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Why do I receive an "cuDriverGetVersion" was not found error when calling the gpuArray function in Parallel Computnig Toolbox 5.0 (R2010b)?

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I am interested in GPU Computation functionality of Parallel Computing Toolbox 5.0 (R2010b). I have an NVIDIA graphics card that supports CUDA. When I attempt to use GPU Computation functionality by calling the GPUARRAY function I get the following error:
ERROR: The CUDA driver was found, but the function "cuDriverGetVersion" was not found.
This can occur with old versions of CUDA. The library name used was: "nvcuda.dll".
The required CUDA version is: 3 or greater.

Accepted Answer

MathWorks Support Team
MathWorks Support Team on 23 Jun 2021
Edited: MathWorks Support Team on 23 Jun 2021
The error indicates that the version of NVIDIA CUDA library installed on your system is out of date. To resolve this issue:
1. Verify that the NVIDIA graphics card you are using has CUDA Compute Capability of 1.3 or higher. A list of CUDA enabled graphics cards and their associated Compute Capability can be found at the following links:
If your card is not listed in the resources above, or does not have the Compute Capability of 1.3 or higher it is not supported for GPU Computation in Parallel Computing Toolbox 5.0.
2. If your card is listed in one of the above mentioned links and has Compute Capability of 1.3 or higher update the graphics drivers. The latest version of NVIDIA drivers can be found at:
3. Install the CUDA Toolkit. The CUDA Toolkit can be downloaded from:
4. After updating the drivers and installing the CUDA Toolkit start MATLAB.
5. At the MATLAB Command Prompt type:
>>paralleldemo_gpu_devices
This will test whether MATLAB recognizes your GPU. If everything went well you should see output similar to:
DeviceName: 'Tesla C1060'
DeviceIndex: 1
ComputeCapability: 1.3000
DeviceSupportsDouble: 1
DriverVersion: 3
MaxThreadsPerBlock: 512
MaxShmemPerBlock: 16384
MaxThreadBlockSize: [512 512 64]
MaxGridSize: [65535 65535]
SIMDWidth: 32
TotalMemory: 4.2948e+09
FreeMemory: 4.2573e+09
MultiprocessorCount: 30
GPUOverlapsTransfers: 1
KernelExecutionTimeout: 0
DeviceSupported: 1

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