[HN Gopher] LUMI, Europe's most powerful supercomputer
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LUMI, Europe's most powerful supercomputer
Author : Sami_Lehtinen
Score : 75 points
Date : 2022-06-13 18:17 UTC (4 hours ago)
(HTM) web link (www.lumi-supercomputer.eu)
(TXT) w3m dump (www.lumi-supercomputer.eu)
| occamrazor wrote:
| What is a goid benchmark today for supercomputers? TFLOPS don't
| seem to be a good measure, because it's relatively easy to deploy
| tens of thousands of servers. Is it the latency of the
| interconnection? Or the bandwidth? Or something entirely
| different?
| alar44 wrote:
| That's like asking what the benchmark for an engine is. It all
| depends on what you're trying to do with it. There's no single
| metric to compare a diesel semi truck engine to a 2 stroke golf
| cart. You need multiple measures and the importance of each is
| dependent on your workload.
| nabla9 wrote:
| They never have used flops to measure supercomputer
| performance.
|
| Its GFLOPS in HPLinpack (dense matrice multiplication)
| the_svd_doctor wrote:
| Hard/impossible to respond. Every workload is different. It can
| be mostly compute bound (Linpack), communication bound, a mix,
| very latency sensitive, etc. Imho, it just depends on the
| workflow and we should probably use multiple metrics instead of
| just Linpack peak TFLOPS.
| formerkrogemp wrote:
| The most powerful computer is the one that can launch nuclear
| weapons. "Shall we play a game?"
| saddlerustle wrote:
| A supercomputer comparable to mid-size hyperscaler DC. (and no,
| it doesn't have uniquely good interconnect, it's broadly on par
| with the HPC GPU instances available from AWS and Azure)
| slizard wrote:
| Hard no. Amazon EFA can barely come close to a dated HPC
| interconnect from the lower part of the top500 (when it comes
| to running code that does use the network, e.g. molecular
| dynamics or CFD), Azure does offer Cray XC or CS
| (https://azure.microsoft.com/en-us/solutions/high-
| performance...) which can/will be set up as proper HPC machines
| with fast interconnects, but I doubt these can be readily
| rented in the 100s of PFlops size.
|
| Check these talks from the recent ISC EXACOMM workshop if you
| want to see why HPC machines and HPC computing are an entirely
| different league compared to traditional data center computing:
| https://www.youtube.com/watch?v=9PPGvqvWW8s&list=WL&index=9&...
| https://www.youtube.com/watch?v=q4LkF33YMJ4&list=WL&index=7
| hash07e wrote:
| Nope.
|
| It has Slinghshot-11[1] as interconnection having a raw power
| of 200GB speed, plus caching and other heavy optimizations.
|
| It is not only the gpu instances but the way it interconnects.
| This model has even containers available for use.[2]
|
| It is more open.
|
| [1] - https://www.nextplatform.com/2022/01/31/crays-slingshot-
| inte...
|
| [2] - https://www.lumi-supercomputer.eu/may-we-introduce-lumi/
| ClumsyPilot wrote:
| Whats is the difference between a DC and why don't DCs appear
| in supercomputer rankings?
| why_only_15 wrote:
| Generally speaking a DC is designed for doing a bunch of
| different things that have less punishing interconnect needs,
| whereas supercomputers are designed for doing fewer things
| with higher interconnect needs. Datacenters often look like
| rows upon rows of racks with weaker interconnects between
| them, whereas supercomputers are much more tightly bound and
| built to work together.
| wongarsu wrote:
| I think the main difference is that on a supercomputer you
| generally run one task at a time, while in a DC you have
| computers that do different, unrelated things.
|
| The rest kind of follows from that, like how a supercomputer
| that consists of multiple computers needs a fast, low-latency
| interconnect between them to coordinate and exchange results,
| while computers in a DC care a lot less about each other.
|
| On the other hand the distinction is fluid. Google could call
| the indexers that power their search engine a supercomputer,
| but they prefer to talk about datacenters
| SiempreViernes wrote:
| Not so much "generally" as having the ability of doing it,
| but it is true that it a supercomputer is managed like it
| is one big thing that has _one_ job queue it tries to
| optimise.
| pbsd wrote:
| Entries #13, #36, #37, #38, #39 on the current list are Azure
| clusters. #52 is an EC2 cluster.
| dekhn wrote:
| Because if you tried to run the supercomputer benchmark on a
| DC, you'd get a low score, and you can't easily make up for
| that by adding more computers to a DC. To win the
| supercomputer benchmarks, you need low-latency, high
| bandwidth networks that allow all the worker nodes in the
| computer to communicate calculation results. Different real
| jobs that run on supercomputers have different communications
| needs but none of them really scale well enough to be
| economic to run on datacenter style machines.
