Hi Lev:
I am not sure what is happening here but there are a few things we can do to
try and narrow things done.
1. If you run with --mca btl_smcuda_use_cuda_ipc 0 then I assume this error
will go away?
2. Do you know if when you see this error it happens on the first pass through
your
I'm using PyCUDA 2014.1 and mpi4py (git commit 3746586, uploaded today) built
against OpenMPI 1.8.4 with CUDA support activated to asynchronously send GPU
arrays between multiple Tesla GPUs (Fermi generation). Each MPI process is
associated with a single GPU; the process has a run loop that starts
Thanks guys,
I have tried two configure lines:
(1) ./configure
--prefix=/home/projects/power8/openmpi/1.8.4/gnu/4.8.2/cuda/none
--enable-mpi-thread-multiple CC=/usr/bin/gcc CXX=/usr/bin/g++
FC=/usr/bin/gfortran
(2) ./configure
--prefix=/home/projects/power8/openmpi/1.8.4/gnu/4.8.2/cuda/none
It might be helpful to send all the information listed here:
http://www.open-mpi.org/community/help/
> On Mar 26, 2015, at 10:55 PM, Ralph Castain wrote:
>
> Could you please send us your configure line?
>
>> On Mar 26, 2015, at 4:47 PM, Hammond, Simon David (-EXP)
Hello,
That's an interesting question:
Even if the GPU is physically-located inside the die, it is exposed as a
"virtual" PCI device (vendor number 1002 and model number 130f), and
that's how we detect it, and that's how the driver configures it. Many
components of the CPU die are configured
Hello,
I run lstopo on my APU A10-7850K (4CPUs + 8 GPUs), they are detected
(see included picture) but the 8 GPUs are detected on the PCI bus, while
they are on the same die as the CPUs and directly share parts of the RAM.
... I don't understand the signification of the numbers PCI 1002:130f