GPU MEX not compatible with GPU with compute capability '3.0'?

3 views (last 30 days)
Hi, I'm trying to set up the prerequisites for the GPU Coder. In the MATLAB Command Window, I entered:
gpuEnvObj = coder.gpuEnvConfig;
gpuEnvObj.BasicCodegen = 1;
gpuEnvObj.BasicCodeexec = 1;
results = coder.checkGpuInstall(gpuEnvObj)
and got the following results:
Compatible GPU : FAILED (The compute capability '3.0' of the selected GPU '0' is not supported by GPU Coder. Execution of the generated GPU MEX will not be available.)
CUDA Environment : PASSED
Runtime : PASSED
cuFFT : PASSED
cuSOLVER : PASSED
cuBLAS : PASSED
Basic Code Generation : PASSED
results =
struct with fields:
gpu: 0
cuda: 1
cudnn: 0
tensorrt: 0
basiccodegen: 1
basiccodeexec: 0
deepcodegen: 0
deepcodeexec: 0
tensorrtdatatype: 0
profiling: 0
My GPU is NVIDIA Quadro K420 (Driver version: 465.89, CUDA version 11.3). My questions are
  • Is there really no way to execute GPU Coder on my GPU? In the MATLAB documentations, I have not found descriptions about the requirement of the compute capability.
  • The result doesn't say it's impossible to generate the MEX code. Is it possible to generate the MEX code on my PC and then execute the generated code on a cluster node if the node is equipped with a better compute capability?
I appreciate any help.

Accepted Answer

Walter Roberson
Walter Roberson on 27 Mar 2022
Edited: Walter Roberson on 27 Mar 2022
  4 Comments
Daigo
Daigo on 28 Mar 2022
Edited: Daigo on 28 Mar 2022
Thank you, Walter. I installed CUDA Toolkit 10.1 and changed an enviroment variable to
  • CUDA_PATH = C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v10.1
and set the path to to the CUDA executables (C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v10.1\bin)
I restarted my PC and confirmed that the CUDA Toolkit is correctly installed by entering `nvcc --version` on command prompt:
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2019 NVIDIA Corporation
Built on Fri_Feb__8_19:08:26_Pacific_Standard_Time_2019
Cuda compilation tools, release 10.1, V10.1.105
However, still, I get the GPU compatibility error. Here is the input of the GPU Environment Check App:
and here is the result I got:
Does the driver API version also need to be 10.1? According to this post, CUDA has 2 primary APIs: Runtime API and Driver API. Currently, my Runtime API version (result of nvcc --version on cmd0) is 10.1 but my Driver API version (result of nvidia-smi on cmd) is 11.3. In the same post, it is discussed that this kind of inconsistency won't cause any problem in general, but I'm not sure that is the case for the use of GPU Coder.

Sign in to comment.

More Answers (0)

Categories

Find more on Get Started with GPU Coder in Help Center and File Exchange

Products


Release

R2020a

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!