From what I heard, RTX series has separate integer and FP units, and this project is integer only. This is probably why RTX gets such boost.

dont expect much increase for RTX cards, nearly half of gpu core take that "tensor"..

Just installed my RTX 2080.....averaging 134 seconds a task. :)

Nice numbers )) Thank you for sharing.
Soo all about ..is like sergey wrote in up ..
Custom 2080Ti can get maybe 80-100 sec ..? have you also 2080Ti ?
Saddly prices on custom or msrp are too high .. on rtx 1080ti have 699 usd ... two used 1080ti is about 1000 usd now.

No, I only got a 2080, no Ti. I'm actually really surprised the performance was that good. My 1080 only eked out 300 second WU's but this was very surprising.

Have to do more testing with other Boinc projects and see if these results are similar or something that is just benefiting this project.



Soooo.....about that 24 or 25 kernel size. lol. :)

133 vs 601 sec on some tasks ... Linux Fedora
Fedora 27 (Twenty Seven) [4.18.7-100.fc27.x86_64|libc 2.26 (GNU libc)]
https://sech.me/boinc/Amicable/results.php?hostid=54096&offset=0&show_names=0&state=4&appid= this host with nvidia RTx do task average 133 sec. but there is also some task 600 sec..

<core_client_version>7.10.2</core_client_version>
<![CDATA[
<stderr_txt>
Initializing prime tables...done
X server found. dri2 connection failed!
DRM_IOCTL_I915_GEM_APERTURE failed: Invalid argument
Assuming 131072kB available aperture size.
May lead to reduced performance or incorrect rendering.
get chip id failed: -1 [22]
https://sech.me/boinc/Amicable/result.php?resultid=17599793 is from 600 sec task
this one is from 133 sec task
<core_client_version>7.10.2</core_client_version>
<![CDATA[
<stderr_txt>
Initializing prime tables...done
X server found. dri2 connection failed!
DRM_IOCTL_I915_GEM_APERTURE failed: Invalid argument
Assuming 131072kB available aperture size.
May lead to reduced performance or incorrect rendering.
get chip id failed: -1 [22]
param: 4, val: 0

They probably have a 2080 and a second older card. BOINC only reports back how many cards you have installed and only the model of one, usually the fastest one. So the 133 is coming from the 2080 and the 600 is from whatever other card they have.

https://foldingforum.org/viewtopic.php?f=83&t=31051&sid=3692e2e3ee44efee1f6c8544bea63eae&start=15
2080Ti amazing impresive 2,2 mil. PPD in folding home
https://docs.google.com/spreadsheets/d/1v5gXral3BcFOoXs5n1M6l_Uo3pZpQYogn6gVlxRPnz0/edit#gid=0

Sorry bit off topic.. but can maybe help in some way for this project ) to show performance for users if not any more

Hi,

i am using a Vega VII and with standard kernel size 21 i got a run time of 12754,61s. The GPU-Load was about 0,00...1%.
For me it looks as if the GPU is not used.
Now i try 23 - but maybe there is something completely wrong if others have some minutes run times and i need hours?

Hi MagicEye04,

There is nothing wrong with your computer, so please do not worry about that :)

Presently; the calculations performed for this project are almost exclusively performed with the CPU and almost nothing is done on the GPU. You can run multi-threaded CPU tasks and, with your CPU, your run-time should be approximately 30 minutes per task if you are using all threads.

Regards,
Kellen

But why are there tasks send out that seem to use a GPU?
Wouldnt it be better to send only the CPU tasks?

Hi,
I'm using an AMD Radeon Vega 8 INTERGRATED gfx. It seems that with any kernel size the screen lags and soon the cursor become immovable. How to solve this?

It's not GPU lags in your case, you jut need more than 8 GB system memory to run GPU tasks. Your notebook is swapping and everything starts to lag.

When looking at averaged task times, I noticed that my GTX 1650 appears to be at least as productive as my 1080 Ti, if not even a tad better (both 1.1-1.2 million cr/day). I have both running one task at a time, kernel size 23. Is Turing really that superior or am I doing something wrong with the 1080 Ti? The Ti is even running on a DDR4 Linux system, the 1650 only DDR3 and Windows. Both have ample RAM available and core load is close to 100%.

Turing really is that much better for these tasks :)

Turing really is that much better for these tasks :)

I guess so.

Another thing, I'm running two tasks at once on this RTX 2080 and although it runs well (and throughput improves) every once in a while a task gets stuck and runs endlessly. Trying to reduce kernel size to 22 and see if it happens again.

It doesn't get stuck: https://sech.me/boinc/Amicable/workunit.php?wuid=11804634 - another GPU finished it, you just had to wait a bit more.

Huh. Why are these so exceptionally long?

Probably because task size is 68*10¹², 100 times more than usual. Task generator was definitely not perfect.

2 wu too little crediter

10 Nov 2019, 21:13:38 UTC 14 Nov 2019, 19:29:48 UTC Terminé et validé 141,192.21 4,272.16 6,836.19 Amicable Numbers up to 10^21 v3.02 (opencl_nvidia)
x86_64-pc-linux-gnu

10 Nov 2019, 21:13:36 UTC 12 Nov 2019, 20:26:03 UTC Terminé et validé 137,003.05 3,820.35 6,836.19 Amicable Numbers up to 10^21 v3.02 (opencl_nvidia)
x86_64-pc-linux-gnu

Probably because task size is 68*10¹², 100 times more than usual. Task generator was definitely not perfect.

I guess I got another one of these. One of my GPU tasks has been running for almost three hours now and it's 9.5% done. I'll leave it running.