I assume ldconfig has properly cached cuda libraries, 

$ sudo ldconfig -v
ldconfig: Can't stat /opt/intel/composerxe/compiler/lib/intel64: No such 
file or directory
ldconfig: Can't stat /opt/intel/composerxe/mpirt/lib/intel64: No such file 
or directory
ldconfig: Can't stat /opt/intel/mpi/lib/intel64: No such file or directory
ldconfig: Can't stat /opt/intel/composerxe/tbb/lib/intel64/gcc4.4: No such 
file or directory
ldconfig: Can't stat /opt/intel/composerxe/tbb/lib/intel64/gcc4.4/irml: No 
such file or directory
ldconfig: Path `/usr/lib' given more than once
ldconfig: Path `/usr/lib64' given more than once
ldconfig: Can't stat /usr/libx32: No such file or directory
/opt/cuda/lib64:
libnppidei.so.8.0 -> libnppidei.so.8.0.44
libcudnn.so.5 -> libcudnn.so.5.0.5
libcufft.so.8.0 -> libcufft.so.8.0.44
libcuinj64.so.8.0 -> libcuinj64.so.8.0.44
libcublas.so.8.0 -> libcublas.so.8.0.45
libnppi.so.8.0 -> libnppi.so.8.0.44
libnppig.so.8.0 -> libnppig.so.8.0.44
libnvrtc.so.8.0 -> libnvrtc.so.8.0.44
libcudart.so.8.0 -> libcudart.so.8.0.44
libnppc.so.8.0 -> libnppc.so.8.0.44
libnppif.so.8.0 -> libnppif.so.8.0.44
libcusolver.so.8.0 -> libcusolver.so.8.0.44
libnppicc.so.8.0 -> libnppicc.so.8.0.44
libnvblas.so.8.0 -> libnvblas.so.8.0.44
libnpps.so.8.0 -> libnpps.so.8.0.44
libnvrtc-builtins.so.8.0 -> libnvrtc-builtins.so.8.0.44
libnppim.so.8.0 -> libnppim.so.8.0.44
libnppisu.so.8.0 -> libnppisu.so.8.0.44
libnppial.so.8.0 -> libnppial.so.8.0.44
libnvgraph.so.8.0 -> libnvgraph.so.8.0.44
libcurand.so.8.0 -> libcurand.so.8.0.44
libnppist.so.8.0 -> libnppist.so.8.0.44
libnppitc.so.8.0 -> libnppitc.so.8.0.44
libcufftw.so.8.0 -> libcufftw.so.8.0.44
libnppicom.so.8.0 -> libnppicom.so.8.0.44
libnvToolsExt.so.1 -> libnvToolsExt.so.1.0.0
libcusparse.so.8.0 -> libcusparse.so.8.0.44
libOpenCL.so.1 -> libOpenCL.so.1.0.0
/opt/cuda/nvvm/lib64:
libnvvm.so.3 -> libnvvm.so.3.1.0


On Wednesday, 8 February 2017 10:21:53 UTC+5:30, Jayendra Parmar wrote:
>
> Reading the .so file seems to be using the correct linrary
> $ readelf -a cuda_ndarray.so | grep NEEDED
>  0x0000000000000001 (NEEDED)             Shared library: [libcublas.so.8.0]
>  0x0000000000000001 (NEEDED)             Shared library: 
> [libpython3.6m.so.1.0]
>  0x0000000000000001 (NEEDED)             Shared library: [libcudart.so.7.5]
>  0x0000000000000001 (NEEDED)             Shared library: [librt.so.1]
>  0x0000000000000001 (NEEDED)             Shared library: [libpthread.so.0]
>  0x0000000000000001 (NEEDED)             Shared library: [libdl.so.2]
>  0x0000000000000001 (NEEDED)             Shared library: [libstdc++.so.6]
>  0x0000000000000001 (NEEDED)             Shared library: [libm.so.6]
>  0x0000000000000001 (NEEDED)             Shared library: [libgcc_s.so.1]
>  0x0000000000000001 (NEEDED)             Shared library: [libc.so.6]
>
> On Wednesday, 8 February 2017 09:20:31 UTC+5:30, Jayendra Parmar wrote:
>>
>> With more debugging I get error here
>>
>> https://github.com/Theano/Theano/blob/8b9f73365e4932f1c005a0a37b907d28985fbc5f/theano/gof/cmodule.py#L302
>>
>> when `nvcc_compiler` tries to load the `cuda_ndarray.so` from 
>> `cuda_ndarray` in theano cache
>>
>> comiplation phase for mod.cu runs without error.