|
| What's interesting is that over time, the datacenter folks
| ended up adding supercomputers to their datacenters, with
| very large and fast database/blob storage/data warehousing
| systems connected up to "ML supercomputers" (like
| supercomputers, but typically only do single precision
| floating point). The two work well together so long as you
| scale the bandwidth between them. At the end of the day, any
| interesting data center has obscenely complex networking
| technology. For example, TPUs are PCI-attached devices in
| Google data centers; they plug into server machines just like
| GPUs. The TPUs themselves have networking between TPUs, that
| allows them to move important data, like gradients, between
| TPUs, as needed to do gradient descent and other operations,
| but the hosts that the TPUs are plugged into have their own
| networks. The TPUs form a mesh- the latest TPUs form a 3D
| mesh, but physically implemented through a complex optical
| switch, while the hosts they are attached to multiple
| switches which themselves from complex graphs of networking
| elements. When running ML, part of your job might be using
| the host CPU to read in training data and transform it,
| keeping the network busy, keeping some remote disk servers
| busy, while pushing the transformed data into the TPUs, which
| then communicate internal data between themselves and other
| TPUs, over an entirely distinct network. Crazy stuff.
| jeffbee wrote:
| A cloud datacenter is about 50x larger than this, for
| starters.
| freemint wrote:
| Optimization for different workloads, scheduling is per
| workload not renting per machine and that they are submitted
| the TOP500 list and run benchmarks.
|
| Why do not DCs appear? Because they have not submitted
| benchmarks and power measurements.
| SiempreViernes wrote:
| > scheduling is per workload
|
| This is really the key: a supercomputer has the (software)
| facilities that makes it possible to launch one coordinate
| job that runs across all nodes. A data centre is just a
| bunch of computers placed next to each other, with no
| affordances to coordinate things across them.
|
| At on point in time the hardware differences were much
| greater between the two, but the fundamental distinction
| where a supercomputer really _is_ concerned with having the
| ability to be "one" computer remains.
| anttiharju wrote:
| Lumi is the Finnish word for snow in case anyone's wondering.
| kgwgk wrote:
| Good to know the inspiration was not this:
| https://www.collinsdictionary.com/dictionary/spanish-english...
| jjtheblunt wrote:
| is there a cognate in an indo-european neighboring language,
| perhaps by loanword?
| user_7832 wrote:
| https://en.m.wiktionary.org/wiki/lumi
|
| Doesn't look like in a quick glance
| jjtheblunt wrote:
| holy cow, I didn't realize that was searchable or i'd have.
| thank you.
| [deleted]
| geoalchimista wrote:
| Its peak flops performance seems on par with DOE's Summit and 15%
| of Frontier, according to the top 500 supercomputer list:
| https://www.top500.org/lists/top500/2022/06/.
| throw0101a wrote:
| Using AMD GPUs.
|
| How popular are they compared to Nvidia for HPC?
| cameronperot wrote:
| NVIDIA has a significantly larger market share for HPC [1]
| (select accelerator for category).
|
| [1] https://top500.org/statistics/list/
| brandmeyer wrote:
| That's not my take-away from the chart, especially if you
| normalize by performance share. "Other" is the clear winner,
| and AMD has slightly more performance share than NVIDIA.
| cameronperot wrote:
| Good point. I was looking at the "Family" aggregation which
| doesn't list AMD in the performance share chart, which was
| a bit misleading.
| fancyfredbot wrote:
| I really love supercomputing but I worry whether, with a machine
| like this one, we get the right balance between spending on
| software optimization Vs spending on hardware. It used to be the
| case that fast hardware made sense because it was cheaper than
| optimising hundreds of applications but these days with
| unforgiving GPU architectures the penalty for poor optimisation
| is so high...
| jbjbjbjb wrote:
| I wonder if anyone on HN could tell us how well optimised the
| code is on these? I imagine the simulations are complicated
| enough without someone going in and adding some performance
| optimisation.
| nestorD wrote:
| I am not familiar with that particular one but I have used
| other supercomputers and those people are not waiting for
| better hardware, they are trying to squeeze the best
| performance they _can_ out of what they have.
|
| The end result mostly depends on the balance between
| scientists and engineers in the development team, it will
| oscillates between "this is python because the scientists
| working on the code know only that but we are using MPI to at
| least use several cores" and "we have a direct line with the
| hardware vendors in order to help us write the best software
| possible for this thing".
| SiempreViernes wrote:
| It varies quite a lot depending on the exact project and how
| much is expected to be purely waiting on one big compute job
| to finish.
|
| For something like climate simulations where a project is
| running big long jobs repeatedly I imagine they spend quite a
| bit of time on making it fast.
