience has been both GTX780 and 780Ti use 99% (presumably 100%) gpu on either LL or TF, so maybe I'm optimized.[/QUOTE]
How 'bout you install GPU-Z, (or your favorite tool), switch to the right tab and have a _good_ look to the bars (ALL bars, not only the core occupancy, but also memory use, memory transfers, etc), for both cudaLucas and mfaktc, and we talk after that?