Linux CUDA 'Special' App finally available, featuring Low CPU use

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Message 1894702 - Posted: 11 Oct 2017, 20:00:02 UTC - in response to Message 1894685.  
Last modified: 11 Oct 2017, 20:02:48 UTC

Do we have this task offline?
Here you go, Raistmer: WU2705262578

Got it, thanks.
Still had to restore building environment to hunt any bugs in OpenCL and very limited on free time to setup Linux host to help with Petri's app bughunting but TestCase reserved for the future...


Thanks for any help you can provide. All help needed. Insights, ideas, ... Thank you.

EDIT: Saved the wu too to include it into my development test cycle.

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Message 1894708 - Posted: 11 Oct 2017, 20:30:24 UTC - in response to Message 1894701.  
Last modified: 11 Oct 2017, 20:34:21 UTC

Hi,

zi3t2 may report wrong pulses time to time. It should not be used.
Petri
Does that apply to zi3t2b as well? I have that version running on 2 of my Linux boxes, but have zi3v running on the other one. The reason I haven't moved all of them to zi3v is that annoying problem with restarted tasks spewing out phantom spikes or triplets after the restart until the task overflows, resulting in the task getting marked Invalid. About 20% of my restarted tasks on the zi3v box end up that way, while in all the months that I've been running zi3t2b, I think I've only seen one single task behave that way.

EDIT: Meant to say 15%, or about 3 per week out of 20 restarted tasks.
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Message 1894713 - Posted: 11 Oct 2017, 20:45:17 UTC - in response to Message 1894708.  
Last modified: 11 Oct 2017, 20:46:35 UTC

Hi,

zi3t2 may report wrong pulses time to time. It should not be used.
Petri
Does that apply to zi3t2b as well? I have that version running on 2 of my Linux boxes, but have zi3v running on the other one. The reason I haven't moved all of them to zi3v is that annoying problem with restarted tasks spewing out phantom spikes or triplets after the restart until the task overflows, resulting in the task getting marked Invalid. About 20% of my restarted tasks on the zi3v box end up that way, while in all the months that I've been running zi3t2b, I think I've only seen one single task behave that way.

EDIT: Meant to say 15%, or about 3 per week out of 20 restarted tasks.


EDIT: Sorry. I'll check and TBar will chek.

Check your code for t2b. If the pulse find code does not have C_SCAN then it should not be used.

grep C_SCAN cuda/*.cu

The command should find a lot of lines. If none is found it does not have sequential scan in it.

I'll add the restart problem to my to do list.
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Message 1894718 - Posted: 11 Oct 2017, 20:54:17 UTC - in response to Message 1894605.  

As far as I know, the previously discovered Best Gaussian problem discovered with the Windows SoG App DOES cross validate, and STILL EXISTS. You don't seem very concerned about that problem, and it's actually more troublesome than an occasional race condition with the Best Pulse.
It's not that problems like that don't still concern me, it's just that it's been pretty thoroughly discussed and enough examples of the issue have already been posted. I try to keep an eye out for issues that appear in the latest versions of the apps, whether they're new problems, or continuing ones that I would hope would have been fixed in those newer versions. The two Best Pulse examples that I posted are the first I've seen with the Cuda 9.0 app and, since I'm not the one running that version, they only show up to me when one of my wingmen is running it and then that WU shows up in my Inconclusives list.
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Message 1894727 - Posted: 11 Oct 2017, 21:52:29 UTC - in response to Message 1894701.  


To the pulse issue that is not a pulse (Not a reported one): Do not look at the peak. Look at the score. Score is used to determine if a pulse should be reported. The s2 sometimes misses one but that is a rare occasion.

The single signal if I recall correctly where score depends not only from peak is Gaussian.
In all other peak and score correlate monotonically.


Then, if it is said by the administration that a pulse should be reported the it will -- and they allow half of them to be wrong.

