20190227, 03:25  #1 
Jan 2019
Pittsburgh, PA
E7_{16} Posts 
Round off error problems
Hello guys! Hopefully everyone is enjoying or enduring the weather. It's bad weather here at Iowa.
I was running cudalucas 2.06beta on an RTX 2080, but it seems like I kept on getting this error Code:
Round off error at iteration = 22746300, err = 0.375 > 0.35, fft = 4704K. Code:
Round off error at iteration = 22746300, err = 0.375 > 0.35, fft = 4704K. Restarting from last checkpoint to see if the error is repeatable. Using threads: square 256, splice 128. Continuing M87515717 @ iteration 22740001 with fft length 4704K, 25.98% done  Feb 26 21:05:49  M87515717 22750000 0x600e2a5aac882d3a  4704K 0.34375 4.2361 42.35s  3:04:14:02 25.99%  Looks like the error went away, continuing. Code:
Round off error at iteration = 5632400, err = 0.375 > 0.35, fft = 4704K. Restarting from last checkpoint to see if the error is repeatable. Using threads: square 256, splice 128. Continuing M87515717 @ iteration 5630001 with fft length 4704K, 6.43% done Round off error at iteration = 5632400, err = 0.35938 > 0.35, fft = 4704K. The error persists. Trying a larger fft until the next checkpoint. Using threads: square 256, splice 128. Continuing M87515717 @ iteration 5630001 with fft length 5120K, 6.43% done  Feb 26 00:11:57  M87515717 5640000 0x8692fae95ad89471  5120K 0.03906 4.0596 40.59s  3:20:19:49 6.44%  Resettng fft. I have attached partial log for an LL test for M87515717, from 6.43% to 26.09%. Much thanks! log.txt Last fiddled with by dcheuk on 20190227 at 03:28 
20190227, 03:37  #2 
P90 years forever!
Aug 2002
Yeehaw, FL
2×5×691 Posts 
A roundoff error < 0.4 simply means you are testing an exponent near the limits of what that FFT size can support. Your hardware and end result are just fine.
Your choice is to endure the rollbacks of force using a larger FFT size (I don't know how to do that). 
20190227, 03:39  #3  
Jan 2019
Pittsburgh, PA
3·7·11 Posts 
Quote:
Thanks again! 

20190227, 03:43  #4  
Jan 2019
Pittsburgh, PA
E7_{16} Posts 
Quote:
UPDATE: increasing the FFT length seems to have solved the problem. No more errors! yay. Thanks. Last fiddled with by dcheuk on 20190227 at 04:30 

20190227, 05:53  #5  
"Eric"
Jan 2018
USA
7×29 Posts 
Quote:
I would genuinely advise you to conduct a FFT benchmark and thread benchmark as 5120K doesn't seem to be the fastest FFT in my case (I'm using Pascal/volta so I am not sure about Turing optimization and how it deals with FFT, with 5184K FFT being near the speed of 4608K and much faster than 5120K, it is also able to tolerate higher exponents than 5120K so this is highly advised as you can speed up your work and increase efficiency). Then you would just go to the CUDALucas.ini file to change the FFT at the very bottom as well as the thread as shown in the benchmark list. Refer to the instruction in the ini file for how to input the values. 

20190227, 15:36  #6  
Jan 2019
Pittsburgh, PA
347_{8} Posts 
Quote:
You're right I noticed that surprisingly after increasing the FFT size the time to complete each iteration decreased lol 

20190227, 16:01  #7  
"Marv"
May 2009
near the TannhÃ¤user Gate
2×13×19 Posts 
Quote:
https://www.mersenneforum.org/showpo...84&postcount=6 

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