Le mar. 7 févr. 2017 23:51, Jayendra Parmar <[email protected]> a
écrit :

> 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]
>

I think this is a reference to cuda 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.
>
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