This is probably going to sound wierd but "mostly no".
So, I can run like this for ten times and get the same error over and
over again. Eventually I will get a message saying no cuda devices
available, which requires me to reboot.

Sascha I will try to think of a way where I can help you reproduce it.

I don't mind waiting for the new version. But I suspect this bug is in
the cuda environment itself since I get the same error with the same
frequency of problems when running for instance gpu_md5_bruteforce.

I will play around with this some more during the coming days to see
if I can come up with some more informative output.

Thanks Kugg

On Tue, Oct 20, 2009 at 9:12 PM, Sascha Krissler <[email protected]> wrote:
> A way to reproduce would be cool. Otherwise i could
> just ignore the error and recover+restart the cuda runtime context.
> Since the new version changes quite a lot of things, i hope
> the error does not occur there.
> Do you have to reboot after those kinds of erros or can you just restart
> the application?
>
>
>> Hey sorry for my late reply, I suspect that this problem persist on
>> other cuda applicaitons.
>> How ever here is the information:
>> 1. Linux version
>> Linux kakmonstret 2.6.28-11-server #42-Ubuntu SMP Fri Apr 17 02:45:36
>> UTC 2009 x86_64 GNU/Linux
>>
>> 2. CPU info
>> vendor_id       : AuthenticAMD
>> model name      : AMD Athlon(tm) II X2 240 Processor
>> cpu MHz         : 2809.543
>>
>> 3. GPU and driver info
>> Device 0: "GeForce GTX 260"
>>   CUDA Driver Version:                           2.30
>>   CUDA Runtime Version:                          2.30
>>   CUDA Capability Major revision number:         1
>>   CUDA Capability Minor revision number:         3
>>   Total amount of global memory:                 938803200 bytes
>>   Clock rate:                                    1.46 GHz
>>
>> Device 1: "GeForce GTX 260"
>>   CUDA Driver Version:                           2.30
>>   CUDA Runtime Version:                          2.30
>>   CUDA Capability Major revision number:         1
>>   CUDA Capability Minor revision number:         3
>>   Total amount of global memory:                 939261952 bytes
>>   Clock rate:                                    1.46 GHz
>>
>> Ill try with the newer versions from: 
>> http://www.nvidia.com/object/cuda_get.html
>> and will report back if it works.
>>
>> Regards Kugg
>>
>> On Mon, Oct 5, 2009 at 6:20 PM, Sascha Krissler <[email protected]> 
>> wrote:
>> > i do not have a solution for this problem or a good guess what the problem
>> > is, so i ask you to wait for the next release and if the problem remains i 
>> > will
>> > take a look at cuda-gdb and see whether it is usable or write a kernel 
>> > that generates
>> > more debugging information.
>> > cuda-gdb should be able to print information about the error, so if you 
>> > want to invest
>> > time, you can try it out. it should be able to at least print the source 
>> > file line number
>> > of the instruction that was responsible for the error in the case of the 
>> > failed cudaThreadSynchronize,
>> > the error in the memcpy and the no_device_found are a different story as 
>> > no code is
>> > executed on the GPU in that case.
>> > maybe your drivers are too old. also if you are on a 32bit system you have 
>> > to compile
>> > with -malign-double as enabled by default in the Makefile.local.dist.
>> > Maybe you can post nvidia driver version, cpu arch and linux version.
>> >
>> >> Trying again gave me a similar error:
>> >> $ ./a51table --condition rounds:rounds=32 --roundfunc
>> >> xor:condition=distinguished_point::bits=15:generator=lfsr::tablesize=32::advance=139584
>> >> --implementation sharedmem --algorithm A51 --device
>> >> cuda:operations=512 --work random:prefix=11,0 --consume
>> >> file:prefix=data:append --logger normal generate --chains 380000000
>> >> --chainlength 3000000 --intermediate filter:runlength=512
>> >> Initialize implementation sharedmem...
>> >> 106 chains done, current rate 1.77 chains/sec (interval: 00:01:00)
>> >> 6633 chains done, current rate 108.78 chains/sec (interval: 00:01:00)
