Will Asteroids support those new Nvidia Gpu´s soon.
Would be much appreciated

Best Regards

I would like to put mine here as well. Any plans?

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wild guess: not soon

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The GTX 1660 Ti would be in more people’s reach. l ask that we get the app updated to support the Turing based cards please. Hopefully it would just be a matter of recompiling it with the latest CUDA compiler but I bet it’s not that simple.

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BOINC blog

... getting the following comp error on volta:


Stderr output

<core_client_version>7.14.2</core_client_version>
<![CDATA[
<message>
The system cannot find the file specified.
(0x2) - exit code 2 (0x2)</message>
<stderr_txt>
CUDA RC12!!!!!!!!!!
CUDA Device number: 0
CUDA Device: Quadro GV100
Compute capability: 7.0
Multiprocessors: 80
Unsupported CC detected (CC2.0 and better supported only).

</stderr_txt>
]]>

may be of help or interest ...

I get the same.

<core_client_version>7.14.2</core_client_version>
<![CDATA[
<message>
The system cannot find the file specified.
(0x2) - exit code 2 (0x2)</message>
<stderr_txt>
CUDA RC12!!!!!!!!!!
CUDA Device number: 0
CUDA Device: GeForce RTX 2070
Compute capability: 7.5
Multiprocessors: 36
Unsupported CC detected (CC2.0 and better supported only).

</stderr_txt>
]]>

I tried substituting libcudart.so.10.2 for the older 5.5 but it did not work even after telling BOINC not to check the file size or do a checksum test.

I had actually tried this approach on the Milkyway project app and managed to get a different library to be used. It didn't make any difference in performance but at least it ran.

Please go over here
https://askubuntu.com/questions/1204434/cuda-backwards-capability
and bump up my question.

Maybe there is a way to fool the Asteroids app into using the newer library. Seems to me the app should work with newer lib even if it does not take advantage of new performances in the device.

The GTX 1660 Ti would be in more people’s reach. l ask that we get the app updated to support the Turing based cards please. Hopefully it would just be a matter of recompiling it with the latest CUDA compiler but I bet it’s not that simple.

My 1080Ti, 1060 and 760 gpu's work just fine here, about 11 minutes per wu for the 1080Ti and about 47 minutes for the 760.

The GTX 1660 Ti would be in more people’s reach. l ask that we get the app updated to support the Turing based cards please. Hopefully it would just be a matter of recompiling it with the latest CUDA compiler but I bet it’s not that simple.

My 1080Ti, 1060 and 760 gpu's work just fine here, about 11 minutes per wu for the 1080Ti and about 47 minutes for the 760.

Your RAC here is 0. Consider giving up collatz. It is more likely an asteroid will hit us and stop "collatz" before collatz will find an exception to 3p+1, publish it, and stop.

I am back crunching but will pack up and leave if they get on the GRIDCOIN graylist or blacklist for not having work.

Yea, they fixed the same problem back 3 years ago. Maybe they kept notes on how it was done.
https://www.reddit.com/r/BOINC/comments/4wi1sf/astroidshome_wu_error_gtx_1080/
The following is a mix of one gtx1070, one 1070Ti, and three P102-100

       Run Time     CPU Time     Credit
         (sec)         (sec)
           660.3         658.4        480.0
           264.3         261.1        480.0
           205.1         203.1        480.0
           651.4         647.6        480.0
            23.2          21.1        480.0
           876.6         871.1        480.0
           675.5         672.6        480.0
           647.2         643.2        480.0
           138.7         135.4        480.0
          1007.9        1004.4        480.0
           680.3         675.9        480.0
           675.9         673.5        480.0
           141.6         139.8        480.0
           656.2         654.3        480.0
           794.1         789.6        480.0
           641.1         639.1        480.0
           656.2         654.8        480.0
           907.4         904.2        480.0
           593.9         591.7        480.0
           652.2         650.4        480.0
         ----------------------------------

Avg:       577.4         574.6        480.0
STD:       267.1         266.6          0.0

1.20 seconds per credit from above info one device
0.8312 Credits per second for one device
Times shown above were divided by number of concurrent tasks(1)
2,992 number of credits in an hour this system