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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