>>
>> On Wednesday, 8 February 2017 06:59:25 UTC+5:30, Jayendra Parmar wrote:
>>>
>>> No I don't have two CUDAs in my system I have only CUDA8
>>>
>>> On Wednesday, 8 February 2017 03:27:51 UTC+5:30, nouiz wrote:
>>>>
>>>> So it probably mean your environment contain a mix of both cuda 
>>>> version. Make sure your environment variable only contain one cude 
>>>> version. 
>>>> Sometimes there is a mix. Using the env variable CUDA_ROOT or the Theano 
>>>> flag cuda.root isn't a reliable way to select which cuda version to use.
>>>>
>>>> Fred
>>>>
>>>> On Mon, Feb 6, 2017 at 10:37 AM Frédéric Bastien <[email protected]> 
>>>> wrote:
>>>>
>>>>> Delete your Theano cache. You probably have it populated with module 
>>>>> that request cuda 7.5. Run:
>>>>>
>>>>> theano-cache purge
>>>>>
>>>>> otherwise, by default it is under ~/.theano
>>>>>
>>>>> Fred
>>>>>
>>>>> On Sun, Feb 5, 2017 at 10:50 PM, Jayendra Parmar <[email protected]
>>>>> > wrote:
>>>>>
>>>>>> defintely I can run the cuda samples
>>>>>>
>>>>>> $ ./deviceQuery 
>>>>>> ./deviceQuery Starting...
>>>>>>
>>>>>>  CUDA Device Query (Runtime API) version (CUDART static linking)
>>>>>>
>>>>>> Detected 1 CUDA Capable device(s)
>>>>>>
>>>>>> Device 0: "GeForce GTX 970M"
>>>>>>   CUDA Driver Version / Runtime Version          8.0 / 7.5
>>>>>>   CUDA Capability Major/Minor version number:    5.2
>>>>>>   Total amount of global memory:                 3016 MBytes 
>>>>>> (3162570752 bytes)
>>>>>>   (10) Multiprocessors, (128) CUDA Cores/MP:     1280 CUDA Cores
>>>>>>   GPU Max Clock rate:                            1038 MHz (1.04 GHz)
>>>>>>   Memory Clock rate:                             2505 Mhz
>>>>>>   Memory Bus Width:                              192-bit
>>>>>>   L2 Cache Size:                                 1572864 bytes
>>>>>>   Maximum Texture Dimension Size (x,y,z)         1D=(65536), 
>>>>>> 2D=(65536, 65536), 3D=(4096, 4096, 4096)
>>>>>>   Maximum Layered 1D Texture Size, (num) layers  1D=(16384), 2048 
>>>>>> layers
>>>>>>   Maximum Layered 2D Texture Size, (num) layers  2D=(16384, 16384), 
>>>>>> 2048 layers
>>>>>>   Total amount of constant memory:               65536 bytes
>>>>>>   Total amount of shared memory per block:       49152 bytes
>>>>>>   Total number of registers available per block: 65536
>>>>>>   Warp size:                                     32
>>>>>>   Maximum number of threads per multiprocessor:  2048
>>>>>>   Maximum number of threads per block:           1024
>>>>>>   Max dimension size of a thread block (x,y,z): (1024, 1024, 64)
>>>>>>   Max dimension size of a grid size    (x,y,z): (2147483647, 65535, 
>>>>>> 65535)
>>>>>>   Maximum memory pitch:                          2147483647 bytes
>>>>>>   Texture alignment:                             512 bytes
>>>>>>   Concurrent copy and kernel execution:          Yes with 2 copy 
>>>>>> engine(s)