Very bad point of view and approach in general. For result to be correct ALL signals should match in ~1% tolerance. No any "half to be wrong" at all! Where "half" appears is just credits awards to encourage users to continue participation, nothing more. Devs should never take this into account. We are here not to collect credits.

If the score is less than a given threshold then it is reported as best so far just to make the screen saver happy and to make an educated guesses of a sequential apps inner workings.

Nope. To check processing correctness even on relatively silent data sets.

The is no scientific meaning in those not reported but best anyway still pulses. They are there to prevent faking. One could say that no pulses were found without scanning through all possibilities. The best but not reported is a sanity check. If my app fails that sometimes it is not so big a deal.

So it has meaning. Yes, some sort of CRC for processing pipeline to be short.
And I'm working on it.

That's good part. Either processing logic for "best" in your app greatly differs from "reportable" or issue with best could show itself on reportable ones too. So better to explore this more.



The bigger problem is that there are people running zi3t2 that is faster but does not sometimes report all true pulses. The t2 has a parallel only pulse search (it is fast) but it is not valid. The s2 is far much better. When it finds a suspect best or a true pulse it reverts back to sequential search. The t2 does not.

That's usual issue with any open testing. Not all testers follow guidlines. And that's why we all agreed so far that Windows builds should be postponed.

My SW does all the work needed. No faking. Everything is computed.

Nobody suspect anything else AFAIK. But your code just as stock one is GPL so available. And nor you not anyone else could prevent to use it in malice way. So as baseline we should not neglect "CRC checking".

The problem is in (storing intermediate results on same PoT) the reporting, my lack of time during the weeks I have to go to the work and the day having only 24 hours in it during the weekends.

And that would require additional serialization perhaps. And any serialization quite slow on big GPUs. That will constitute an issue when you will face the need to replace "fast but wrong some time" to "rock-stable but a little slower". Especially taking into account that "half could be wrong" part and obsession with credits for some participants.
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Message 1894742 - Posted: 11 Oct 2017, 23:56:28 UTC - in response to Message 1894718.  
Last modified: 11 Oct 2017, 23:58:12 UTC

As far as I know, the previously discovered Best Gaussian problem discovered with the Windows SoG App DOES cross validate, and STILL EXISTS. You don't seem very concerned about that problem, and it's actually more troublesome than an occasional race condition with the Best Pulse.
It's not that problems like that don't still concern me, it's just that it's been pretty thoroughly discussed and enough examples of the issue have already been posted. I try to keep an eye out for issues that appear in the latest versions of the apps, whether they're new problems, or continuing ones that I would hope would have been fixed in those newer versions. The two Best Pulse examples that I posted are the first I've seen with the Cuda 9.0 app and, since I'm not the one running that version, they only show up to me when one of my wingmen is running it and then that WU shows up in my Inconclusives list.
Hmmm, where has the problem with the SoG Best Gaussian been thoroughly discussed other than this thread? I must have missed that. The Best Pulse problem with the CUDA App has been run into the ground, go back to the first page of this thread and you will find it there. There is a difference though, we still don't know what causes the problem with the Rare Bad Best Pulse whereas we Do know the problem with the SoG OpenCL App and Bad Best Gaussian. Just use the Non-SoG OpenCL App and the Bad Best Gaussian goes away. We are still working on the Bad Best Pulse and fortunately it is rare and only effects around 100 people, it also rarely gets by the Validation phase. On the other hand, there are 1000s of times more people using the SoG App and it constantly slips by because other SoG Apps validate against it. The only time it shows itself is against other Apps such as the CPU only machines. Don't bother looking for it on an SoG machine, just look at a CPU machine, https://setiathome.berkeley.edu/workunit.php?wuid=2675920971
Best gaussian: peak=4.105192, mean=0.5110582, ChiSq=1.134106, time=39.43, d_freq=1420289942.89, score=2.552872, null_hyp=2.239423, chirp=-30.138, fft_len=16k
Best gaussian: peak=3.76384, mean=0.5175309, ChiSq=1.381263, time=41.1, d_freq=1420289892.33, score=2.347487, null_hyp=2.354173, chirp=-30.138, fft_len=16k

