I’d argue that a factor in CUDA’s success is their army of in-house researchers which use CUDA to do novel things. Sometimes those things get turned into products (OptiX) other times they are essentially DevRel to show off what the hardware can do and documentation for how to do it. Additionally I’m sure they use pre-release hardware and software and give feedback about how to improve it.
I don’t know what AMD has in mind for this acquisition but I could see there being a lot of value having an in house LLM team to create models for customers to build on, run in benchmarks, and improve their products.
As someone who has designed and taught those courses, my experience (admittedly only one persons) is that you pick what will work with the least hassle - because you'll have plenty of hassle elsewhere and probably no real time to deal with any of it without making more.
This is actually one of my favorite comments of all time, because it's how software wins. The software that students use is the software the industry uses about five years later.
> The software that students use is the software the industry uses about five years later.
which is why it's anti-competitive for a company to sponsor university courses (such as providing educational versions for free). It should be disallowed, unless the course is _specifically_ teaching the software, rather than a general course.
Sort of -- but basically no course is going to teach X and Y, if they're functionally equivalent ways to learn about Z, because almost no course is specifically about X or Y, it's about Z, and learning both X and Y isn't germane to learning Z, just learning one is enough.
As long as the companies behind X and Y both have a fair shot at sponsorship, this isn't really anti-competitive. It's literally a competition in which the companies compete for student and faculty attention.
Anti-competitive would be a company saying "you must teach X and not Y in your class about Z because you use Xco's mail services" or some other such abuse of one contractual relationship for an unrelated gain.
>Nvidia also spends a metric shit ton of money to make sure professors use and teach on their platform.
Do you have a source for this claim? Or do you simply mean that since they spend money making it better that professors end up using it on their own accord?
I hold an NVidia instructors cert from when I worked in academia. They even give you access to hardware while you’re running courses on it. It’s super easy and totally free.
I'm sure plenty of professors use CUDA in their courses because it's what they actually use. At the same time, in 2013 when I was in college I took a course on "parallel computing" as a CS elective. The professor told us on day 1 that NVidia was sponsoring the course and had donated a bunch of GPUs to the clusters we could remotely connect into for the sake of the class. Naturally we used CUDA exclusively.
I know for a fact that this happened at a lot of schools. I don't know if it's still happening since I'm not in that world anymore, but don't see why it would have stopped.
CUDA is extremely simple, the classes might as well be on rails. OpenCL is like impossible without graphics and/or CUDA/distributed computing/operating system experience.
I'm not sure if I really agree - the level of abstraction used for each is extremely similar. There's not really any "Graphics Pipeline Specifics" pollution in OpenCL or CUDA.
No nvidia makes great tooling. Like as a startup if I had to pick a development tool AmD fails repeatedly while nvida tooling is like matlab level of usefulness.
Those companies have money to make ‘nice’ things which open source software doesn’t have the time to do.
For 100m you could probably make some pretty sweet clones if amd is hiring anybody to man that position.
I’m not sure if I’m in the minority here but Matlab levels of tooling is an insult. Their guides were always two or three steps before being useful. Just enough to make you think whatever they were selling would solve your problems but never enough when really building a solution.
Nvidia makes software that induces demand for their products. Sometimes that software is a tool, or a platform, or an ML model, or foundational research on algorithms.
Thousands of OSS devs would be willing to devote serious time to it, but can’t/won’t run the gauntlet of starting such a ludicrously large project from scratch
It’s easy to contribute, difficult to be the one organising the contributions
The success of CUDA is basically a dual effect of AMD devices being inefficient and bad for years, plus AMD having no answer to CUDA for a solid 7+ years while the foundations of GPGPU were being laid down.
AMD is (according to their own statements) in the process of picking up a lot of software manpower. And wages in Finland are European tier, not US West Coast. Why lay them off?
Because nobody has been fired or fiscally punished for firing excessive number of people? :) People are notoriously bad at predicting potential positives, so firing people means nobody can prove that something wasn't created. In reverse it is possible to blame people for overhiring because that can be supported by hard numbers.
I guess their growth strategy was mostly about hiring every Finnish person, or living in Finland (and then in other countries) with a PhD in some quantitative topic and then market the "we have xx PhDs as a consultancy for all your projects". So you probably are right that not all these are needed anymore?
I don’t know what AMD has in mind for this acquisition but I could see there being a lot of value having an in house LLM team to create models for customers to build on, run in benchmarks, and improve their products.