Oj0 Posted July 17, 2016 Share Posted July 17, 2016 Yes, use 2.3.4 it fixes all fo the sync and validation issues with multiple cards. Btw, 2.2 had no runtime validation, it only validates the final result. That's why it works. I know, but 2.2 would pass the end validation. Quote Link to comment Share on other sites More sharing options...
_mat_ Posted July 17, 2016 Author Share Posted July 17, 2016 The end validation has not changed at all. But if you are using CUDA, the kernels have changed so it will be harder on your GPUs. Try to reduce oc or increase voltage/cooling. Quote Link to comment Share on other sites More sharing options...
kezu Posted August 11, 2016 Share Posted August 11, 2016 Hello im having a bad day with gpupi. pops up this message: Error synchronizing device after kernel execution any hints for solution, drivers reinstalled etc. No can do. 6700k&ranger & gt710 pcie card Maybe ill just swap to system for gpupi bench Quote Link to comment Share on other sites More sharing options...
_mat_ Posted August 11, 2016 Author Share Posted August 11, 2016 That's a CUDA error, that happens directly after the calculation kernel when waiting for the GPU to return the data. Something like this occurs for example when there was something wrong with the memory (read or write in unallocated areas). Is the card heavily overclocked? Are you using high batch and reduction sizes? Try stock clocks and the lowest sizes and see if that's the problem. Btw, you should have also gotten a detailed error message in square brackets right next to the error you posted. Please let me know what it is. Quote Link to comment Share on other sites More sharing options...
newlife Posted August 11, 2016 Share Posted August 11, 2016 Hello im having a bad day with gpupi. pops up this message: Error synchronizing device after kernel execution any hints for solution, drivers reinstalled etc. No can do. 6700k&ranger & gt710 pcie card Maybe ill just swap to system for gpupi bench To run 1b on a gt 710 you need to set batch size below 10m or it will fail at loop 4 Quote Link to comment Share on other sites More sharing options...
WhiteWulfe Posted November 2, 2016 Share Posted November 2, 2016 Since I can't flag my own submission, I noticed something about GPU PI 2.3.4.... Any particular reasons why the data file puts my Phenom II X4 955 BE as a non-BE? I've gone in and edited the submission so it's showing as a Black Edition, but is this a limitation of GPU Pi in and of itself, or? WhiteWulfe`s GPUPI for CPU - 1B score: 20min 19sec 331ms with a Phenom II X4 955 for my submission in question. EDIT: Actually, it won't let me edit it to a Black Edition, just winds up sitting at Apache Tomcat/7.0.59 - Error report and doesn't go back to my submission. Quote Link to comment Share on other sites More sharing options...
Administrators websmile Posted November 4, 2016 Administrators Share Posted November 4, 2016 Moved the post to the GPUPI thread, maybe _mat_ can explain or help Quote Link to comment Share on other sites More sharing options...
WhiteWulfe Posted November 4, 2016 Share Posted November 4, 2016 Moved the post to the GPUPI thread, maybe _mat_ can explain or help It would be nice to know... I also didn't know about this thread On the plus side, the other bit about not being to edit it.... I was able to edit my 1B and 100M score afterwards so it's the correct processor. Still annoying that it registers as the incorrect processor, and then the server wouldn't let me manually correct it to a Black Edition. Quote Link to comment Share on other sites More sharing options...
Administrators websmile Posted November 4, 2016 Administrators Share Posted November 4, 2016 It would be nice to know... I also didn't know about this thread On the plus side, the other bit about not being to edit it.... I was able to edit my 1B and 100M score afterwards so it's the correct processor. Still annoying that it registers as the incorrect processor, and then the server wouldn't let me manually correct it to a Black Edition. I checked the sub, it is shown as Phenom II X4 955 BE for me... is this different for you? I don´t think so, edit worked, maybe it can be fixed so that edit is no need in the future WhiteWulfe`s GPUPI for CPU - 1B score: 20min 19sec 331ms with a Phenom II X4 955 BE Quote Link to comment Share on other sites More sharing options...
