Yes you can stop and start a task at any time when all your cards are the same.

Thanks for confirming that, Keith.
I've also found that when device zero is in the lead but less than 90% it will (sometimes) pick them both back up without erring. When dev 0 is beyond 90% it will show a computation error even if it is in the lead. Has anyone else observed this?

An unrelated note: BOINC sees a GTX 1650 as device 0 when paired with my 1060 3GB, even though it is slightly slower than the 1060 (almost undetectable running ACEMD tasks).
I think it might be due to Turing being newer than Pascal. I don't see any GPU benchmarking done by the BOINC manager.

By the way, muchas gracias to ServicEnginIC for hosting this thread! It's totally synchronous with my current experiences as a cruncher. 🥇👍🥇

An unrelated note: BOINC sees a GTX 1650 as device 0 when paired with my 1060 3GB, even though it is slightly slower than the 1060 (almost undetectable running ACEMD tasks).
I think it might be due to Turing being newer than Pascal. I don't see any GPU benchmarking done by the BOINC manager.

BOINC will order Nvidia cards based on CC (compute capability), and then by how much memory it has.

the 1650 has CC of 7.5 where the 1060 has 6.1. the 1650 also has more memory than the 3GB version of the 1060.

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Pop Piasa wrote:

By the way, muchas gracias...

You're welcome, de nada,
I enjoy learning new matters, and sharing knowledge

Ian&Steve C. wrote:

BOINC will order Nvidia cards based on CC (compute capability), and then by how much memory it has.

I've ever wondered about that.
Thank you very much!, one more detail I've learnt...

Thanks for your generous reply Ian & Steve, you guys have a great working knowledge of BOINC's innards!
It pays for me to come here and ask, as a newbie in distrib. computing.

Great that you brought your talents and hardware over to this project when they stopped SETI. (Hmm... does shutting down the search mean that they gave up, or that the search is complete?)👽

Great that you brought your talents and hardware over to this project when they stopped SETI. (Hmm... does shutting down the search mean that they gave up, or that the search is complete?)👽

Without getting too far off topic, they basically had money/staffing problems. they didnt have the resources to constantly babysit their servers, while working on the backend analysis system at the same time. all of the work that has been processed over the last 20 years has not been analyzed by the scientists yet, it's just sitting in the database. they are building the analysis system that will sort through all the results, so they are shutting down the data distribution process so they can focus on that. they feel like 20 years of listening to the northern sky was enough for now. They left the option open that the project might return someday.

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they feel like 20 years of listening to the northern sky was enough for now.

When SETI first started I used a Pentium II machine at the University I retired from to crunch when it was idle and my boss dubbed me "Mr Spock". Thanks for filling in the details and providing a factual perspective to counter my active imagination. I should have guessed it was a resource issue.

SETI is written in Distributed Computing history with bold letters.

On Apr 18th 2020 | 22:34:50 UTC Pop Piasa wrote:

...I Just finished a PABLO WU which took a little over 12 hrs on one of my GTX1650 GPUs.
I guess long runs are back.

I also received one of this PABLO WUs... and by any chance it was assigned to my slowest GPU currently in production.
It took 34,16 hours to complete in a GTX750, anyway in time to get half bonus.

I also received one of this PABLO WUs... and by any chance it was assigned to my slowest GPU currently in production.
It took 34,16 hours to complete in a GTX750, anyway in time to get half bonus.

I've run 2 PABLOs so far, but only on my 1650s. They both ran approx. 12:10 Hrs, 11:58 CPU time. If I can get one on my 750ti (also a Dell/Alienware and clocked at 1200Mhz; 2GB 2700Mhz DDR3) we can get a good idea how they all compare.
If anyone has run a PABLO designed ACEMD task on a 1050 or other low power GPU please share your results. I would also like to see how these compare to a 2070-super as I am considering replacing the 750ti with one.

If anyone has run a PABLO designed ACEMD task on a 1050 or other low power GPU please share your results.

e2s112_e1s62p0f90-PABLO_UCB_NMR_KIX_CMYB_5-2-5-RND2497_0
GTX 750Ti
109,532.48 seconds = 30h 25m 32.48s

If anyone has run a PABLO designed ACEMD task on a 1050 or other low power GPU please share your results. I would also like to see how these compare to a 2070-super as I am considering replacing the 750ti with one.

not a low power card, but something to expect when moving to the 2070-super. I have 2080's and 2070's. the 2070-super should fall somewhere between these two, maybe closer to the 2080 in performance.

my 2080s do them in about ~13000 seconds = ~3.6 hours.
my 2070s do them in about ~15500 seconds = ~4.3 hours.

so maybe around 4hrs on average for a 2070 super.

