I have been struggling getting CUDA to work on Mathematica 11.3 and Manjaro Linux (kernel 4.19.16-1-MANJARO). Trying some commands I get the following:

in: CUDAQ[]
out: False
in: CUDAMap[Cos,1.0*Range[10]]
out: CUDAMap: CUDA was not able to find a valid CUDA driver.
in: CUDADriverVersion[]
out: CUDADriverVersion: CUDALink was not able to locate the NVIDIA driver binary.

However, Mathematica is able to find my GPU (as long as I run it from the terminal using "optirun mathematica"), since I can run neural network training with TargetDevice->"GPU". Also, running SystemInformation[], Mathematica find my dedicated graphics card (nVidia GTX950m)

I have installed the CUDAResources,

in: CUDAResourcesInformation[]
out: {{"Name" -> "CUDAResources", "Version" -> "11.3.154", 
   "BuildNumber" -> "", "Qualifier" -> "Lin64", 
   "WolframVersion" -> "11.3", "SystemID" -> {"Linux-x86-64"}, 
   "Description" -> "{ToolkitVersion -> v9.1, MinimumDriver -> 290}", 
   "Category" -> "", "Creator" -> "", "Publisher" -> "", 
   "Support" -> "", "Internal" -> False, 
   "Location" -> 
   3.154", "Context" -> {}, "Enabled" -> True, "Loading" -> Manual, 
   "Hash" -> "2bcd82c65870e597344b0444ebbc5c27"}}

I have the latest drivers:

$ pacman -Qs |grep nvidia
 local/lib32-nvidia-utils 1:415.27-1
 local/linux414-nvidia 1:415.27-2 (linux414-extramodules)
 local/linux419-nvidia 1:415.27-2 (linux419-extramodules)
 local/mhwd-nvidia 1:415.27-1
   MHWD module-ids for nvidia 415.27
 local/nvidia-utils 1:415.27-1
 local/opencl-nvidia 1:415.27-1

I have installed CUDA:

$ pacman -Qs |grep cuda
   local/cuda 10.0.130-2

I can run CUDA outside of Mathematica using the samples that come with the CUDA installation, e.g.:

$ optirun bin/x86_64/linux/release/deviceQuery

  CUDA Device Query (Runtime API) version (CUDART static linking)

  Detected 1 CUDA Capable device(s)

  Device 0: "GeForce GTX 950M"
    CUDA Driver Version / Runtime Version          10.0 / 10.0
    CUDA Capability Major/Minor version number:    5.0
    Total amount of global memory:                 4046 MBytes (4242604032 bytes)
    ( 5) Multiprocessors, (128) CUDA Cores/MP:     640 CUDA Cores
    GPU Max Clock rate:                            1124 MHz (1.12 GHz)
    Memory Clock rate:                             1001 Mhz
    Memory Bus Width:                              128-bit
    L2 Cache Size:                                 2097152 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 1 copy engine(s)
    Run time limit on kernels:                     Yes
    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 supports Compute Preemption:            No
    Supports Cooperative Kernel Launch:            No
    Supports MultiDevice Co-op Kernel Launch:      No
    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 = 10.0, CUDA Runtime Version = 10.0, NumDevs = 1
  Result = PASS

I do not think it is a problem with the paths, as was the issue in Are you able to use CUDA on Linux?

$ ls /usr/lib64/ |grep libnvidia

$ ls /usr/lib64/ |grep libcuda

1 Answer 1


After struggling for two days, I finally figure it out minutes after asking for help... so typical :) Nevertheless, I post my solution here in case anyone else gets stuck.

The Mathematica documentation ( https://reference.wolfram.com/language/CUDALink/tutorial/Setup.html#271291502 ) claims that the default paths for the path variables are:

$NVIDIA_DRIVER_LIBRARY /usr/lib64/libnvidia-tls.so
$CUDA_LIBRARY_PATH /usr/lib64/libcuda.so

if the path variables are not already defined. This appears to be incorrect. The variables were undefined for me, but explicitly defining them solved the problem.

In your ~/.bashrc , add the following lines (assuming your lib-files are installed at the default locations):

export NVIDIA_DRIVER_LIBRARY_PATH=/usr/lib64/libnvidia-tls.so
export CUDA_LIBRARY_PATH=/usr/lib64/libcuda.so  

Re-initate the .bashrc file by running:

$ source .bashrc

Start Mathematica with optirun (if you have both integrated and dedicated graphics cards):

$ optirun mathematica
in: Needs["CUDALink`"]
in: CUDAQ[]
out: True
  • $\begingroup$ Thanks for reporting back! $\endgroup$ Commented Feb 7, 2019 at 19:29

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service and acknowledge you have read our privacy policy.

Not the answer you're looking for? Browse other questions tagged or ask your own question.