[QUOTE=Manpowre;349834]please correct me, but the 590 doesnt use 365w with cuda. as there is overhead here. there is memcopy back to memory after the FFT operation, then there is memcopy to card again, then normalization etc.. so that doesnt put the card at 365w. more like 190w-200w.[/QUOTE]
Sorry, put TDP in there.

Can anybody explain what I did wrong here:
[URL="http://radikal.ru/fp/29f87ab6d36d4525a26be03132825a7d"][img]http://s005.radikal.ru/i210/1309/7e/f4dc98c7be0a.jpg[/img][/URL]
System: Win7 x64, 6Gb RAM, CUDA 5.5, Nvidia GeForce 780 with 980Mhz Core and 3Gb Memory.
This error appears sometimes, not often, but I can't be sure to leave my computer doing this task for a long time.
Is it wrong "-t" parameter? And which parapeters should I set in the ini-file?

[QUOTE=Nipal;352736]Can anybody explain what I did wrong here:
[URL="http://radikal.ru/fp/29f87ab6d36d4525a26be03132825a7d"][img]http://s005.radikal.ru/i210/1309/7e/f4dc98c7be0a.jpg[/img][/URL]
System: Win7 x64, 6Gb RAM, CUDA 5.5, Nvidia GeForce 780 with 980Mhz Core and 3Gb Memory.
This error appears sometimes, not often, but I can't be sure to leave my computer doing this task for a long time.
Is it wrong "-t" parameter? And which parapeters should I set in the ini-file?[/QUOTE]

Either your FFT is too small or your GPU is a little bit unstable. You might try choosing a larger FFT or underclocking your core GPU speed.

My GPU [U]must[/U] be stable. It was bought about a week ago, and it did many TF assignments when I was at work.
At first I moved savefiles away to get correct results.
I tried to enlarge a FFT (it was 5242880 and even 10485760) , but I get the same error almost immidiatly after program start. It always was like this: "iteration = 1001>=1000 && err = ........". I tried to change a number of threads to 1024, with the FFT=4194304 but there were no changes with ETA.
Could it be because of program is compiled for CUDA 4.2 and I have CUDA 5.5 installed?
Could it be because of I have no parameters set in ini-file?
If neither 1st nor 2nd, then what's wrong?

Probably the fft is too big. Try something closer to 3072000 for those exponents.

I let CuLu to decide which FFT to use. CuLu chose 3145728 and the [U]whole[/U] ETA is now less than one with FFT=4194304 and 6.5M+ completed iterations.
I'll leave them (CuLu and GPU) alone. ))
Thanks a lot for all your answers.

[QUOTE=Nipal;352759]My GPU [U]must[/U] be stable. It was bought about a week ago, and it did many TF assignments when I was at work.[/QUOTE]

Even when a GPU is perfectly stable for TF, it can be too unstable for LL. My GPU was like this when it was new, too. I had [URL="http://www.mersenneforum.org/showthread.php?t=17598"]similar questions[/URL] when I was new to GPUs. Read there for a lot of details about GPU stability, from the perspective of a newbie (me) and those more familiar with it.
I underclocked my memory, and overclocked my core, and ended up with an LL-stable GPU. (I misremembered earlier and stated something incorrect - it's the memory that most likely needs to be underclocked, not the core) The LL is highly sensitive to memory instability, unlike TF and graphics rendering. Graphics card memory is clocked/tested so that the memory is stable enough for graphics display, but that's not stable enough for LLs.

First of all, (sorry for repeating what other said, but this way it will be better stressed!) doing LL tests uses the card totally different comparing with doing TF. It must be that some card works perfect for one type of the task, but doesn't work for the other. If you have the Prime95 package (not only the exe), please read the last passage of the "stress.txt" file. That applies to GPU testing too.

