M,
Isn't it more accurate to say that HPCG measures the whole system more
realistically, and memory bandwidth happens to be the "rate limiting
step" in just about all architectures? Even with LINPACK, which should
be CPU-bound, the Top500 list shows that HPL results are affected by the
network. For example, there's this article which is a bit old, but I
think still applies (doing the same analysis on the current top500 list
is on my to-do list, actually):
https://www.nextplatform.com/2015/07/20/ethernet-will-have-to-work-harder-to-win-hpc/
On 3/18/22 8:34 PM, Massimiliano Fatica wrote:
HPCG measures memory bandwidth, the FLOPS capability of the chip is
completely irrelevant.
Pretty much all the vendor implementations reach very similar
efficiency if you compare them to the available memory bandwidth.
There is some effect of the network at scale, but you need to have a
really large system to see it in play.
M
On Fri, Mar 18, 2022 at 5:20 PM Brian Dobbins <bdobb...@gmail.com> wrote:
Hi Jorg,
We (NCAR - weather/climate applications) tend to find that HPCG
more closely tracks the performance we see from hardware than
Linpack, so it definitely is of interest and watched, but our
procurements tend to use actual code that vendors run as part of
the process, so we don't 'just' use published HPCG numbers.
Still, I'd say it's still very much a useful number, though.
As one example, while I haven't seen HPCG numbers for the MI250x
accelerators, Prof. Matuoka of RIKEN tweeted back in November that
he anticipated that to score around 0.4% of peak on HPCG, vs 2% on
the NVIDIA A100 (while the A64FX they use hits an impressive 3%):
https://twitter.com/ProfMatsuoka/status/1458159517590384640
Why is that relevant? Well, /on paper/, the MI250X has ~96 TF
FP64 w/ Matrix operations, vs 19.5 TF on the A100. So, 5x in
theory, but Prof Matsuoka anticipated a ~5x differential in HPCG,
/erasing/ that differential. Now, surely /someone/ has HPCG
numbers on the MI250X, but I've not yet seen any. Would love to
know what they are. But absent that information I tend to bet
Matsuoka isn't far off the mark.
Ultimately, it may help knowing more about what kind of
applications you run - for memory bound CFD-like codes, HPCG tends
to be pretty representative.
Maybe it's time to update the saying that 'numbers never lie' to
something more accurate - 'numbers never lie, but they also rarely
tell the whole story'.
Cheers,
- Brian
On Fri, Mar 18, 2022 at 5:08 PM Jörg Saßmannshausen
<sassy-w...@sassy.formativ.net> wrote:
Dear all,
further the emails back in 2020 around the HPCG benchmark
test, as we are in
the process of getting a new cluster I was wondering if
somebody else in the
meantime has used that test to benchmark the particular
performance of the
cluster.
From what I can see, the latest HPCG version is 3.1 from
August 2019. I also
have noticed that their website has a link to download a
version which
includes the latest A100 GPUs from nVidia.
https://www.hpcg-benchmark.org/software/view.html?id=280
What I was wondering is: has anybody else apart from Prentice
tried that test
and is it somehow useful, or does it just give you another set
of numbers?
Our new cluster will not be at the same league as the
supercomputers, but we
would like to have at least some kind of handle so we can
compare the various
offers from vendors. My hunch is the benchmark will somehow
(strongly?) depend
on how it is tuned. As my former colleague used to say: I am
looking for some
war stories (not very apt to say these days!).
Either way, I hope you are all well given the strange new
world we are living
in right now.
All the best from a spring like dark London
Jörg
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