[QUOTE=flashjh;293926]CuLu has come a long way. The assessment about the trial period is correct. We had a lot of testing for a while. Newer versions are stable and fast. Original DC took ~24 hours, now with 1.69 I can run a DC in ~15 hours. That's without specific code optimizations for CUDA and shader model.

As a side, I'm willing to do TF in the 332M range one we're caught up.[/QUOTE]

Too bad that my GTX285 must stay with version 1.3...

Luigi

[QUOTE=ET_;293931]Too bad that my GTX285 must stay with version 1.3...

Luigi[/QUOTE]

Why 1.3?

[QUOTE=chalsall;293906]However, I would really like to see a proper analysis done on where exactly the "curves cross" as far as how much TFing can a GPU do before it takes longer to find a factor than to run a LL test. I suspect, based on for example, [URL="http://www.gpu72.com/reports/worker/2423ae6e8f696d5e7d1447de91ca35a6/"]LaurV's[/URL] statistics, that it would actually be "profitable" to go at least one, perhaps two, additional bits, but it would be nice to have hard data rather than a gut feel.[/QUOTE]

This will be different for pre-Kepler vs Kepler. Most likely, Kepler will end up doing 1 more bit compared to the previous gens, since the relative DP/integer performance is much worse than others, thus favoring mfaktc over CUDALucas even more.

[QUOTE=chalsall;293914]Could you?[/QUOTE]I could. I'll need a wider variety of data samples than the single one I have. If anyone reading this thread could fire up CUDAlucas and PM/email me some iteration times for a variety of exponent sizes (at least 25M, 50M and 75M would be great). If possible, a variety of CUDAlucas versions would also be interesting. Naturally I'd also need to know what GPU you're using (and at what clock speed, if overclocked (whether factory or by yourself)).

[QUOTE=James Heinrich;293951]I could. I'll need a wider variety of data samples than the single one I have. If anyone reading this thread could fire up CUDAlucas and PM/email me some iteration times for a variety of exponent sizes (at least 25M, 50M and 75M would be great). If possible, a variety of CUDAlucas versions would also be interesting. Naturally I'd also need to know what GPU you're using (and at what clock speed, if overclocked (whether factory or by yourself)).[/QUOTE]

I will arrange to get some test results, with details.....in a bit. I just reconfigured my balance between CPU & GPU. I now have 4x P-1 on the CPU, and 1 each mfaktc and CuLu 1.69 on the GTX 460. I'm still observing that change. Once I have some idea how this is working, I'll do a run with CuLu sans mfaktc.

@James H., if you want other tests, just say so.

[QUOTE=kladner;293974]Once I have some idea how this is working, I'll do a run with CuLu sans mfaktc[/QUOTE]I don't need anything fancy. Really, just a 60-second test run of each exponent range would be fine, just give me the average per-iteration timing. No need to do a full run, I just need timings for assorted FFT sizes (25M, 50M, 75M should give me a good starting point).

Got it. I'll work on it soon.

Why such large sizes?

[QUOTE=James Heinrich;293976]..... I just need timings for assorted FFT sizes (25M, 50M, 75M should give me a good starting point).[/QUOTE]

Sorry. On reflection, I'm not sure now how to proceed. I've been studying, and experimenting with FFT sizes, but I don't really understand what to feed to CuLu to get the results you want. Does this correspond to exponent sizes in some way?

For FFT length, just type in 25*2^30, 50*2^30, etc... in full (decimal) form (Wolfram Alpha or google them). (I believe you specify length with -f. You can also just use -r to automatically test a whole bunch of sizes.)

[QUOTE=kladner;293982]Sorry. On reflection, I'm not sure now how to proceed. I've been studying, and experimenting with FFT sizes, but I don't really understand what to feed to CuLu to get the results you want. Does this correspond to exponent sizes in some way?[/QUOTE]

Using exponents in the ranges he suggests will end up using different FFTs, which is why he said to do 25/50/75M exps as an example.