Do you have any idea how many of the SoG Tasks are Cross Validating with the Wrong Bad Best Gaussian? Let me put it this way, the Bad Best Pulse numbers Pale in comparison.
But, we know the source of the Gaussian problem, it could be fixed very simply. However, it appears people have decided not to worry about all those Bad Best Gaussians and instead focus on the Rare CUDA Best Pulse. Some of us know the Score, I would suggest you consider the people that have decided all those Bad Best Gaussians are OK before giving Petri a hard time about a much less common problem. As he said, he is working on it. If others want to help they are more than welcome, it would be very easy to setup a nVidia machine with the Special CUDA App. Install the OS then add this package, http://www.arkayn.us/forum/index.php?topic=197.msg4515#msg4515

BTW Raistmer, do you think you could help convince Eric to switch the Mac ATI App over to the non-SoG version? As more people update to the new OS the number of Failed tasks are going to be impressive.
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Message 1894746 - Posted: 12 Oct 2017, 0:31:45 UTC

Too much here to read through the whole thread when it goes on for several pages on how to install Ubuntu so please forgive it's been asked in the many pages in between.

I already have a BOINC install I don't want to mess with. Can I copy over these files in from the below link to the SETI project directory that I have now? I have a single 1070 and when I compared with several of the top hosts they are producing a lot more per Run time/GPU.

http://www.arkayn.us/forum/index.php?topic=197.msg4515#msg4515
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Message 1894754 - Posted: 12 Oct 2017, 1:00:48 UTC - in response to Message 1894746.  
Last modified: 12 Oct 2017, 1:35:00 UTC

You just need to download the 3 parts of the package in the message and unpack them to your Desktop. Double-click on the BOINC client and you are up and running. Also the message states you need to download the CUDA 8.0 libraries from the location in the readme.txt file and put those files into the SETI project directory the package created. The package already has the necessary AP and MB files with the app_info for those applications already installed. Couldn't be more simple. You might just need to write your own app_config to tailor exactly how you want to run the tasks.
[Edit] Read your post again and missed the existing BOINC install under Linux. You just need to add the special app, download the CUDA 8.0 libraries and rewrite your app_info to handle the special app declaration.
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Message 1894764 - Posted: 12 Oct 2017, 4:04:20 UTC - in response to Message 1894742.  

Hmmm, where has the problem with the SoG Best Gaussian been thoroughly discussed other than this thread? I must have missed that. The Best Pulse problem with the CUDA App has been run into the ground,
Why does it need to be discussed elsewhere? If any topic was run into the ground, I'd say it was the Best Gaussian. I know. I was pretty deeply involved in that back in June, spending a lot of time combing through my Inconclusives and posting many, many examples. But it seems to me that the ultimate conclusion was that it might not be exclusive to SoG. That, in fact, there was some divergence in the code paths that went back several years. As I recall, Jason had intended to dig into it some more but he's been kind of disengaged since then. Perhaps when he drifts back in, the discussion can pick up. In the meantime, unless something changes, it seems rather pointless to keep posting additional examples.

And whether or not the Best Pulse problem with the CUDA app has been "run into the ground", the fact that a new version of the Special App has started showing up makes it eminently reasonable to take a close look at the results to see if anything has changed, been improved, or fixed. Simply because it's a few seconds faster doesn't mean we should all bow down, close our eyes and just give thanks. If a new SoG app had arrived, the same scrutiny should be applied. The difference there is that new SoG apps (and just about every other new app) hit Beta first, whereas the Special App just goes straight to Broadway. Hence, close scrutiny is even more important.
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Message 1894789 - Posted: 12 Oct 2017, 7:06:18 UTC - in response to Message 1894742.  


But, we know the source of the Gaussian problem, it could be fixed very simply.

Really? Send me the patch then please. I'll add it to repo from old host.