WhiteWulfe Posted November 4, 2016 Share Posted November 4, 2016 I checked the sub, it is shown as Phenom II X4 955 BE for me... is this different for you? I don´t think so, edit worked, maybe it can be fixed so that edit is no need in the future WhiteWulfe`s GPUPI for CPU - 1B score: 20min 19sec 331ms with a Phenom II X4 955 BE .... .....I just said I was finally able to edit it. Wasn't able to when it was originally submitted, hence why I had created the thread in the first place. GPU Pi is identifying my processor as a 955 non-black edition for some reason. I can resubmit the datafile as a no-points submission if that helps. Quote Link to comment Share on other sites More sharing options...
Administrators websmile Posted November 4, 2016 Administrators Share Posted November 4, 2016 I am not sure this will help, because cpuz identifies cpu as non be as well and this problem seems to be as old as the cpu. Stepping and all this are recognized the same on BE and non BE CPU-Z Validator 3.1 CPU-Z Validator 3.1 Quote Link to comment Share on other sites More sharing options...
_mat_ Posted November 4, 2016 Author Share Posted November 4, 2016 The name of the device is retrieved via the opencl driver, which normally just takes the CPUID brand string as it is shown in CPU-Z, a hardcoded value inside the CPU. GPUPI removes various prefixes and postfixes to be able to submit the result to HWBOT. Quote Link to comment Share on other sites More sharing options...
marco.is.not.80 Posted June 25, 2017 Share Posted June 25, 2017 I have a question and before someone says "search" or it was discussed already in this thread I fully read from the last page in this thread all the way to page 30 and then fell asleep at my keyboard and now just woke up and decided to ask my question anyways at risk of being flamed or moderated - so here goes: My understanding is that as long as I have a skylake/kabylake processor AND I'm on Windows 10 then I'm not supposed to be forced to set the HPET settings in the operating system or the BIOS since my system isn't "bugged". When I run GPUPI there is no way for me to avoid setting it in the O/S or it complains about the HPET timer not being set. How can I bypass this? If I can't because I'm totally misunderstanding the HPET bug thingy please feel free to re-educate me... right after I get a coffee. ;-) Marco Quote Link to comment Share on other sites More sharing options...
Mr.Scott Posted June 25, 2017 Share Posted June 25, 2017 (edited) You misunderstand. HPET needs to be on no matter what OS is involved. There is no HPET bug. There is a RTC bug. Edited June 25, 2017 by Mr.Scott Quote Link to comment Share on other sites More sharing options...
marco.is.not.80 Posted June 25, 2017 Share Posted June 25, 2017 Ok, got it... so it's not actually a timer bug. Got it. So I guess I'm still a little perplexed because those of us on Skylake/KabyLake using Windows 10 aren't affected by this bug so once again my question is why do I need to change anything for this particular benchmark? - Marco Quote Link to comment Share on other sites More sharing options...
Mr.Scott Posted June 25, 2017 Share Posted June 25, 2017 Because for the bench to run, it needs the High Precision Event Timer. That's the way the bench was made. If it's not on, the bench doesn't work. It's that simple. Quote Link to comment Share on other sites More sharing options...
_mat_ Posted June 25, 2017 Author Share Posted June 25, 2017 (edited) Windows 8 and above are effected by the RTC skewing bug when bclock is changed in Windows. I don't think that Skylake and Kaby Lake are any exception to this rule, but I haven't tested it myself yet. To circumvent HPET you have to use Windows 7. Edit: Rules of HWBOT allow the legacy benchmarks on SL and KL, so I guess it has been tested and it's not affecting the RTC timer. Well, with the next version GPUPI I will remove the HPET restriction on SL and KL. Edited June 25, 2017 by _mat_ Quote Link to comment Share on other sites More sharing options...
marco.is.not.80 Posted June 26, 2017 Share Posted June 26, 2017 Wow, Mat - thanks so much for responding and I can't speak for everyone but thank you for all the work you do for the community and I look forward to the next version :-) - Marco Quote Link to comment Share on other sites More sharing options...
_mat_ Posted June 26, 2017 Author Share Posted June 26, 2017 Thank you for your kind words, very much appreciated. Quote Link to comment Share on other sites More sharing options...