>> >> 10350 chains done, current rate 61.95 chains/sec (interval: 00:01:00)
>> >> 14632 chains done, current rate 71.37 chains/sec (interval: 00:01:00)
>> >> 19810 chains done, current rate 86.30 chains/sec (interval: 00:01:00)
>> >> ../tmto/device/cuda/working_set_methods.hpp(38)[void
>> >> tmto::device::cuda::working_set::simple_host<T,
>> >> Round>::copyToDevice(int) [with T =
>> >> tmto::device::combined_work_item<tmto::algorithm::A51::data_type,
>> >> tmto::configuration::state::state<void, void,
>> >> tmto::condition::tag::rounds,
>> >> tmto::round_function::arguments::selector<tmto::round_function::tag::xor_,
>> >> tmto::condition::tag::distinguished_point,
>> >> tmto::round_function::generator::tag::sharedmem<tmto::round_function::gen
>> >>
>> >> Trying one more time I got
>> >> $ ./a51table --condition rounds:rounds=32 --roundfunc
>> >> xor:condition=distinguished_point::bits=15:generator=lfsr::tablesize=32::advance=139584
>> >> --implementation sharedmem --algorithm A51 --device
>> >> cuda:operations=512 --work random:prefix=11,0 --consume
>> >> file:prefix=data:append --logger normal generate --chains 380000000
>> >> --chainlength 3000000 --intermediate filter:runlength=512
>> >> NVIDIA: could not open the device file /dev/nvidia0 (Input/output error).
>> >> Initialize implementation sharedmem...
>> >> ../tmto/round_function/generator/sharedmem_methods.hpp(12)[void
>> >> tmto::round_function::generator::host_part<tmto::round_function::generator::tag::sharedmem<Real>
>> >> >::copyToDevice() const [with Real =
>> >> tmto::round_function::generator::tag::lfsr]]: cuda error: no
>> >> CUDA-capable device is available
>> >>
>> >> Im running on two GeForce GTX 260's
>> >>
>> >> Regards Kugg
>> >>
>> >> On 10/4/09, Christoffer Jerkeby <[email protected]> wrote:
>> >> > Hi I got the same error, I was using the configuration generated from
>> >> > http://reflextor.com/cgi-bin/a51/a51id.cgi .
>> >> >
>> >> > $ ./a51table --condition rounds:rounds=32 --roundfunc
>> >> > xor:condition=distinguished_point::bits=15:generator=lfsr::tablesize=32::advance=139584
>> >> > --implementation sharedmem --algorithm A51 --device
>> >> > cuda:operations=512 --work random:prefix=11,0 --consume
>> >> > file:prefix=data:append --logger normal generate --chains 380000000
>> >> > --chainlength 3000000 --intermediate filter:runlength=512
>> >> >
>> >> > Initialize implementation sharedmem...
>> >> > 148 chains done, current rate 2.47 chains/sec (interval: 00:01:00)
>> >> > 6639 chains done, current rate 108.18 chains/sec (interval: 00:01:00)
>> >> > 10356 chains done, current rate 61.95 chains/sec (interval: 00:01:00)
>> >> > 14655 chains done, current rate 71.65 chains/sec (interval: 00:01:00)
>> >> > 19769 chains done, current rate 85.23 chains/sec (interval: 00:01:00)
>> >> > 24015 chains done, current rate 70.77 chains/sec (interval: 00:01:00)
>> >> > 28610 chains done, current rate 76.58 chains/sec (interval: 00:01:00)
>> >> > ../tmto/device/cuda/host_side_methods.hpp(76)[void
>> >> > tmto::device::cuda::cudaSynchronize()]: cuda error: unspecified launch
>> >> > failure
>> >> >
>> >> > Regards Kugg
>> >> >
>> >> > On 10/2/09, Sascha Krissler <[email protected]> wrote:
>> >> >> gotta love those specific cuda error codes.
>> >> >> does it happen more than just once?
>> >> >> did you use any form of signaling through the fifo, like change number 
>> >> >> of
>> >> >> operations?
>> >> >> (if it happens more frequently) does it always happen on the same card?
>> >> >> at which positions? (chains done).
>> >> >>
>> >> >>> Hi,
>> >> >>>
>> >> >>> after some time (around 2 hours) i get this error:
>> >> >>>
>> >> >>> 1334412 chains done, current rate 141.42 chains/sec (interval: 
>> >> >>> 00:01:00)
>> >> >>> ../tmto/device/cuda/host_side_methods.hpp(76)[void
>> >> >>> tmto::device::cuda::cudaSynchronize()]: cuda error: unspecified launch
>> >> >>> failure
>> >> >>>
>> >> >>> this happens only on 1 process, other processes on this machine are
>> >> >>> still running..
>> >> >>>
>
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