raj_m

Looks really interesting. I presume this is accepted to SIG18 ???

One may argue that a Phd student working in genomics must know the Monotone Queue variant because it MAY come up as a research implementation in his/her work. But this doesn't hold true for general software engineering folks.

I am a Phd student in Computer Graphics and so it is a reasonable expectation that I should know more about linear algebra than my peers. But if you extrapolate it to ask extremely hard research level problem it kills the purpose.

That's an interesting observation. So what you are saying is that if I make sufficient headway into the problem without providing the most efficient answer, it should be fine?

There are rumors that unless you are spot on perfect in Big 4 interviews, they wont advance you.

Emailed you. Phd student in Computer Graphics with FEM background. Never thought I would actually find something so relevant to my skillset.

I am a Phd student in physics based simulation for Computer Graphics. I was a summer intern at WDAS and most of my colleagues were two of the following : 1) MS in CS with specialization in COmputer Graphics from places like UPenn 2) Phd in CS with specialization in Computer Graphics/Phd in Applied Mathematics from UCLA/Harvard.

I really don't think this will make a dent in CUDA's platform. CUDA has a well established ecosystem in deep learning and compatible cards like Quadro coupled with very matured platform makes it miles ahead of platform.

That said, I would love to be proven wrong. Healthy competition such as this fosters much better results. Also CUDA is not without issues in certain matters.