Just finished an FAX4 on a GTX 460 1GB. Took 28 hours, and about 45-mins of pressing the retry button to get the WU to upload completely.

http://www.gpugrid.net/workunit.php?wuid=3278935

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Just finished an FAX4 on a GTX 460 1GB. Took 28 hours, and about 45-mins of pressing the retry button to get the WU to upload completely.

http://www.gpugrid.net/workunit.php?wuid=3278935

Well, 41,331.61 seconds on a GTX480, driven by an QX9650 CPU, running @ 3.5GHz.,
seems OK then. The card has 15 CUDA cores and 1532(?) MByte DRAM

Work unit 3323833.

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Knight Who Says Ni N!

I'm new and I've got 53 hours to do and it's also not crunching but saying the computer is in use I have an i5 processor and a Cuda GEFORCE 410 mobile and latest drivers, any suggestions?

Your GeForce 410 mobile is too slow for this project.

I've gone on to join World Community grid.

So you figure it out by yourself. At WCG your GPU will be useful.

WCG does NOT have any gpu units except those in Beta testing, which are VERY infrequent!!

just completed 2 'Paola' tasks which I have not seen before.
they were biggies!
http://www.gpugrid.net/result.php?resultid=5415785

http://www.gpugrid.net/result.php?resultid=5410160

ran consistenly at 90% GPU load. didn't check memory usage on them though.

this is on a 560ti 2gb @ 925

so current task
http://www.gpugrid.net/result.php?resultid=5418278

is using



currently showing a completion time of 19:04:00

bit longer than I would like, but it may come down in a few hours

Hi all,

I have submitted some new work units that will replace some I submitted earlier in the week. The names will be "NATHAN_FAX3". These tasks are in the true spirit of the long queue, and will take about 12+ hours on the fastest cards. Some have already been returned and indeed have been around 13 hours. This is markedly longer than what you have expected traditionally, but we really want the long queue to be for critical tasks, computationally intensive tasks, and the like. I suggest you all take note of how these tasks run on your computers and be mindful of temps and errors as you start to receive them.

I have noticed some crunchers expressing concern/dismay that perhaps they will not be able to get the 24h bonus with such long tasks. We are mindful of that concern, and will keep an eye on this group as an experiment. If we think it is too unfair to people with fast but not the fastest cards, we'll be sure to correct that in future groups. But the less send/recieve we have to do, the better. We are also mindful of the fact that longer tasks might be more susceptible to errors/crashes, and we want to see how this goes. I'll be looking out for the severe error percentage over the next few days for any problems.

Also, a note about tasks beginning with NATHAN_FA... These tasks are unique in that they are quite large simulations, compared to many others we have done in the past which are smaller (bigger biomolecules mean bigger simulations). They not only take longer per step, but require more memory. Cards with lower memory (below 1GB) may suffer additional performance loss. There is nothing we can do about this, unfortunately.

Happy crunching.

Nate

I really wish you wouldn't suck the last drop of blood out of my cards, they actually do have another purpose!!!

Not everyone can have dedicated machines or the latest and greatest cards for your benefit.

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I really wish you wouldn't suck the last drop of blood out of my cards, they actually do have another purpose!!!

Not everyone can have dedicated machines or the latest and greatest cards for your benefit.

Please read a little further into this thread to see where Nate describes how he hear's us and has reconfigured the tasks so they are now 66% of the project's optimum size to better suit us.

By far the GPUGrid team is much more in touch with and has shown an honest desire to collaborate with us crunchers than the vast majority of the BOINC projects (Go team GPUGrid !!!)

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Thanks - Steve

My problem with these units isn't how long they take but the amount of resources they use while running.

Or do you mean reduce resource demands to 66%?

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This area has been a bone of contention for years. It's about choice for the cruncher vs project management and overall project performance for the scientists. GPUGrid is an ever changing project. New faces, new research, new apps, new cards..., new problems and re-emerging old ones.

Firstly, it's fantastic that Nate has managed to utilize larger memory resources; most CC2.0 cards have >1GB GDDR5 memory, just waiting there to be used. In doing so Nate has expanded GPUGrid's research boundaries. This is a very important achievement in itself.

Perhaps in this case some sort of opt out is worth considering?
Crunchers could chose to opt out of a project if it requires more resources (GPU memory) than they have, if not having more memory actually slows performance significantly on such cards (512MB). The alternatives are crunchers choosing which tasks to crunch (a lot of work for the team) or aborting such tasks (bad for research). Of course this impacts on the recognition system too; if you don't crunch for a project you don't get recognition (a badge and links to that research), hence the opt out rather than an opt in suggestion.
It's also worth noting that the GTX460 (and similar CC2.1 cards) are not high end cards, and while they can complete long tasks in a reasonable length of time (<2days), they are perhaps more suited to the normal length tasks.
It might also be worth waiting and seeing how the CUDA4.0 or CUDA4.2 apps perform (if there will be a 15% performance boost for Nate's tasks, and if this will allow them to finish significantly faster, or not).

Thanks for your opinions on such matters,

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FAQ's

HOW TO:
- Opt out of Beta Tests
- Ask for Help

This area has been a bone of contention for years. It's about choice for the cruncher vs project management and overall project performance for the scientists. GPUGrid is an ever changing project. New faces, new research, new apps, new cards..., new problems and re-emerging old ones.

Firstly, it's fantastic that Nate has managed to utilize larger memory resources; most CC2.0 cards have >1GB GDDR5 memory, just waiting there to be used. In doing so Nate has expanded GPUGrid's research boundaries. This is a very important achievement in itself.

