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How to Get the CUDA and cuDNN Version on Windows with Anaconda

In the world of data science, CUDA and cuDNN are essential tools for accelerating deep learning tasks. CUDA, or Compute Unified Device Architecture, is a parallel computing platform and API model created by NVIDIA. It allows developers to use NVIDIA GPUs for general purpose processing. On the other hand, cuDNN, or CUDA Deep Neural Network library, is a GPU-accelerated library for deep neural networks. It provides highly optimized primitives for deep learning.
By Saturn Cloud | | Miscellaneous

How to Get the CUDA and cuDNN Version on Windows with Anaconda

In the world of data science, CUDA and cuDNN are essential tools for accelerating deep learning tasks. CUDA, or Compute Unified Device Architecture, is a parallel computing platform and API model created by NVIDIA. It allows developers to use NVIDIA GPUs for general purpose processing. On the other hand, cuDNN, or CUDA Deep Neural Network library, is a GPU-accelerated library for deep neural networks. It provides highly optimized primitives for deep learning.

In this blog post, we will guide you on how to get the CUDA and cuDNN version on Windows with Anaconda installed. This will be beneficial for data scientists who want to ensure that their deep learning libraries are compatible with their CUDA and cuDNN versions.

Prerequisites

Before we start, make sure you have the following:

  • Windows 10
  • Anaconda installed
  • NVIDIA GPU (optional, but recommended for deep learning tasks)

Step 1: Open Anaconda Prompt

First, open the Anaconda Prompt. You can do this by searching for “Anaconda Prompt” in the Windows search bar and clicking on it.

Step 2: Check CUDA Version

To check the CUDA version, type the following command in the Anaconda Prompt:

nvcc --version

This command will display the CUDA version installed on your system. The output should look something like this:

nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2020 NVIDIA Corporation
Built on Wed_Jul_22_19:09:09_PDT_2020
Cuda compilation tools, release 11.0, V11.0.221
Build cuda_11.0_bu.TC445_37.28845127_0

In this example, the CUDA version is 11.0.

Step 3: Check cuDNN Version

Checking the cuDNN version is a bit more complicated because there is no direct command to do it. However, you can check the cuDNN version by looking at the header file located in the CUDA directory.

First, navigate to the CUDA directory by typing the following command in the Anaconda Prompt:

cd %CUDA_PATH%/include

Then, open the cuDNN header file by typing:

notepad cudnn.h

This will open the cudnn.h file in Notepad. Look for the line that defines CUDNN_MAJOR, CUDNN_MINOR, and CUDNN_PATCHLEVEL. The version of cuDNN is the combination of these three numbers.

For example, if you see:

#define CUDNN_MAJOR 8
#define CUDNN_MINOR 0
#define CUDNN_PATCHLEVEL 1

This means that the cuDNN version is 8.0.1.

Conclusion

Knowing the versions of CUDA and cuDNN installed on your system is crucial for compatibility with deep learning libraries. We hope this guide has been helpful in showing you how to get the CUDA and cuDNN version on Windows with Anaconda installed. If you have any questions or run into any issues, feel free to leave a comment below.

Keywords

  • CUDA
  • cuDNN
  • Anaconda
  • Windows
  • Data Science
  • Deep Learning
  • NVIDIA
  • GPU
  • Parallel Computing
  • API
  • Deep Neural Networks
  • Primitives
  • Compatibility
  • Version
  • Command
  • Header File
  • Directory
  • Notepad
  • Major
  • Minor
  • Patchlevel

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