BTW Raistmer, do you think you could help convince Eric to switch the Mac ATI App over to the non-SoG version? As more people update to the new OS the number of Failed tasks are going to be impressive.

Think it's possible. Just abandon some of plan classes for Mac. Post few such hosts please.
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Message 1894794 - Posted: 12 Oct 2017, 8:11:39 UTC - in response to Message 1894789.  
Last modified: 12 Oct 2017, 8:12:41 UTC

When I tested it in Linux all I had to do was use the Non-SoG version to solve the Best Gaussian problem. If you look at the Apps page it shows Windows as the only platform that doesn't have a Non-SoG nVidia App. I would suggest you build a Non-SoG Windows App and see if it has the Gaussian problem, I'd wager it won't.

You can see the Mac results at Beta, along with the posts in the Questions & Answers section,
http://setiweb.ssl.berkeley.edu/beta/setiathome_v8_x86_64-apple-darwin__opencl_ati5_mac.html
http://setiweb.ssl.berkeley.edu/beta/setiathome_v8_x86_64-apple-darwin__opencl_ati5_SoG_mac.html
SoG OS 17.0.0 : hosts_success 0.5000 : results_success 0.6091
Non SoG OS 17.0.0 : hosts_success 1.0000 : results_success 0.8854
This Host just changed to the Non SoG App after posting in Q & A, https://setiathome.berkeley.edu/results.php?hostid=8248108&offset=40
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Message 1894808 - Posted: 12 Oct 2017, 11:59:19 UTC
Last modified: 12 Oct 2017, 11:59:54 UTC

Hmm

What to do about this? Running Mint 17.3 with Nvidia 384.90..

"<core_client_version>7.2.42</core_client_version>
<![CDATA[
<message>
process exited with code 127 (0x7f, -129)
</message>
<stderr_txt>
../../projects/setiathome.berkeley.edu/setiathome_x41zi3xs2_x86_64-pc-linux-gnu_cuda90_static: relocation error: ../../projects/setiathome.berkeley.edu/setiathome_x41zi3xs2_x86_64-pc-linux-gnu_cuda90_static: symbol _ZTVNSt7__cxx1119basic_istringstreamIcSt11char_traitsIcESaIcEEE, version GLIBCXX_3.4.21 not defined in file libstdc++.so.6 with link time reference

</stderr_txt>
]]>
"

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Message 1894836 - Posted: 12 Oct 2017, 13:22:51 UTC - in response to Message 1894794.  

When I tested it in Linux all I had to do was use the Non-SoG version to solve the Best Gaussian problem. If you look at the Apps page it shows Windows as the only platform that doesn't have a Non-SoG nVidia App. I would suggest you build a Non-SoG Windows App and see if it has the Gaussian problem, I'd wager it won't.

To use another app doesn't mean to fix the bug. Any bug in any software could be "fixed" by abandon app usage ;)


You can see the Mac results at Beta, along with the posts in the Questions & Answers section,
http://setiweb.ssl.berkeley.edu/beta/setiathome_v8_x86_64-apple-darwin__opencl_ati5_mac.html
http://setiweb.ssl.berkeley.edu/beta/setiathome_v8_x86_64-apple-darwin__opencl_ati5_SoG_mac.html
SoG OS 17.0.0 : hosts_success 0.5000 : results_success 0.6091
Non SoG OS 17.0.0 : hosts_success 1.0000 : results_success 0.8854
This Host just changed to the Non SoG App after posting in Q & A, https://setiathome.berkeley.edu/results.php?hostid=8248108&offset=40

I'll take detailed look, thanks.
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Message 1894898 - Posted: 12 Oct 2017, 18:36:56 UTC - in response to Message 1894808.  

version GLIBCXX_3.4.21 not defined in file libstdc++.so.6 with link time reference
That's similar to the problems I saw with Ubuntu 14.04.1. You probably need a newer version of Mint with the static App. I've been able to compile other versions in Ubuntu 14.04.1 and even 12.04.5 that work with the older systems, but, I'm still testing it. For now you'll probably need Mint 18.2 for Petri's App.
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Message 1895056 - Posted: 13 Oct 2017, 16:19:31 UTC