|
| For something like detector development where you run the
| hardware simulation production once and then spend three
| years trying to find the best way to reconstruct events less
| effort is put into making it fast. Saving two months from a
| six months job you run once isn't worth it if you have to
| spend more than a few weeks optimising it, and as these type
| of jobs need to write a lot to disk there's a limit to how
| much you'll get from optimising the hot loop.
| jp0d wrote:
| They've also partnered with the RIKEN Centre for Computation
| Science (Developer of the fastest Super computer on earth). Quite
| impressive and interesting at the same time as they use very
| different architectures.
|
| https://www.r-ccs.riken.jp/en/outreach/topics/20220518-1/
| https://top500.org/lists/hpcg/2022/06/
| robinhoodexe wrote:
| For a more technical overview:
|
| https://www.lumi-supercomputer.eu/may-we-introduce-lumi/
| oittaa wrote:
| And full specs at https://www.lumi-supercomputer.eu/lumis-full-
| system-architec...
| sampo wrote:
| The computer as a whole has an entry (3.) in the top500 list. And
| then the cpu-only part of the computer has another entry (84.).
| The whole computer does about 150 PFlop/s, and the cpu-only part
| about 6 PFlop/s. So 96% of the computing power comes from the GPU
| cards.
|
| https://www.top500.org/lists/top500/list/2022/06/
| jpgvm wrote:
| Interesting to see Ceph mixed into the storage options.
|
| Lustre still king of the hill though.
| asciimike wrote:
| My assumption is that Ceph is just there for easy/cheap block
| storage, while Lustre is doing the majority of the heavy
| lifting for the "supercomputing." Ceph file storage performance
| is abysmal, so it doesn't make sense to try and offer it for
| everything.
| Barrin92 wrote:
| > _" In addition, the waste heat produced by LUMI will be
| utilised in the district heating network of Kajaani, which means
| that its overall carbon footprint is negative. The waste heat
| produced by LUMI will provide 20 percent of Kajaani's annual
| demand for district heat"_
|
| Pretty cool honestly. Reminds me of the datacenter that Microsoft
| built in a harbor to cool with the surrounding seawater.
| jupp0r wrote:
| Their definition of negative carbon footprint is broken. Unless
| there is something in the computer that permanently binds
| carbon from the atmosphere.
| weberer wrote:
| That's also in Finland. The district heating infrastructure is
| already in place, so if you're producing heat, its not hard to
| push steam in a nearby pipe and make an easy PR statement about
| sustainability.
| danielvaughn wrote:
| though couldn't the district then save money by either
| reducing their own infra, or eliminating it entirely?
| nabla9 wrote:
| There are now several datacenters in Finland that link into
| local district heating.
|
| Microsoft recently announced that they build similar data
| center in Finland too
| https://www.fortum.com/media/2022/03/fortum-and-microsoft-an...
| asciimike wrote:
| [Cloud and Heat](https://www.cloudandheat.com/hardware/) offers
| liquid cooling systems that purport to offer waste hot water on
| the town/small city scale.
| alkonaut wrote:
| I hope no datacenters these days are built on the idea of just
| running cooling with straight electricity (e.g. no cooling
| water) and shifting the heat straight out to the air (no waste
| heat recovery). Even in the late 90's that sounds like a poor
| design.
| why_only_15 wrote:
| that's how all of Google's datacenters are built in my
| understanding. Water cooling is very expensive compared to
| air cooling, and only used for their supercomputer-esque
| applications like TPU pods. I don't know about waste heat
| recovery but I don't think they use that either.
| RobertoG wrote:
| There is also immersion cooling. The liquid is not water
| and it seems is pretty efficient:
|
| https://submer.com/immersion-cooling/
| asciimike wrote:
| Exceedingly efficient (PUEs of 1.0X) vs cold plate liquid
| cooled or air cooled. The tradeoff is that mineral oil is
| annoying (messy especially if leaked but even with
| maintenance) and fluorinated fluids are bad for the
| environment (high GWP, tend to evaporate) and crazy
| expensive. In either case, the fluids tend to have weird
| effects on plastics or other components, so you have to
| spend a good amount of time testing your components and
| ensuring that someone doesn't switch components on your
| motherboards without you knowing, lest it not play well.
| tuukkah wrote:
| "A case in point is our technologically advanced, first-of-
| its-kind cooling system that uses seawater from the Bay of
| Finland, which reduces energy use."
| https://www.google.com/about/datacenters/locations/hamina/
| Out_of_Characte wrote:
| Depending on what you define as water cooling, Google most
| definitely uses watercooling in all their datacenters.
|
| https://www.datacenterknowledge.com/archives/2012/10/17/how
| -...
|
| https://arstechnica.com/tech-policy/2012/03/google-
| flushes-h...
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