>>>>>>   Run time limit on kernels:                     No
>>>>>>   Integrated GPU sharing Host Memory:            No
>>>>>>   Support host page-locked memory mapping:       Yes
>>>>>>   Alignment requirement for Surfaces:            Yes
>>>>>>   Device has ECC support:                        Disabled
>>>>>>   Device supports Unified Addressing (UVA):      Yes
>>>>>>   Device PCI Domain ID / Bus ID / location ID:   0 / 1 / 0
>>>>>>   Compute Mode:
>>>>>>      < Default (multiple host threads can use ::cudaSetDevice() with 
>>>>>> device simultaneously) >
>>>>>>
>>>>>> deviceQuery, CUDA Driver = CUDART, CUDA Driver Version = 8.0, CUDA 
>>>>>> Runtime Version = 7.5, NumDevs = 1, Device0 = GeForce GTX 970M
>>>>>> Result = PASS
>>>>>>
>>>>>>
>>>>>> On Monday, 6 February 2017 08:59:50 UTC+5:30, Ria Chakraborty wrote:
>>>>>>>
>>>>>>> Is your GPU supported for CUDA? Check in NVIDIA website for list of 
>>>>>>> GPUs supported by CUDA.
>>>>>>>
>>>>>>> On 06-Feb-2017 8:51 AM, "Jayendra Parmar" <[email protected]> 
>>>>>>> wrote:
>>>>>>>
>>>>>>>> Tried it, but it didn't help me. Moreover I uninstalled theano and 
>>>>>>>> installed it from source, still having that issue.
>>>>>>>>
>>>>>>>> On Monday, 6 February 2017 00:34:52 UTC+5:30, Mustg Oplay wrote:
>>>>>>>>>
>>>>>>>>> May still be worth checking your theanorc file since the same 
>>>>>>>>> error can happen in windows:
>>>>>>>>>
>>>>>>>>> Add the following lines to .theanorc:
>>>>>>>>>         [nvcc]
>>>>>>>>>         flags=--cl-version=2015 -D_FORCE_INLINES
>>>>>>>>> if you do not include the cl-version then you get the error:
>>>>>>>>>
>>>>>>>>> nvcc fatal : nvcc cannot find a supported version of Microsoft 
>>>>>>>>> Visual Studio. Only the versions 2010, 2012, and 2013 are supported
>>>>>>>>>
>>>>>>>>> the D_FORCE_INLINES part is for an Ubuntu bug although I'm not 
>>>>>>>>> sure it's necessary anymore. It can help prevent this error:
>>>>>>>>>
>>>>>>>>> WARNING (theano.sandbox.cuda): CUDA is installed, but device gpu0 
>>>>>>>>> is not available (error: cuda unavailable)
>>>>>>>>>
>>>>>>>>> Note: This error seems to also show if the g++ version is too new 
>>>>>>>>> for the CUDA version.
>>>>>>>>>
>>>>>>>>> -- 
>>>>>>>>
>>>>>>>> --- 
>>>>>>>> You received this message because you are subscribed to the Google 
>>>>>>>> Groups "theano-users" group.
>>>>>>>> To unsubscribe from this group and stop receiving emails from it, 
>>>>>>>> send an email to [email protected].
>>>>>>>> For more options, visit https://groups.google.com/d/optout.
>>>>>>>>
>>>>>>> -- 
>>>>>>
>>>>>> --- 
>>>>>> You received this message because you are subscribed to the Google 
>>>>>> Groups "theano-users" group.
>>>>>> To unsubscribe from this group and stop receiving emails from it, 
>>>>>> send an email to [email protected].
>>>>>> For more options, visit https://groups.google.com/d/optout.
>>>>>>
>>>>>
>>>>>

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