So far the version of zi3xs2 compiled in Ubuntu 12.04.5 seems to be working normally. It still has the same occasional Bad Best Pulse it's had Forever, but, the biggest problem is all the Inconclusive Instant Overflows which account for over half the inconclusive count. Ever so often one of the Instant Overflows is given an Invalid. If those Overflow Inconclusives could be reduced it would look Much better. I haven't been able to compile it in anything other than CUDA 9, so, if the CUDA 9 version doesn't work on the Kepler cc 3.5 GPUs there isn't much hope for them.
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Message 1895064 - Posted: 13 Oct 2017, 17:10:36 UTC - in response to Message 1894836.  

@TBar
Lets continue discussion on required Mac ATi apps modification on beta site.
I posted some questions there please respond (there).
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Message 1895065 - Posted: 13 Oct 2017, 17:12:12 UTC - in response to Message 1895056.  

Ever so often one of the Instant Overflows is given an Invalid.

Does wingman report overflow (different set but overflow) also?
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Message 1895068 - Posted: 13 Oct 2017, 17:44:20 UTC - in response to Message 1895065.  
Last modified: 13 Oct 2017, 17:46:50 UTC

This is a Typical Invalid Overflow, https://setiathome.berkeley.edu/workunit.php?wuid=2708379644
The way I remember it, the CUDA App looks for Triplets First. If a Task starts with many Triplets the Overflow result will be 30 Triplets.
If the App looks for Something Else First, such as the SoG App, then the results will most likely be 30 of whatever it is looking for, i.e. Not Triplets.
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Message 1895069 - Posted: 13 Oct 2017, 17:51:57 UTC - in response to Message 1895068.  

This is a Typical Invalid Overflow, https://setiathome.berkeley.edu/workunit.php?wuid=2708379644
The way I remember it, the CUDA App looks for Triplets First. If a Task starts with many Triplets the Overflow result will be 30 Triplets.
If the App looks for Something Else First, such as the SoG App, then the results will most likely be 30 of whatever it is looking for, i.e. Not Triplets.
It actually may not be that simple. During an email exchange I had with Petri about a month ago regarding this problem, he said "I looked at my code and the pulses are checked before triplets. So it is not so an easy fix I thought. I will have to debug why my code misses many pulses on noisy packets and then some on 'normal' data."

To complicate it further, it seems to be a problem that already exists in the older Cuda apps, as I noted previously, so it may be in some code that Petri's app actually inherited from the stock Cuda code. It just never surfaced until the 4-bit WUs started to flow.
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Message 1895105 - Posted: 13 Oct 2017, 20:30:57 UTC

I'm seeing a different type of Invalid Overflow now...and it looks Strange.
There are 3 results, https://setiathome.berkeley.edu/workunit.php?wuid=2708604299