Now, the best way to make use of your card is to tune the FFT by yourself. I had lots of cards in my hands, and there are no two alike. To tune the FFT, you just launch "cudaLucas -cufftbench from upto step" variation. Using a step of 8k or so, would be enough , but if you are maniac, then you can try a step of 1k (caution, "big" cards, with lots of memory and threads don't work in steps of 1k, but this doesn't matter really, for the tuning part). Then you copy the results down in an excel table, sort them by ratio between the length and the time spent, and delete those which "waste the time" (the ratio is 10-20 times bigger).

Then, for each range of exponents you test, the "error" is the best indicator in choosing the size of the FFT. You should choose the size which gives you the best time per iteration, but keeping the error between 0.01 and 0.2. Higher than this interval you will get rounding errors, lower you will get wrong sums. In the photo you linked, the FFT is way too big.

Alternating, you can have less headache and let cuLu chose the FFT length for you, for a penalty between 2% and 15% of the time, depending of the range of the expo you crunch. There are more information in the cuLu thread (with tables and so) if you are enough patient to go through those 160 pages... (it should be chronologically placed somewhere at the end of 2012, beginning of 2013, when cuLu had many changes from v1.66 to v2.04).

Nipal,

Sounds like you're hitting the same error titan owners hit early on.

Do you have the latest nvidia beta drivers installed?

The default ram speed seems to cause problems for predominately dual precision floating point (DPFP). DPFP is what cuda lucas and cudapm1 use. TF uses predominately integers.

The latest beta drivers fix this. I'm now currently running my titans with the default ram speed. Prior to the latest beta drivers, the only fix was to decrease ram speed on the GPU. I sugget to use MSI afterburner to modify clock speeds.

In the nvidia driver panel, there's an option to allow to use beta drivers. select this, then ask the app to check for latest updates, and it should give you the option to use driver version 326.80 or greater.

-- Craig

[QUOTE=nucleon;352966]Nipal,

Sounds like you're hitting the same error titan owners hit early on.

Do you have the latest nvidia beta drivers installed?

The default ram speed seems to cause problems for predominately dual precision floating point (DPFP). DPFP is what cuda lucas and cudapm1 use. TF uses predominately integers.

The latest beta drivers fix this. I'm now currently running my titans with the default ram speed. Prior to the latest beta drivers, the only fix was to decrease ram speed on the GPU. I sugget to use MSI afterburner to modify clock speeds.

In the nvidia driver panel, there's an option to allow to use beta drivers. select this, then ask the app to check for latest updates, and it should give you the option to use driver version 326.80 or greater.

-- Craig[/QUOTE]

Thanks. I will try tomorrow morning (MSK), when my first LL-test will be completed (that's the one with 3145728). Now everything is working absolutly correctly. It has a 5.0 ms/iter average speed and it's running almost round-the-clock (I stopped it sometimes manually to play a couple games :smile:).

"1 of your Lucas-Lehmer assignments have been tested by another worker. These are highlighted in red below with a dagger (†).Please understand when you turn in the results these will be credited as a Double Check by PrimeNet"
What that means? I speak english not very good, and even translators didn't help me.
1. Does that mean that this exp. was checked before me by someone else? (So how did I get it?)
2. Does that mean that this exp. was given to someone else to do DC-test? (Then I will be calm :smile:)

Upd:
53063159 |No factors below2^72
P-1 |B1=630000, B2=18585000
Unverified LL|CE05D844E88621__ by "Nipal" on 2013-09-15
[B]Assigned |LL testing to "ANONYMOUS" on 2013-08-31[/B]
History |no factor to 2^64 by "ANONYMOUS" on 2008-08-04
...
History |no factor for M53063159 from 2^71 to 2^72 [mfaktc 0.18 barrett79_mul32] by "Chuck" on 2012-02-06
History |ce05d844e88621__ by "Nipal" on 2013-09-15

As I can see this exp was given to "ANONYMOUS" [U]before[/U] me to do LL-test (I assigned it at 2013-09-09).
How can it be?