No need to fear from Cuda and Nvidia installation
July 20, 2022

No need to fear from Cuda and Nvidia installation

Anonymous | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User

Overall Satisfaction with Amazon Deep Learning AMIs

We use AWS EC2 for training machine learning models. For spinning up these instances, we use prebuilt AMIs specific for Deep Learning. These AMIs help a lot in setting up the environment very easily without any worries of installing CUDA, Nvidia Drivers, and then specific libraries like Pytorch, and TensorFlow. Support for various Conda environments is also available. The amazing part of this is that it provides support for different types of machines like Ubuntu, Linux, Amazon OS, etc.
  • Setting up environment
  • Support for different types of machines
  • Perfect for Machine Learning / Deep Learning use cases
  • Nvidia / Cuda / Conda support easily
  • Simpler documentation of different types of AMIs
  • Clearly listing out different types of machines as I got confused and spinned up an AMI in Amazon Linux machine instead of Ubuntu
  • Support for latest version of libraries, to avoid manually updating them after launch
  • Nvidia / Cuda drivers
  • Conda environment
  • Support for Ubuntu (multiple versions)
  • Saves a lot of Infra Costs
  • Saves a lot of time in handling environment issues
  • Easy to start a new instance

Do you think Amazon Deep Learning AMIs delivers good value for the price?

Yes

Are you happy with Amazon Deep Learning AMIs's feature set?

Yes

Did Amazon Deep Learning AMIs live up to sales and marketing promises?

Yes

Did implementation of Amazon Deep Learning AMIs go as expected?

Yes

Would you buy Amazon Deep Learning AMIs again?

Yes

Suitable:
1. Best for quickly setting up an instance with pre-installed libraries.
2. Ideal for people in Deep Learning space who struggle with Cuda / Nvidia driver installations.

Not suitable:
1. People who want to install custom libraries or different version of those.
2. In these cases, updating the version of libraries many times leads to version mismatch which can cause many errors.