All these big companies giving free stuff to university students to hook them into their proprietary technology. I remember some of my friends graduating and realizing marlin wasn’t free.
Nvidia will build 700-petaflop supercomputer for University of Florida
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Re: Nvidia will build 700-petaflop supercomputer for University of Florida
#62Sigh, I wish people wouldn’t say “peta flop ” for these. https://www.nvidia.com/en-us/data-center/a100/ is the most official reference. If you scroll to the bottom, you’ll see that an A100 part can do ~20 Teraflops (either FP32 or FP64 in little-matrix aka tensor mode). When they say “each A100 can do 5 petaflops”, they mean each DGX which has 8 such cards and thus they mean 600-ish something-ops per card. The genero…
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Re: Nvidia will build 700-petaflop supercomputer for University of Florida
#63Maybe they can use it to simulate load and stress on pedestrian bridges for some of the other Florida Universities:
https://en.wikipedia.org/wiki/Florida_International_Universi...
Re: Nvidia will build 700-petaflop supercomputer for University of Florida
#64It seems like supercomputers are still generally many times more powerful than what AI researchers at top universities or orgs are using. Has any well known AI research been done on supercomputers? It seems like the case that literally just throwing money at the problem is a solid idea nowadays.
GPT-3 was another buckets worth of evidence in favor of the scaling hypothesis. Performance kept improving (and cost to train kept increasing) as more parameters were added. Even with 175 billion parameters, the performance had not yet plateaued. One take-away is that throwing a lot of compute at the problem helps tremendously :). You can read more about GPT-3 here: https://lambdalabs.com/blog/gpt-3/
Are you alluding to "The Bitter Lesson" [1] by Rich Sutton [2]?
Re: Nvidia will build 700-petaflop supercomputer for University of Florida
#65I'm a bit baffled. How high are the tuitions at the university of florida? This supercomputer is more powerful than many at the national labs and must cost a fortune (multiple 100 millions of dollars).
Research at most US major universities is funded from federal grants, not from tuition. A place like the University of Florida, MIT, Michigan State, whatever, is conducting research with government money in a manner very similar to a national lab.
Indeed, and to paraphrase my PhD adviser, we currently have more research dollars than good students to spend them on.
Re: Nvidia will build 700-petaflop supercomputer for University of Florida
#66They should build proper Linux driver first without enormous signed blobs. One of the worst companies for FOSS community.
Re: Nvidia will build 700-petaflop supercomputer for University of Florida
#67I'm a bit baffled. How high are the tuitions at the university of florida? This supercomputer is more powerful than many at the national labs and must cost a fortune (multiple 100 millions of dollars).
In addition to what everyone else has said, UF has over 50,000 students, making it one of the five largest universities in the USA, iirc.
Precisely explains why NVIDIA did that - to hook up all these 50k students to CUDA. Much more profitable in the long run.
Re: Nvidia will build 700-petaflop supercomputer for University of Florida
#68I'm a bit baffled. How high are the tuitions at the university of florida? This supercomputer is more powerful than many at the national labs and must cost a fortune (multiple 100 millions of dollars).
It's $50 million. That's all. See https://blogs.nvidia.com/blog/2020/07/21/university-of-flori... for the numbers. It's probable the hardware is being offered at a deep discount. The building and infrastructure will cost an additional $20m, covered by the University.
It's "anchored" by $50 million (of which half is support). But what does "anchored" mean here? The article also lists an additional $20 million from UF. I wouldn't be surprised if there was even more.
Re: Nvidia will build 700-petaflop supercomputer for University of Florida
#69Earlier quoted context omitted.
Risk mitigation, maintenance, resell value (?), support, reliability. The custom AI accelerators you mentioned, how long have those been in business for? How many units have they moved? How many generations of hardware have they produced? Will they still be around to replace or upgrade units in 5-10 years? How flexible are they in their workload? That's a lot of factors to keep in mind when you're spending millions o…
TPUs are perfectly positioned to capture this market. There are an endless number of reasons why, but to keep it short: Wanna see a magic trick? https://twitter.com/theshawwn/status/1286426454171975680 GPT-2 117M training at 1 million tokens/sec. Now, I don't have experience with DGX clusters, so I'm not going to make a firm statement. What I will say is that I, as an outsider, managed to achieve a performance level…
Last time I worked on TPUs, a lot of very pervasive LA operations (e.g. Cholesky decomposition) were unoptimized and slow compared to the NN-style operations. I’m sure that can be fixed, but for the time being, it seems inappropriate for anything beyond the obvious NN operations.
Re: Nvidia will build 700-petaflop supercomputer for University of Florida
#70Earlier quoted context omitted.
In addition to what everyone else has said, UF has over 50,000 students, making it one of the five largest universities in the USA, iirc.
Precisely explains why NVIDIA did that - to hook up all these 50k students to CUDA. Much more profitable in the long run.
All 50k Students aren't engineers...