[HN Gopher] LUMI, Europe's most powerful supercomputer ___________________________________________________________________ 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... ___________________________________________________________________ (page generated 2022-06-13 23:00 UTC)