Massman Posted June 27, 2017 Share Posted June 27, 2017 Windows 8 and above are effected by the RTC skewing bug when bclock is changed in Windows. I don't think that Skylake and Kaby Lake are any exception to this rule, but I haven't tested it myself yet. To circumvent HPET you have to use Windows 7. Edit: Rules of HWBOT allow the legacy benchmarks on SL and KL, so I guess it has been tested and it's not affecting the RTC timer. Well, with the next version GPUPI I will remove the HPET restriction on SL and KL. Intel introduced a separate BCLK clockgen on SKL which circumvents the RTC bug :celebration:. Quote Link to comment Share on other sites More sharing options...
_mat_ Posted June 28, 2017 Author Share Posted June 28, 2017 A little preview of some of the features of GPUPI 3.0 for my fellow overclockers. Command line version for Windows: Autoselection of the compute platform, Batch Size and Reduction Size depending by prebenching it for the user: $ ./GPUPI_x64 -c -d 100MGPUPI 3.0 (64 bit) API: OpenCL GPU with 1 devices API: OpenCL CPU with 2 devices API: CUDA with 1 devices Testing device: OpenCL CPU -> Intel® OpenCL -> Intel Core i7-6950X => 1M, 16: 2.294076 (Kernel: 2.250068, Reduction: 0.043280) => 1M, 32: 2.248263 (Kernel: 2.209528, Reduction: 0.037883) => 1M, 64: 2.270596 (Kernel: 2.231809, Reduction: 0.038067) => 1M, 128: 2.245034 (Kernel: 2.207602, Reduction: 0.036715) => 1M, 256: 2.279390 (Kernel: 2.229491, Reduction: 0.049113) => 1M, 512: 2.266061 (Kernel: 2.193988, Reduction: 0.071337) => 2M, 16: 2.315099 (Kernel: 2.236380, Reduction: 0.078018) => 2M, 32: 2.288076 (Kernel: 2.219284, Reduction: 0.068005) => 2M, 64: 2.287389 (Kernel: 2.226804, Reduction: 0.059873) => 2M, 128: 2.249376 (Kernel: 2.191177, Reduction: 0.057482) => 2M, 256: 2.283105 (Kernel: 2.215427, Reduction: 0.066962) => 2M, 512: 2.254495 (Kernel: 2.194912, Reduction: 0.058892) => 4M, 16: 2.307497 (Kernel: 2.218491, Reduction: 0.088419) => 4M, 32: 2.260795 (Kernel: 2.183106, Reduction: 0.077162) => 4M, 64: 2.304972 (Kernel: 2.238267, Reduction: 0.066159) => 4M, 128: 2.255765 (Kernel: 2.196260, Reduction: 0.058924) => 4M, 256: 2.277544 (Kernel: 2.209126, Reduction: 0.067898) => 4M, 512: 2.249683 (Kernel: 2.191406, Reduction: 0.057736) => 5M, 16: 2.304984 (Kernel: 2.217214, Reduction: 0.087279) => 5M, 32: 2.265134 (Kernel: 2.187128, Reduction: 0.077524) => 5M, 64: 2.279445 (Kernel: 2.212483, Reduction: 0.066463) => 5M, 128: 2.238783 (Kernel: 2.180829, Reduction: 0.057460) => 5M, 256: 2.299566 (Kernel: 2.231994, Reduction: 0.067090) => 5M, 512: 2.267714 (Kernel: 2.197324, Reduction: 0.069908) => 10M, 16: 2.311983 (Kernel: 2.226683, Reduction: 0.084900) => 10M, 32: 2.271478 (Kernel: 2.194653, Reduction: 0.076431) => 10M, 64: 2.261646 (Kernel: 2.190358, Reduction: 0.070862) => 10M, 128: 2.238901 (Kernel: 2.181579, Reduction: 0.056898) => 10M, 256: 2.278743 (Kernel: 2.215327, Reduction: 0.062982) => 10M, 512: 2.271698 (Kernel: 2.204813, Reduction: 0.066495) => 20M, 16: 2.316387 (Kernel: 2.224665, Reduction: 0.091349) => 20M, 32: 2.264053 (Kernel: 2.185630, Reduction: 0.078063) => 20M, 64: 2.302941 (Kernel: 