Tony’s long tasks seem to be running well and giving plenty of credit :) On my GTX470’s they complete in under 8h (XP x86, i7-920).

Run time 29089, Claimed credit 27186.875, Granted credit 40780.3125 task
Expected (24/7) daily credit from one (ref/stock) GTX470 = (86400/29089)*40780=120120

Compare that to this different Tony task, on the same GTX470:
Run time 10254, Granted credit 9283
Expected daily credit from one GTX470 = (86400/10254)*9283=78218

Just over 50% more credit.

Happy to report that they finish in about 6.5 hours on a GTX 570. And yes, they give quite a bit of credit. I compared the credit/sec for these new workunits compared to the highest-yielding standard workunit I finished. The long workunits yield about 1.7 credits/sec compared to the standard workunits, which only get around 0.8 credit/sec. That said, the queue for the long workunits is running low.

Their popularity seems to have risen sharply since yesterday; 200 in progress when I checked. Now there are over 1000 in progress, about 1/3 of the tasks.

But out of that thousand, there will probably be hundreds that will fail to complete the workunits. That should keep the queue from completely emptying out. However, there really should be a buffer of about a couple hundred workunits for both acemdlong and acemd2 at all times.

I am still tuning the acemdlong tasks, se we don't have a steady supply of them yet (there will be soon). Glad to see that they worked well. :-)

Hi Toni. Just make sure after 'tuning', that if they error, they do it at the start : )

Awesome! Keep up the good work!

the higher credits should compensate for the fact that the probability to fail is higher due to longer running time.
If you have a stable machine, then it's all good.

gdf

Downloaded four long wu's. All cancelled after some time.

GTX295!

What cards are the best for these long wu's? Fermi?

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Ton (ftpd) Netherlands

Long run tasks run on the 6.13app (cuda31). They should work for Fermi cards and CC1.3 cards such as a GTX295. I expect they are least likely to fail on the top Fermi cards.

For now, I would suggest you chose to only run the normal tasks on your GTX295 system and you might want to restart it. This might be a temporary issue so try again in a week or so.

Good luck,

For these long tasks, running time is about 5h40m (20400s) on a GTX 480 (at 800 Mhz) and 5h10m (18600s) on a GTX 580 (at 850 Mhz). GPU utilization is 72% and 68%, respectively. CPU is a C2Q9650 at 4.0 GHz, SWAN_SYNC=0 applied.

Utilization will increase in new jobs, this was an old one made longer as we needed further results.

gdf

when will we be getting the 99% utilization tasks again? march 4?

We are introducing the possibility for users to select between shorter (acemd2, approx 4 hours on GTX275 cards) and longer (acemdlong, 8 to 12 hours on GTX480) tasks. Simply go to your account preference to select which applications you want to crunch for. Long task are of course credited higher, but GPUs with less cores cannot simply compute them in time. 31 Jan 2011

With respect to the short tasks, I am seeing tasks as short as 6h on a GT240 and as long as 20h on the same system, or 28h on another GT240 (Vista, without swan_sync=0). I guess different projects require different runtimes, and perhaps you were testing, but if possible closer runtimes would be much preferred.

Thanks,

We have released internally guidelines for short and long runs. Most likely a factor 2 difference is unavoidable between different workunits in the same queue.

gdf

We have released internally guidelines for short and long runs. Most likely a factor 2 difference is unavoidable between different workunits in the same queue.

gdf

I noticed 1 long run WU, when I checked, I found this ,
WU , but isn't a
long runner?
They have Long-run in the name of the WU, IMHO.
Is the difference in CPU time, indicating, using SWAN_SYNC?
I use a X9650 @3510MHz CPU.

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Knight Who Says Ni N!

The WU a long run, 8-12 hour on the fastest card is at 55,95% after
4 hours, so I'm curious how much time is really needed, in this case/rig?
(X9650@3510MHz; GPU=GTX480; XP64;BOINC 6.10.58 64BIT)
Running smooth, load is better, as before.
And the latest EINSTEIN CUDA tasks, which also have been optimized, have a better GPU load as before.

Running 3 SETI MB WU's at a time, gives a 99% load and very little CPU
footprint or time to load and unload, also report and upload.

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Knight Who Says Ni N!

Hi Fred, I thought these KASHIF_HIVPR_wo tasks were quite long too.

I see you missed out on the full credit bonus. Perhaps lowering your cache would help, and/or man-managing which projects you run on a day-day or week-week basis.

Not using swan_sync would explain some of the slowness (16.6% slower). On such a powerful card using swan_sync & freeing a CPU core becomes more important.

While your GPU is clocked at 1.4GHz the other card clocks in at 1.45GHz. That said, you might have a faster CPU and are using 64bit XP.

It also looks like your task also restarted about 5 times. Each time can lose up to 5min. Changing your processor usage, Switch between applications everyto a high number such as 999 should prevent this, or using Leave Applications in Memory (LAIM), if you don't already have it selected.

Your task run, 18,302.34 1,226.58 10,347.84 12,934.80 ACEMD2: GPU molecular dynamics v6.13 (cuda31)
Other cruncher, 15,688.01 15,616.50 10,347.84 15,521.76 ACEMD2: GPU molecular dynamics v6.13 (cuda31)

The task on two systems

So, we would like to update the applications to the newest version.
1) Some little speed improvement
2) Only cuda3.1 version
3) Some bug fixes
4) If we can the read of SWAN_SYNC as a boinc parameter.

g

Hi, Linux and Windows and are using Cuda 4 on Nvidia drivers. Greetings.