SSSE3xj OS X 64bit Build 3551
Triplet: peak=7.605578, time=27.31, period=0.03768, d_freq=1419997253.42, chirp=0, fft_len=32
Spike: peak=24.94688, time=18.19, d_freq=1420003004.07, chirp=0, fft_len=1024
Spike: peak=26.08626, time=5.767, d_freq=1419999151.23, chirp=0, fft_len=2k
Spike: peak=26.18389, time=18.14, d_freq=1420003004.07, chirp=0, fft_len=2k
Spike: peak=26.96174, time=0.2097, d_freq=1419999146.46, chirp=0, fft_len=4k
Spike: peak=25.01482, time=0.6291, d_freq=1419999146.46, chirp=0, fft_len=4k
Spike: peak=27.75963, time=1.049, d_freq=1419999146.46, chirp=0, fft_len=4k
Spike: peak=25.49809, time=1.468, d_freq=1419999146.46, chirp=0, fft_len=4k
Spike: peak=31.66115, time=1.887, d_freq=1419999146.46, chirp=0, fft_len=4k
Spike: peak=30.64291, time=2.307, d_freq=1419999146.46, chirp=0, fft_len=4k
Spike: peak=26.10745, time=2.726, d_freq=1419999146.46, chirp=0, fft_len=4k
Spike: peak=26.03222, time=3.146, d_freq=1419999146.46, chirp=0, fft_len=4k
Spike: peak=27.84687, time=3.985, d_freq=1419999146.46, chirp=0, fft_len=4k
Spike: peak=36.50471, time=5.243, d_freq=1419999151.23, chirp=0, fft_len=4k
Spike: peak=40.21223, time=5.662, d_freq=1419999151.23, chirp=0, fft_len=4k
Spike: peak=34.20884, time=6.082, d_freq=1419999151.23, chirp=0, fft_len=4k
Spike: peak=28.26171, time=6.921, d_freq=1419999151.23, chirp=0, fft_len=4k
Spike: peak=26.50147, time=7.34, d_freq=1419999151.23, chirp=0, fft_len=4k
Spike: peak=39.61049, time=7.759, d_freq=1419999151.23, chirp=0, fft_len=4k
Spike: peak=32.48127, time=8.179, d_freq=1419999151.23, chirp=0, fft_len=4k
Spike: peak=36.98731, time=8.598, d_freq=1419999151.23, chirp=0, fft_len=4k
Spike: peak=34.13403, time=9.437, d_freq=1419999151.23, chirp=0, fft_len=4k
Spike: peak=34.47166, time=10.28, d_freq=1419999151.23, chirp=0, fft_len=4k
Spike: peak=30.22753, time=10.7, d_freq=1419999151.23, chirp=0, fft_len=4k
Spike: peak=29.06599, time=11.11, d_freq=1419999151.23, chirp=0, fft_len=4k
Spike: peak=31.13299, time=12.37, d_freq=1419999151.23, chirp=0, fft_len=4k
Spike: peak=28.21013, time=12.79, d_freq=1419999151.23, chirp=0, fft_len=4k
Spike: peak=27.57712, time=13.63, d_freq=1419999151.23, chirp=0, fft_len=4k
Spike: peak=29.07048, time=14.05, d_freq=1419999151.23, chirp=0, fft_len=4k
Spike: peak=34.00376, time=14.47, d_freq=1419999151.23, chirp=0, fft_len=4k
OpenCL queue synchronized
SETI@Home Informational message -9 result_overflow
NOTE: The number of results detected equals the storage space allocated.

Best spike: peak=40.21223, time=5.662, d_freq=1419999151.23, chirp=0, fft_len=4k
Best autocorr: peak=0, time=-2.12e+11, delay=0, d_freq=0, chirp=0, fft_len=0
Best gaussian: peak=0, mean=0, ChiSq=0, time=-2.12e+11, d_freq=0,
score=-12, null_hyp=0, chirp=0, fft_len=0
Best pulse: peak=3.214275, time=62.38, period=0.01748, d_freq=1419997558.59, score=0.9178, chirp=0, fft_len=16
Best triplet: peak=7.605578, time=27.31, period=0.03768, d_freq=1419997253.42, chirp=0, fft_len=32

Spike count: 29
Autocorr count: 0
Pulse count: 0
Triplet count: 1
Gaussian count: 0