2.229473, Reduction: 0.073087) => 20M, 128: 2.256671 (Kernel: 2.193457, Reduction: 0.062854) => 20M, 256: 2.256185 (Kernel: 2.194374, Reduction: 0.061453) => 20M, 512: 2.239121 (Kernel: 2.177762, Reduction: 0.061003) => 100M, 16: 2.351734 (Kernel: 2.219785, Reduction: 0.131625) => 100M, 32: 2.284867 (Kernel: 2.182241, Reduction: 0.102328) => 100M, 64: 2.331753 (Kernel: 2.241809, Reduction: 0.089634) => 100M, 128: 2.314707 (Kernel: 2.239817, Reduction: 0.074468) => 100M, 256: 2.272911 (Kernel: 2.204067, Reduction: 0.068538) => 100M, 512: 2.262099 (Kernel: 2.198868, Reduction: 0.062920) Testing device: OpenCL CPU -> Experimental OpenCL 2.1 CPU Only Platform -> Intel Core i7-6950X => 1M, 16: 2.256272 (Kernel: 2.208813, Reduction: 0.046615) => 1M, 32: 2.259307 (Kernel: 2.213463, Reduction: 0.045005) => 1M, 64: 2.261296 (Kernel: 2.217321, Reduction: 0.043054) => 1M, 128: 2.255290 (Kernel: 2.210472, Reduction: 0.043979) => 1M, 256: 2.276476 (Kernel: 2.228651, Reduction: 0.046952) => 1M, 512: 2.290972 (Kernel: 2.212072, Reduction: 0.078073) => 2M, 16: 2.281812 (Kernel: 2.198045, Reduction: 0.082942) => 2M, 32: 2.257342 (Kernel: 2.186708, Reduction: 0.069812) => 2M, 64: 2.274022 (Kernel: 2.210600, Reduction: 0.062644) => 2M, 128: 2.242322 (Kernel: 2.182171, Reduction: 0.059333) => 2M, 256: 2.284035 (Kernel: 2.214316, Reduction: 0.068943) => 2M, 512: 2.245358 (Kernel: 2.182079, Reduction: 0.062468) => 4M, 16: 2.314692 (Kernel: 2.223573, Reduction: 0.090524) => 4M, 32: 2.287976 (Kernel: 2.207894, Reduction: 0.079501) => 4M, 64: 2.280830 (Kernel: 2.212408, Reduction: 0.067748) => 4M, 128: 2.246577 (Kernel: 2.185500, Reduction: 0.060417) => 4M, 256: 2.267059 (Kernel: 2.196838, Reduction: 0.069591) => 4M, 512: 2.245285 (Kernel: 2.185138, Reduction: 0.059543) => 5M, 16: 2.297634 (Kernel: 2.208198, Reduction: 0.088819) => 5M, 32: 2.252606 (Kernel: 2.173261, Reduction: 0.078811) => 5M, 64: 2.289753 (Kernel: 2.219699, Reduction: 0.069525) => 5M, 128: 2.241125 (Kernel: 2.181959, Reduction: 0.058589) => 5M, 256: 2.272509 (Kernel: 2.203694, Reduction: 0.068293) => 5M, 512: 2.255514 (Kernel: 2.184216, Reduction: 0.070740) => 10M, 16: 2.283480 (Kernel: 2.197331, Reduction: 0.085667) => 10M, 32: 2.259312 (Kernel: 2.181606, Reduction: 0.077262) => 10M, 64: 2.273700 (Kernel: 2.201239, Reduction: 0.071997) => 10M, 128: 2.239782 (Kernel: 2.180927, Reduction: 0.058395) => 10M, 256: 2.288214 (Kernel: 2.223593, Reduction: 0.064161) => 10M, 512: 2.275962 (Kernel: 2.210551, Reduction: 0.064933) => 20M, 16: 2.298107 (Kernel: 2.206268, Reduction: 0.091459) => 20M, 32: 2.282686 (Kernel: 2.204328, Reduction: 0.077989) => 20M, 64: 2.264337 (Kernel: 2.189890, Reduction: 0.074074) => 20M, 128: 2.261340 (Kernel: 2.197828, Reduction: 0.063139) => 20M, 256: 2.254334 (Kernel: 2.191051, Reduction: 0.062873) => 20M, 512: 2.261168 (Kernel: 2.199776, Reduction: 0.060975) => 100M, 16: 2.363773 (Kernel: 2.221893, Reduction: 0.141445) => 100M, 32: 2.325590 (Kernel: 2.220586, Reduction: 0.104667) => 100M, 64: 2.281907 (Kernel: 2.196272, Reduction: 0.085290) => 100M, 128: 2.290375 (Kernel: 2.214583, Reduction: 0.075452) => 100M, 256: 2.274559 (Kernel: 2.203661, Reduction: 0.070590) => 100M, 512: 2.287639 (Kernel: 2.223986, Reduction: 0.063316) Best device found: OpenCL CPU -> Intel® OpenCL -> Intel Core i7-6950X with 5M, 128. Timer: HPET (14.32 MHz) Init HWiNFO: Ok OpenCL CPU: Intel Core i7-6950X (20 CUs, 3000 MHz) Compiling OpenCL kernels ... done. Calculating 100.000.000th digit of PI. 20 iterations. Allocated device memory : 83.89 MB Batch Size : 5M Reduction Size : 128 00h 00m 00.480s Batch 1 finished. 00h 00m 00.945s Batch 2 finished. 00h 00m 01.403s Batch 3 finished. 00h 00m 01.850s Batch 4 finished. 00h 00m 02.263s Batch 5 finished. 00h 00m 02.734s Batch 6 finished. 00h 00m 03.201s Batch 7 finished. 00h 00m 03.649s Batch 8 finished. 00h 00m 04.089s Batch 9 finished. 00h 00m 04.502s Batch 10 finished. 00h 00m 04.980s Batch 11 finished. 00h 00m 05.450s Batch 12 finished. 00h 00m 05.915s Batch 13 finished. 00h 00m 06.367s Batch 14 finished. 00h 00m 06.784s Batch 15 finished. 00h 00m 07.257s Batch 16 finished. 00h 00m 07.724s Batch 17 finished. 00h 00m 08.187s Batch 18 finished. 00h 00m 08.639s Batch 19 finished. 00h 00m 09.055s PI value output -> CB840E219 Highest clocks measured: CPU: 3800.11 MHz GPU: 202.50 MHz GPU memory: 101.25 MHz Statistics: Calculation + Reduction time: 8.822s + 0.231s PI calculation is done! 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marco.is.not.80 Posted June 28, 2017 Share Posted June 28, 2017 Can't wait! Quote Link to comment Share on other sites More sharing options...
niobium615 Posted July 2, 2017 Share Posted July 2, 2017 Quick question, having an issue with GPUPI. I'm doing 32B runs on a 1080Ti, they'll complete just fine and the checksum appears to be right. If I save the validation file, I get the normal message saying that the file was saved successfully. However, if I try to immediately validate that same file, I get the following error: "The result file was successfully decrypted, but the data is invalid[invalid XML data]". Tried validating the file on another computer to no avail, any ideas? Quote Link to comment Share on other sites More sharing options...
_mat_ Posted July 2, 2017 Author Share Posted July 2, 2017 Check GPUPI.log there should be an extended error description which XML node makes the file invalid. Please post it here, might be a bug in the validation. Quote Link to comment Share on other sites More sharing options...
niobium615 Posted July 2, 2017 Share Posted July 2, 2017 Check GPUPI.log there should be an extended error description which XML node makes the file invalid. Please post it here, might be a bug in the validation. Here's the relevant data from the log file. Error while decrypting output: StreamTransformationFilter: invalid PKCS #7 block padding foundError while decrypting output: StreamTransformationFilter: invalid PKCS #7 block padding found XML validation: submission node not found! Message box: The result file was successfully decrypted, but the data is invalid [invalid XML data] (Validation result) Thanks for your help. Quote Link to comment Share on other sites More sharing options...
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