G2

Prakhar A.

Senior Software Developer

Enterprise (> 1000 emp.)

8/7/2022

"Seamless setup experience & ease of use"

4.5/5

What do you like best about NVIDIA CUDA GL?

- Containerizing a graphical program with ML backend using CUDA has become super easy, thanks to NVIDIA's effort of glvnd. With Cuda GL containers, it is much easier to get up and running within a few minutes, avoiding all the headache of incompatible libraries versions and arbitrary crashes. Nvidia toolkit has support for a large range of ml/dl libraries Review collected by and hosted on G2.com.

What do you dislike about NVIDIA CUDA GL?

- From the last time I saw it, I remember the development and release of new containers were paused for some other tech debt work. Other than that, I think community around is good and slowly growing. Review collected by and hosted on G2.com.

What problems is NVIDIA CUDA GL solving and how is that benefiting you?

It has made it easy to quickly set up my ML/DL environment a churn out a POC for an idea that is floating. For example, if we were to create profiles of similar companies based on their 100s/1000s of employees, or create avatar animations or show product in action, any idea can be brought into action in a matter of a few days. This helps make the business decision easier and with more supporting data. Previous to these, often I used to create just command line programs since Cuda and OpenGL interop was sort of difficult to set up. Review collected by and hosted on G2.com.