We've now started formal testing of GeneferOCL 3.3.0. Once 3.3.0 is live, we plan on removing the GeneferCUDA apps.

As far as we know, in all situations, GeneferOCL is faster than GeneferCUDA. The only reason for using GeneferCUDA was that GeneferCUDA wouldn't use a full CPU core. GeneferOCL would use a full core, under some circumstances. Since GeneferOCL 3.3.0 has fixed the problem with CPU hogging, there appears to be no reason to use GeneferCUDA anymore.

If you have a reason why we should keep GeneferCUDA, now is the time to speak up. Once we turn it off, it will be too late.
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Which GPU's does this make unable to run PrimeGrid?

Currently my older laptops with series Quadro FX 1600m, FX 2800m and FX3700m can all run CUDA WU's with minimal CPU usage.

When you move support R9 290/290X ???????

An interesting point regarding the older cards.

I just fired up the first test 65536 unit using both cuda and ocl on a mac with a 320m, and it did fine under the test ocl executable and the production oclcuda executable, aside from being painfully slow. That gpu is compute capability 1.2, however. I have a quadro 5600 and an 1800fx sitting in a drawer, and they are cc 1.0, if my memory serves me correctly.

Would there be any value in testing against these, at least for the shorter tasks, or do cuda's b limits put it in a catch-22 (can't run the shorter tasks, and the longer ones are just too long to be practical)?

An interesting point regarding the older cards.

I just fired up the first test 65536 unit using both cuda and ocl on a mac with a 320m, and it did fine under the test ocl executable and the production oclcuda executable, aside from being painfully slow. That gpu is compute capability 1.2, however. I have a quadro 5600 and an 1800fx sitting in a drawer, and they are cc 1.0, if my memory serves me correctly.

Would there be any value in testing against these, at least for the shorter tasks, or do cuda's b limits put it in a catch-22 (can't run the shorter tasks, and the longer ones are just too long to be practical)?

CUDA is only usable on n=21 and n=22 tasks, which are incredibly long computations for old, slow cards. A top-of-the-line GTX 280 takes about 10 days to run an n=22 task. Even older cards will take a lot longer.

Would the CUDA app be deleted and not being able to be found anywhere else, or would we just remove it from the selection page, storing it "in an archive" or something?

CUDA has not really been worked on since Yves came back and wrote the OCL apps. All improvements are only being performed on the OCL code; no changes are made to the CUDA code anymore.

It's unlikely -- bordering on impossible -- that CUDA would work better on any new architectures simply because OCL is the app that will be optimized for new architectures. Nobody's worked on CUDA for a few years now.

On Nvidia GPUs, the difference between CUDA and OCL is analogous to the difference between the "C" and "C++" languages. They both essentially do the same thing, in similar ways, but are somewhat different. (Ignore the object oriented stuff for the purposes of this analogy.) One isn't necessarily better than the other other, but they're different.

The reason GeneferOCL is faster than GeneferCUDA isn't because OCL is inherently faster on hardware X than is CUDA; it's because for the last two years Yves has been working hard at making Genefer faster, and he's working on GeneferOCL. GeneferCUDA is simply obsolete, and there seems to be no need anymore to maintain two different versions of what's essentially the same program. The last remaining reason for using GeneferCUDA (i.e., GeneferOCL hogging a CPU core) goes away with the 3.3.0 release of Genefer.
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All of my recent Genefer workunits were described as using OCLcuda rather than only CUDA or only OCL. Should I consider them as showing that both of my computers should be able to run the 3.30 OCL version?

Someone asked how to install ocl.

Replacing CUDA in favour of OCL (or whatever name you may use for it) seems to be the trend anyway too. POEM e.g. does ist the same way. I find less an less pure CUDA-Tasks (with low CPU-usage) within the world of BOINC.

After all considerations, giving up a core for solving numerous other problems seems very reasonable.

Replacing CUDA in favour of OCL (or whatever name you may use for it) seems to be the trend anyway too. POEM e.g. does ist the same way. I find less an less pure CUDA-Tasks (with low CPU-usage) within the world of BOINC.

After all considerations, giving up a core for solving numerous other problems seems very reasonable.

I am going to speak anecdotally here for a moment. I will also preface this by stating that I may have an unstable graphics card even though none of the traditional graphics benchmarks or games have any issue running. If you look at my profile you can see that I'll have a few units with errors from GFN-17MEGA, GFN-18 and GFN-19.

Running the OCL app for GFN-21 and GFN-22 causes my system to stutter so badly it becomes unusable. After a while, anywhere from a few minutes to a few hours, a BSOD will happen.
Today I decided to give the CUDA version of GFN-21 a go to see what would happen. As of this post it has been running for 25 minutes without the tiniest indication that anything is even happening as far as system usability and stability are concerned. It's running fantastically. I will, of course, have to see if it returns an error or not in about 60 hours.

This may be a reason for keeping CUDA around, but if the new OCL acts like the current CUDA then I have no objections.

I would assume if there were a hardware issue I would see errors on all GFN... But maybe not.

Could it be that the larger units are more hardware intensive which would expose an error that smaller units, games and benchmarks would not expose?

I am going to speak anecdotally here for a moment. I will also preface this by stating that I may have an unstable graphics card even though none of the traditional graphics benchmarks or games have any issue running. If you look at my profile you can see that I'll have a few units with errors from GFN-17MEGA, GFN-18 and GFN-19.

