NVIDIA CUDA GL

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

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.

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.

What do you like best about NVIDIA CUDA GL?

I used CUDA in college to study stuff like parallel processing with GPUs so it's good if you want to know the basics and then start off with more advanced steps

What do you dislike about NVIDIA CUDA GL?

The only disadvantage seems to be its age, it's good for someone to clear the basics but it's kind of outdated and is load intensive . i had to run its program on google collab rather than local pc due to too much time taking to run

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

getting a grasp of parallel processing, load sharing programs and threading in software that will further help me in other fields of study and getting to know of GPU architecture.

What do you like best about NVIDIA CUDA GL?

-The best part about it is the cross platform support which ensures that it behaves in same manner throughout different operating systems.

-It is quite easy to integrate it with already built model and is quite helpful in speeding up compute heavy models/applications .

What do you dislike about NVIDIA CUDA GL?

This is not necessary a con but building basic implementations might be easier but for more complex applications you require good level of understanding , but then again that part is usually taken care by senior devs.

So it might take some time to get a good command over it upto and intermediate to expert level.

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

I deal with a large amount of tabular data, pdf,doc and other documents with text larger than 100-200 GB. In any of the text processing done in batches I see atleast 5-8 times speedup with a medium level GPU ( not TITAN and RTX 3090 levels) than if I were to do the same without it.

This allows me to try out more things in less amont of time and build an overall better performing code.

What do you like best about NVIDIA CUDA GL?

I worked on NVIDIA CUDA long time back in 2010. I was building a coding assessment platform similar to Leetcode but for NVIDIA CUDA, which tracks the number of cores and memory usage along with correctness of the solution. I found it difficult to understand, as the concepts are different. However I was able to get the project working and it was used by the university of California to access the skill of the students in parallel programming.

What I liked best was the ability to split and parallelly execute programs which allows massive throughput and reduced time to run compute-intensive programs by orders of magnitude.

What do you dislike about NVIDIA CUDA GL?

As it was new, I had difficulty understanding the concepts of designing programs to run on multiple cores. I also did not like the tooling around it. There is no debugging or good IDE support. This was initially when I worked on it way back in 2010. Not sure of the current state.

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

NVIDIA CUDA allows running compute-intensive analyses and simulations to run without the need for massive infrastructure. This can be used to run analyses on big data or analyze gnome data or run simulations on affordable machines that is accessible by masses

What do you like best about NVIDIA CUDA GL?

I have been using NVDIA from 6 years now and it has been very good in performance. Durability at its best.Running smoother for 6 years is something which should be appreciated.

What do you dislike about NVIDIA CUDA GL?

There is nothing I dislike regarding NVIDIA, but given technology advancements, products should be available for reasonable prices. Apart from that I think everything is good.

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

I play and stream at the same time, the parallel computing helps my videos running smoothly in youtube. It has been excellent in running machine learning modules.