I'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).
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).
The A100 is 9.7 general purpose Tflops of float64, versus 624 Tflops of float16 / bfloat16 (perhaps also just tensor cores not general purpose)?
So quoting it the same way, this Florida machine would only be a (700 * (9.7 / 624)) = 10.9 Pflop supercomputer, not counting host CPUs.
Granted though, the hot new HPC approach is to approximate certain expensive high-precision calculations with ML inference instead, but that only works for certain algorithms.
IIUC, HPL can use double-precision tensor operations. It might also be able to use mixed-precision for some computations.
Are the performance numbers for this HPC system at University of Florida also from HPL ?
Lets put it this way: As of the A100 GPU generation, the tensor cores are able to do double precision calculations too. By using the tensor core the peak FP64 flops double to 19.5 Tflops. And yes, the CUDA BLAS library (that the HPL benchmark uses) uses the tensor cores on the A100.
> It might also be able to use mixed-precision for some computations.
There is currently a lot of interest in mixed precision algorithms, but I'm not sure that the algorithm used for HPL is amenable to that approach, nor whether it's allowed per the benchmark rules.
That #7 machine got 27.6 Pflops on HPL, so I would guess the Florida machine will get roughly half of that.
(Please keep in mind the tensor cores on the A100 can do FP64, so the theoretical peak flops per GPU is 19.5)
one day when disaggregated hardware becomes common in data centers the idea of a supercomputer will seem dated
The building and infrastructure will cost an additional $20m, covered by the University.
According to ^, that's about 11 GPT-3s trainings worth in the cloud.
I mean, we already have (my old 2013 desktop would - I guess - compete with a cray 1 from the 1980s). What do you expect will happen if people get more CPU?
This is 140 DGX A100 systems. The advertised price for each DGX A100 is $199,000, so 140 of them is ~$28 million. It's plausible the networking, storage, cooling, power distribution, etc (i.e. everything but the compute nodes) could cost $22 million.
In-state tuition at the University of Florida is inexpensive compared to most major US universities and is generally considered one of the better values among universities. ~$6,400 per year in-state. Florida State is also comparable in cost.
The first time I walked on the campus, it blew my mind. I'd never heard about Florida International University as an American, but it's easily the biggest and most beautiful I've seen.
Although I wasn't a graduate student so maybe way more of them have access than I realize.
To be eligible for an account on HiPerGator, you must be on an education or research project that has as one of its Principal or Co-Principal investigators a faculty or staff member at the University of Florida.
I'm also a UF alumni (undergrad & grad EE), and IIRC back in my day high performance computing was a grad class. I never took it, but it wouldn't surprise me if for the grad class there would be labs on the super computer where students can get limited access.
Recently, it also became possible to use C++17 stdpar and get GPU acceleration (https://docs.nvidia.com/hpc-sdk/compilers/c++-parallel-algor...).