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my 2080s do them in about ~13000 seconds = ~3.6 hours.
my 2070s do them in about ~15500 seconds = ~4.3 hours.

so maybe around 4hrs on average for a 2070 super.

Thanks for the info., that pretty much agrees with the percentage ratios I've seen on Userbenchmark.com.
I plan to replace my PSU when I can afford it and eventually have two matching high-power GPUs on my ASUS Prime board (i7-7700K). That will leave me with a 1060 3GB and a 750ti to play with in some other old machine I might acquire from my friends' business throw-aways.

I also received one of this PABLO WUs... and by any chance it was assigned to my slowest GPU currently in production.
It took 34,16 hours to complete in a GTX750, anyway in time to get half bonus.

I was lucky to receive two more PABLO WUs today.

One of them was assigned to my currently fastest GPU.
So I can compare with the first one already mentioned, assigned to the slowest.
I'll put them in image format, because they'll dissapear from GPUGrid's database in a few days.
- GTX 750 - WU 19473911: 122.977 seconds = 34,16 hours
- GTX 1660 Ti - WU 19617512: 24.626 seconds = 6,84 hours
Conclusion: GTX 1660 Ti has processed its PABLO WU in about 1/5 the time than GTX 750. (About 500% relative performance)

The second PABLO WU received today has been assigned again to other of my GTX 750 GPUs, and it will serve as a consistency check for execution time comparing to the first one.
At this time, this WU is completed in 25,8% after an execution time of 9,5 hours.

If I were lucky enough to get PABLO WUs at every of my GPUs, I'd be able to pepare a new table similar to the one at the very first of this thread...

Or, perhaps, Toni would be able to take this particular batch to rebuild the Performance page with data from every GPU models currently contributing to the project...😏

Here you go, ServicEngineIC:

GTX 1650 gpu@1860MHz/ mem@4001MHz
(Dell Optiplex 980/i7-860 @2926MHz/ 12GB PC3-10600 @1200MHz)
45,400.71sec =12.6Hrs
http://httpd://www.gpugrid.net/workunit.php?wuid=19582490

GTX 1650 gpu@1860MHz/ mem@4001MHz
(ASUS Prime Z-270/i7-7700K @4200MHz/ 16GB PC4-2132 @3000MHz)
44,027.23sec =12.2Hrs
https://www.gpugrid.net/workunit.php?wuid=19495626

Here you go, ServicEngineIC for the Pablo tasks.

https://www.gpugrid.net/result.php?resultid=24501891
RTX2080@1805Mhz mem@14400Mhz
14,864 seconds = 4.13hrs
AMD Ryzen 3950X@4100Mhz @3600Mhz CL14

https://www.gpugrid.net/result.php?resultid=24502927
RTX2070@1700Mhz mem@14400Mhz
13,911 seconds = 3.87hrs
AMD Threadripper 2920X@4100Mhz @3466Mhz CL14

Ok!
Thank you!
I'll try to throw a new comparative table on this Sunday April 26th, with all data that I receive until Saturday 23:59 UTC...
Data, Data, Crunch, Crunch, 🔥🔥

Well, I tried to manipulate a PABLO WU over to my gtx 750ti by suspending it at 0.23% on my gtx1650, and when it restarted on the 750ti it crashed, falsifying my theory that ACEMD tasks can all be restarted before 10%. Perhaps it is still true running MDAD tasks.

Dmitriy Otroschenko's gtx 1060 3GB ran it:
39,016.09sec = 10.84Hrs.
AMD Ryzen 7 2700X Eight-Core Processor

I'm currently in the middle of 3 more PABLO tasks (almost as if Grosso knows I want them somehow), one on each of the 3 types of GPUs on my hosts. Not sure about being finished on the 750ti by midnight, ServicEnginIC.

i think the PABLO tasks cannot be restarted at all, even in a system with identical GPUs. I had a GPU crash the other day, and after rebooting a PABLO task tried to restart on a different GPU, and it failed immediately saying that it cannot be restarted on a different device. I haven't had that problem with the MDAD tasks though. they seem to be able to be stopped and restarted pretty much whenever, even on another device if it's the same as the one it started on, 0-90% without issue.

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I still am running with the switch timers set at 360 minutes. So don't step away from a running task for six hours. Think that might have covered my Pablo tasks but I never have changed my settings even after moving to an all RTX 2080 host.