Running the OCL app for GFN-21 and GFN-22 causes my system to stutter so badly it becomes unusable. After a while, anywhere from a few minutes to a few hours, a BSOD will happen.
Today I decided to give the CUDA version of GFN-21 a go to see what would happen. As of this post it has been running for 25 minutes without the tiniest indication that anything is even happening as far as system usability and stability are concerned. It's running fantastically. I will, of course, have to see if it returns an error or not in about 60 hours.

This may be a reason for keeping CUDA around, but if the new OCL acts like the current CUDA then I have no objections.

Kieth, if screen lag is indeed a problem with OCL, then yours is the first response that's potentially useful to me. This is the first I've heard of anyone complaining about screen lag with OCL. Screen lag is common with CUDA, which is why we have a block size adjustment which lets you trade off performance for reduced screen lag.

There's no corresponding adjustment for OCL because there's been few if any complaints about it, and I'm not even sure if such an adjustment is possible with OCL. Because of the lack, or at least rarity, of such complaints, I'm wondering if the usability problems you're seeing are related to the other problems you're having with your GPU. It could be that there's an underlying problem causing both symptoms.

I shall have to drop BOINC, I simply can't afford yet more equipment, Sorry and Bye.

I shall have to drop BOINC, I simply can't afford yet more equipment, Sorry and Bye.

As soon as the WU expands it's memory requirement and leaves GPU dedicated RAM to use a pool of shared system RAM is when the BSODs start occurring on all 3 of my Dell Precision m6xxx series workstations. 6300, 6400 and 6500 all get BSoD in GFN-21/22 along with massive stuttering. It doesn't matter if it's OCL or CUDA.

Hi !

Just tried OCL app (GFN16) instead of CUDA with my Nvidia GT430 (no oc), compute capability = 2.1..
It's very fast !! 14min to get... an error while computing.

On Boinc's events, it's returning the results and then say that if I get errors repeatly I should reset the project.

Any advice ?
For now, I stay on CUDA.
Thanks.

I remember now, I switched to GFN CPU, I leave Sieve as CUDA's app.
Well, should I test first if GFN CUDA's working before testing OCL GFN app ?

I did had a previous GFN problem but I changed both system and hardware (but not the graphic card).

Before trying to fix something, do you think that if I run GFNcpu app with an Intel(R) Core(TM) i7-4770 CPU @ 3.40GHz, it's better than an old (CUDA or OCL) GPU GT430 ?

I keep my old GPU for easiest tasks (Sieve or other projects) then.

I should turn off hyperthreading ? What benefits ?

Just tried OCL app (GFN16) instead of CUDA with my Nvidia GT430 (no oc), compute capability = 2.1..
It's very fast !! 14min to get... an error while computing.

I do want to discover why it didn't.

I found another topic "LLR and HT", and it seems that it's only on Windows based system that makes a difference.

I read the announce of the end of CUDA as a warning that old type NVIDIA cards would be incapable of running the new system. I already have four NVIDIA and one AMD that get no work.

Upon reflection, I want to hear about the following three (maybe four) things, IF AND ONLY IF they apply to you. Any other posts will probably be hidden. I want to be able to see if anyone actually will be affected, so from now on I'm keeping this topic tightly focused on this narrow issue. Other posts will be hidden.


I want to know if...

1) You CAN run GeneferCUDA on N=21 or N=22 but CAN NOT run GeneferOCL on N=21 or N=22.

2) GeneferCUDA runs FASTER on N=21 or N=22 than GeneferOCL.

3) Screen lag is NOTICEABLY AND SIGNIFICANTLY WORSE with GeneferCOCL on N=21 or N=22 than with GeneferCUDA.

4) Any other valid reason why you want to use GeneferCUDA rather than GeneferOCL. I don't think there are any other reasons, but you may have one that I didn't think of. If it's off topic like most of the previous posts, your post will be hidden.


* Posts about GFN 15 through 20 will be hidden.

* Posts about ATI/AMD GPUs will be hidden.

* Posts about CPU apps will be hidden.

Please let's keep focused on this one question. Thank you!


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Please do not PM me with support questions. Ask on the forums instead. Thank you!

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As GeneferCUDA apps are about to be removed it becomes crucial for me to be able to run the GeneferOCL 3.3.0. apps. Currently they are all failing.
“Output file …. For task … absent”
I put a post in the Problem section.
Any assistance shall be greatly appreciated.

Yair

We will be turning off the CUDA apps in the next couple of days. The timing of this decision is due to the Nvidia driver bug -- we can't tell which CUDA tasks might be affected by the bug and which ones aren't.

This is the final notice -- it's time now to switch from CUDA to OCL. Please go to the preferences page and deselect CUDA, then select the OpenCL box that is immediately above the CUDA box. If you do that, you'll find that your GPU is likely processing tasks faster than before. In some cases, a lot faster. If you don't, you'll soon find that your GPU isn't getting any tasks.

This change only affects GFN-21 and GFN-22 (aka GFN-WR).
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Please do not PM me with support questions. Ask on the forums instead. Thank you!

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The GeneferCUDA apps are now deprecated.

The Genefer CUDA apps are no longer being sent out, and you can no longer select them on the PrimeGrid preferences page. If for some reason you still had CUDA selected for GFN-21 or GFN-22 you will need to select Nvidia OpenCL instead.

If you've got Genefer CUDA apps that are currently running, you may complete them if you wish. They will be accepted when returned to the server.

Please note that this does not affect ATI/AMD GPUs. It does not affect GFN-15 through GFN-20. It does not affect PPS-Sieve. It does not affect CPU apps.


____________
Please do not PM me with support questions. Ask on the forums instead. Thank you!

My lucky number is 75898⁵²⁴²⁸⁸+1