SSE3xj Win32 Build 3584
Triplet: peak=7.605577, time=27.31, period=0.03768, d_freq=1419997253.42, chirp=0, fft_len=32
Spike: peak=24.94678, time=18.19, d_freq=1420003004.07, chirp=0, fft_len=1024
Spike: peak=26.08626, time=5.767, d_freq=1419999151.23, chirp=0, fft_len=2k
Spike: peak=26.18378, time=18.14, d_freq=1420003004.07, chirp=0, fft_len=2k
Spike: peak=26.96158, time=0.2097, d_freq=1419999146.46, chirp=0, fft_len=4k
Spike: peak=25.01468, time=0.6291, d_freq=1419999146.46, chirp=0, fft_len=4k
Spike: peak=27.75947, time=1.049, d_freq=1419999146.46, chirp=0, fft_len=4k
Spike: peak=25.49793, time=1.468, d_freq=1419999146.46, chirp=0, fft_len=4k
Spike: peak=31.66096, time=1.887, d_freq=1419999146.46, chirp=0, fft_len=4k
Spike: peak=30.64272, time=2.307, d_freq=1419999146.46, chirp=0, fft_len=4k
Spike: peak=26.10729, time=2.726, d_freq=1419999146.46, chirp=0, fft_len=4k
Spike: peak=26.03206, time=3.146, d_freq=1419999146.46, chirp=0, fft_len=4k
Spike: peak=27.84688, time=3.985, d_freq=1419999146.46, chirp=0, fft_len=4k
Spike: peak=36.5047, time=5.243, d_freq=1419999151.23, chirp=0, fft_len=4k
Spike: peak=40.21225, time=5.662, d_freq=1419999151.23, chirp=0, fft_len=4k
Spike: peak=34.20885, time=6.082, d_freq=1419999151.23, chirp=0, fft_len=4k
Spike: peak=28.2617, time=6.921, d_freq=1419999151.23, chirp=0, fft_len=4k
Spike: peak=26.50144, time=7.34, d_freq=1419999151.23, chirp=0, fft_len=4k
Spike: peak=39.61047, time=7.759, d_freq=1419999151.23, chirp=0, fft_len=4k
Spike: peak=32.48125, time=8.179, d_freq=1419999151.23, chirp=0, fft_len=4k
Spike: peak=36.98729, time=8.598, d_freq=1419999151.23, chirp=0, fft_len=4k
Spike: peak=34.13402, time=9.437, d_freq=1419999151.23, chirp=0, fft_len=4k
Spike: peak=34.47162, time=10.28, d_freq=1419999151.23, chirp=0, fft_len=4k
Spike: peak=30.22751, time=10.7, d_freq=1419999151.23, chirp=0, fft_len=4k
Spike: peak=29.06596, time=11.11, d_freq=1419999151.23, chirp=0, fft_len=4k
Spike: peak=31.13296, time=12.37, d_freq=1419999151.23, chirp=0, fft_len=4k
Spike: peak=28.2101, time=12.79, d_freq=1419999151.23, chirp=0, fft_len=4k
Spike: peak=27.57712, time=13.63, d_freq=1419999151.23, chirp=0, fft_len=4k
Spike: peak=29.07047, time=14.05, d_freq=1419999151.23, chirp=0, fft_len=4k
Spike: peak=34.00376, time=14.47, d_freq=1419999151.23, chirp=0, fft_len=4k
OpenCL queue synchronized
SETI@Home Informational message -9 result_overflow
NOTE: The number of results detected equals the storage space allocated.

Best spike: peak=20213.88, time=20.13, d_freq=1420000000, chirp=0.003697, fft_len=128k
Best autocorr: peak=22.41543, time=33.55, delay=0.028262, d_freq=1419999999.29, chirp=-0.021258, fft_len=128k
Best gaussian: peak=0, mean=0, ChiSq=0, time=-2.12e+011, d_freq=0,
score=-12, null_hyp=0, chirp=0, fft_len=0
Best pulse: peak=3.214275, time=62.38, period=0.01748, d_freq=1419997558.59, score=0.9178, chirp=0, fft_len=16
Best triplet: peak=7.605577, time=27.31, period=0.03768, d_freq=1419997253.42, chirp=0, fft_len=32
Spike count: 29
Autocorr count: 0
Pulse count: 0
Triplet count: 1
Gaussian count: 0