Perhaps in this case some sort of opt out is worth considering?
Crunchers could chose to opt out of a project if it requires more resources (GPU memory) than they have, if not having more memory actually slows performance significantly on such cards (512MB). The alternatives are crunchers choosing which tasks to crunch (a lot of work for the team) or aborting such tasks (bad for research). Of course this impacts on the recognition system too; if you don't crunch for a project you don't get recognition (a badge and links to that research), hence the opt out rather than an opt in suggestion.
It's also worth noting that the GTX460 (and similar CC2.1 cards) are not high end cards, and while they can complete long tasks in a reasonable length of time (<2days), they are perhaps more suited to the normal length tasks.
It might also be worth waiting and seeing how the CUDA4.0 or CUDA4.2 apps perform (if there will be a 15% performance boost for Nate's tasks, and if this will allow them to finish significantly faster, or not).

Thanks for your opinions on such matters,

Sorry SK, that looks like a copy and paste reply as you can see my GTX460's can do and return long tasks on time and have 1GB memory. They may not be "high end" but they often return results correctly when "high end" cards fail. Fact is in some cases Nathans units cause apps to run badly and only Nathans. Nothing against Nate but maybe his work should be "opt out"

EDIT TO ADD

It's worth bearing in mind that my 2 460's and I rank about 74th on this project if you exclude people like me how many "high end" "dedicated" crunchers are you going to be left with? Oh and please don't tell me to run shorties.

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I'm another that runs "not high end" cards, a GTX460 and a GTX550Ti and much prefer running long tasks.....I can live with the fact my 550 misses out on the 24Hr bonus most of the time, and on only a couple of occasions I have missed out on the full bonus the the 460.... once by a matter of seconds cos of the upload speed :-(

I am quite proud of the fact that my low cost setup has me sitting in the top 150 RAC wise

This area has been a bone of contention for years. It's about choice for the cruncher vs project management and overall project performance for the scientists. GPUGrid is an ever changing project. New faces, new research, new apps, new cards..., new problems and re-emerging old ones.

Firstly, it's fantastic that Nate has managed to utilize larger memory resources; most CC2.0 cards have >1GB GDDR5 memory, just waiting there to be used. In doing so Nate has expanded GPUGrid's research boundaries. This is a very important achievement in itself.

Perhaps in this case some sort of opt out is worth considering?
Crunchers could chose to opt out of a project if it requires more resources (GPU memory) than they have, if not having more memory actually slows performance significantly on such cards (512MB). The alternatives are crunchers choosing which tasks to crunch (a lot of work for the team) or aborting such tasks (bad for research). Of course this impacts on the recognition system too; if you don't crunch for a project you don't get recognition (a badge and links to that research), hence the opt out rather than an opt in suggestion.
It's also worth noting that the GTX460 (and similar CC2.1 cards) are not high end cards, and while they can complete long tasks in a reasonable length of time (<2days), they are perhaps more suited to the normal length tasks.
It might also be worth waiting and seeing how the CUDA4.0 or CUDA4.2 apps perform (if there will be a 15% performance boost for Nate's tasks, and if this will allow them to finish significantly faster, or not).

Thanks for your opinions on such matters,

It's much more complicated than that.... Although I only started here recently, I have done GPU contributions many other places.
That being said, I started here with a GTX460 (768 meg0 THAT NEVER CAME CLOSE TO 24 hrs ON ANY long run project. If any are in that case they are simply not running 24/7. We should not reassess long run projects for those not willing to do 24/7. They should be relegated to choosing regular projects. Maybe only allow the long projects based on % hours that a machine ID has had the project available?
I have been in positions over the years with my ability to contribute at varying levels. I know the feeling. We just need to keep in mind that the science "NEEDS" to trump our wants in projects. There are many options under Boinc. GPUGrid in any level that I can produce to meet my financial needs will always be my choice now. I'd never wish to slow it down just because I can't keep up.
Open dialog by the project will avert the debaucle that FAH is going through currently. WAS there , left there, all because of the way FAH handled their decisions.

I missed the point on this one!
By 'amount of resources' I thought there was an issue with the amount of memory required to run some of Nate's tasks (~624MB), highlighted earlier.
However, for Fermi's, that could only be an issue on some versions of the GTS450 and GT440. These cards can have 512MB, 1GB or 2GB. The GTX460 has 768 or 1GB, as pointed out, and the rest are 1GB or more. GTX460's have enough for a ~620MB task, and so far I have never had a task use >700MB at GPUGrid.
So I think the resource issue is the old lag one; GPUGrid tasks using the GPU in such a way as to prevents normal use of the system by the user. Typical observations include typing and scrolling lag.
So the possibilities are, aborting these tasks, not crunching with the GPU when using the system, running shorter tasks, crunching for other projects.
Potential possibilities might include altering the priorities, freeing up a CPU core (but probably not), using the motherboards built in GPU for display (sort of defeats the purpose of having a discrete GPU, but doable on some i7 systems), reducing the requirements of the task or having a tool that throttles the app.
I don't see anyone jumping at the idea of enabling an option to only use the GPU by SM count -1, but it's maybe worth considering.

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FAQ's

HOW TO:
- Opt out of Beta Tests
- Ask for Help

I don't know if that was meant for my previous post or not... But good explanation of things I was not aware of :)
Still, Long projects regardless of GPUGrid or elsewhere, have always been (in my experience) more resource intensive. That being said, after replacing my GPUGrid system to have both GPU's 570's as opposed to 460 and 570 have made it possible to play World of warcraft while Both crunching long GPUGrid WU's and 12 cores of WCG without issue. Sure it slows the projects down a little but there is not a constantly noticeable "lag" while gaming on my 990X. And no failures of WU's since. This is the reason that I doubt the "lag" in computer use for simple surfing and such.
Just my experience. OBTW, did the same with 570 and 460 (768) minus the 570 project startup fails (not the 460)... Gaming or not.