AMD-powered Frontier supercomputer breaks the exascale barrier
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AMD-powered Frontier supercomputer breaks the exascale barrier
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Re: AMD-powered Frontier supercomputer breaks the exascale barrier
#2Since they are using AMD's accelerators as well [1], I do wonder whether any usage of these will trickle down and give us improvements in ROCm.
Surely the people at these labs will want to run ordinary DL frameworks at some point - or do they have the money and time to always build entirely custom stacks?
[1] AMD Instinct MI250x in this case.
Re: AMD-powered Frontier supercomputer breaks the exascale barrier
#3Since they are using AMD's accelerators as well [1], I do wonder whether any usage of these will trickle down and give us improvements in ROCm. Surely the people at these labs will want to run ordinary DL frameworks at some point - or do they have the money and time to always build entirely custom stacks? [1] AMD Instinct MI250x in this case.
> Surely the people at these labs will want to run ordinary DL frameworks at some point
I don't know about that. A lot of these labs are doing physics simulations and are probably happy to stick with their dense-matrix multiply / BLAS routines.
Deep learning is a newer thing. These national labs can run them of course, but these national labs have existed for many decades and have plenty of work to do without deep learning.
> or do they have the money and time to always build entirely custom stacks?
Given all the talk about OpenMP compatibility and Fortran... my guess is that they're largely running legacy code in Fortran.
Perhaps some new researchers will come in and try to get some deep-learning cycles in the lab and try something new.
Re: AMD-powered Frontier supercomputer breaks the exascale barrier
#4Since they are using AMD's accelerators as well [1], I do wonder whether any usage of these will trickle down and give us improvements in ROCm. Surely the people at these labs will want to run ordinary DL frameworks at some point - or do they have the money and time to always build entirely custom stacks? [1] AMD Instinct MI250x in this case.
> Surely the people at these labs will want to run ordinary DL frameworks at some point I don't know about that. A lot of these labs are doing physics simulations and are probably happy to stick with their dense-matrix multiply / BLAS routines. Deep learning is a newer thing. These national labs can run them of course, but these national labs have existed for many decades and have plenty of work to do without deep le…
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Re: AMD-powered Frontier supercomputer breaks the exascale barrier
#5Since they are using AMD's accelerators as well [1], I do wonder whether any usage of these will trickle down and give us improvements in ROCm. Surely the people at these labs will want to run ordinary DL frameworks at some point - or do they have the money and time to always build entirely custom stacks? [1] AMD Instinct MI250x in this case.
I’m not using Frontier, but I am using Setonix which is a large AMD cluster being rolled out in Australia. All of AMD’s teaching materials are about ROCm so this is very much how they’re expecting it to be used.
The real pain for us is that there’s no decent consumer grade chips with ROCm compatibility for us to do development on. AMD have made it very clear they only care about the data centre hardware when it comes to ROCm, but I have no idea what kind of developer workflow they’re expecting there.
Re: AMD-powered Frontier supercomputer breaks the exascale barrier
#6Thank you to the authors for not calling it the fastest computer in the world :-) and instead, as they should, the most powerful. Clock speed is not the only factor of course, as instruction per cycle and cache sizes have an impact, but for a pure measure of speed, the fastest still is:
- For practical use, and non overclocked, the EC12 at 5.5 Ghz: https://www.redbooks.ibm.com/redbooks/pdfs/sg248049.pdf
or
- An AMD FX-8370 floating in Liquid Nitrogen at 8.7 Ghz: https://hwbot.org/benchmark/cpu_frequency/rankings#start=0#i...
Re: AMD-powered Frontier supercomputer breaks the exascale barrier
#7Since they are using AMD's accelerators as well [1], I do wonder whether any usage of these will trickle down and give us improvements in ROCm. Surely the people at these labs will want to run ordinary DL frameworks at some point - or do they have the money and time to always build entirely custom stacks? [1] AMD Instinct MI250x in this case.
I’m not using Frontier, but I am using Setonix which is a large AMD cluster being rolled out in Australia. All of AMD’s teaching materials are about ROCm so this is very much how they’re expecting it to be used. The real pain for us is that there’s no decent consumer grade chips with ROCm compatibility for us to do development on. AMD have made it very clear they only care about the data centre hardware when it comes…
Interesting. So what is your workflow right now?
Re: AMD-powered Frontier supercomputer breaks the exascale barrier
#8The more powerful processors become, the less I feel there's a need to build supercomputers.
Thinking about it, the most powerful supercomputer in the world is pretty much a million consumer processors, working in parallel. That's going to stay pretty constant, since cost scales roughly linearly.
If X is the processing power of $1k of consumer hardware, the bigger X gets, the less there is a difference in the class of problems that you can solve with X or X * 1e6 processing power.
Re: AMD-powered Frontier supercomputer breaks the exascale barrier
#9Since they are using AMD's accelerators as well [1], I do wonder whether any usage of these will trickle down and give us improvements in ROCm. Surely the people at these labs will want to run ordinary DL frameworks at some point - or do they have the money and time to always build entirely custom stacks? [1] AMD Instinct MI250x in this case.
> Surely the people at these labs will want to run ordinary DL frameworks at some point I don't know about that. A lot of these labs are doing physics simulations and are probably happy to stick with their dense-matrix multiply / BLAS routines. Deep learning is a newer thing. These national labs can run them of course, but these national labs have existed for many decades and have plenty of work to do without deep le…
> Given all the talk about OpenMP compatibility and Fortran... my guess is that they're largely running legacy code in Fortran.
The must used linear algebra library is written in Fortran. There's nothing "legacy" about it, it's just that nobody was able to replicate its speed in C.
Re: AMD-powered Frontier supercomputer breaks the exascale barrier
#10The more powerful processors become, the less I feel there's a need to build supercomputers. Thinking about it, the most powerful supercomputer in the world is pretty much a million consumer processors, working in parallel. That's going to stay pretty constant, since cost scales roughly linearly. If X is the processing power of $1k of consumer hardware, the bigger X gets, the less there is a difference in the class o…
Sure, but consumer hardware does not have infiniband or other high-bandwidth interconnects. That means you can have at most ~1-2TB of ram accessible at any point. Some problems need coordination, and when you're back at OpenMP etc., a supercomputer suddenly makes sense.