Invalid x41p_zi3xs2, Cuda 9.00 special
Triplet: peak=7.605577, time=27.31, period=0.03768, d_freq=1419997253.42, chirp=0, fft_len=32
Spike: peak=24.44525, time=0.1245, d_freq=1420000000, chirp=0, fft_len=128
Spike: peak=24.64931, time=0.1507, d_freq=1420000000, chirp=0, fft_len=128
Spike: peak=29.38325, time=0.2032, d_freq=1420000000, chirp=0, fft_len=128
Spike: peak=24.58589, time=0.2425, d_freq=1420000000, chirp=0, fft_len=128
Spike: peak=28.28773, time=0.3211, d_freq=1420000000, chirp=0, fft_len=128
Spike: peak=27.24811, time=0.3867, d_freq=1420000000, chirp=0, fft_len=128
Spike: peak=25.1134, time=0.4129, d_freq=1420000000, chirp=0, fft_len=128
Spike: peak=25.7655, time=0.4391, d_freq=1420000000, chirp=0, fft_len=128
Spike: peak=26.09805, time=0.4784, d_freq=1420000000, chirp=0, fft_len=128
Spike: peak=28.27009, time=0.544, d_freq=1420000000, chirp=0, fft_len=128
Spike: peak=24.53212, time=0.5964, d_freq=1420000000, chirp=0, fft_len=128
Spike: peak=28.57932, time=0.793, d_freq=1420000000, chirp=0, fft_len=128
Spike: peak=25.83549, time=0.911, d_freq=1420000000, chirp=0, fft_len=128
Spike: peak=24.35911, time=0.9372, d_freq=1420000000, chirp=0, fft_len=128
Spike: peak=24.07095, time=0.9503, d_freq=1420000000, chirp=0, fft_len=128
Spike: peak=26.67465, time=1.068, d_freq=1420000000, chirp=0, fft_len=128
Spike: peak=24.38368, time=1.081, d_freq=1420000000, chirp=0, fft_len=128
Spike: peak=26.40218, time=1.409, d_freq=1420000000, chirp=0, fft_len=128
Spike: peak=26.35513, time=1.488, d_freq=1420000000, chirp=0, fft_len=128
Spike: peak=24.82981, time=1.514, d_freq=1420000000, chirp=0, fft_len=128
Spike: peak=25.65816, time=1.606, d_freq=1420000000, chirp=0, fft_len=128
Spike: peak=24.29915, time=1.658, d_freq=1420000000, chirp=0, fft_len=128
Spike: peak=24.42895, time=1.71, d_freq=1420000000, chirp=0, fft_len=128
Spike: peak=24.36757, time=1.75, d_freq=1420000000, chirp=0, fft_len=128
Spike: peak=25.86758, time=1.789, d_freq=1420000000, chirp=0, fft_len=128
Spike: peak=24.92279, time=1.855, d_freq=1420000000, chirp=0, fft_len=128
Spike: peak=29.19098, time=2.156, d_freq=1420000000, chirp=0, fft_len=128
Spike: peak=24.90061, time=2.195, d_freq=1420000000, chirp=0, fft_len=128
Spike: peak=24.25422, time=2.209, d_freq=1420000000, chirp=0, fft_len=128
SETI@Home Informational message -9 result_overflow
NOTE: The number of results detected equals the storage space allocated.

Best spike: peak=29.38325, time=0.2032, d_freq=1420000000, chirp=0, fft_len=128
Best autocorr: peak=0, time=-2.12e+11, delay=0, d_freq=0, chirp=0, fft_len=0
Best gaussian: peak=0, mean=0, ChiSq=0, time=-2.12e+11, d_freq=0,
score=-12, null_hyp=0, chirp=0, fft_len=0
Best pulse: peak=3.214274, time=62.38, period=0.01748, d_freq=1419997558.59, score=0.9178, chirp=0, fft_len=16
Best triplet: peak=7.605577, time=27.31, period=0.03768, d_freq=1419997253.42, chirp=0, fft_len=32
Spike count: 29
Autocorr count: 0
Pulse count: 0
Triplet count: 1
Gaussian count: 0

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