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RTX 2080 TI GPU Acceleration for Deep Learning Toolbox?

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ahmet emir
ahmet emir el 2 de En. de 2021
Comentada: ahmet emir el 5 de En. de 2021
Hi,
We have one laptob and one workstation in our lab. Laptop has nvidia quadro p600 and workstation has nvidia rtx2080 ti gpu on it. I know that Matlab 2018b deep learning toolbox implements single precision operations for GPU by default. Processing power is 11 750.40 GFLOPS for RTX2080 ti and 1195 GFLOPS for Quadro P600 (defined in here) for single precision. But training time of quadro p600 of is 4x faster than rtx2080 on deep learning tooolbox for the same program. I think that rtx2080ti shold be much and much faster than quadro p600. I'm really confused. How could I accelerate training time for RTX2080 ti? Which Matlab settings must I change for this?
Would you give me advices please?
Best Regards...
  8 comentarios
ahmet emir
ahmet emir el 2 de En. de 2021
sorry you are correct p600 is much faster
ahmet emir
ahmet emir el 5 de En. de 2021
I want to try MATLAB GPU benchmark program ( here) . Laptop with quadro p600 gpu runned this program without error and the gpu testing process was completed. It works for laptop. But Z820 restart on every run of gpu bencmark after %11 progressing of testing. I'm really confused. How I come of this problem?? I set up Cuda 9.1 toolkit , RTX2080TI drivers correctly.

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