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Intel Failed Science
- NextHendrix 4y agoWhat are the reasons for Intel's delay?
- HelloNurse 4y agoSales getting far ahead of engineering, and lack of liability for the delay.
- SilverBirch 4y agoIntel is meant to do a process shrink every 2 years, which is meant to increase compute density and lower power. The last time they successfully did that was 2014 with 14nm, and since then they spent about 7 years getting to 10nm, and even now I'm not sure they're completely there. So basically all the assumptions about anything built with Intel CPUs getting faster were blown out of the water.
- prvc 4y agoThat series of tweets is difficult to decipher. What is being reported here?
- helf 4y agoIt’s a postdoc whining. Literally nothing more.
- DecoPerson 4y agoSomething under some heavy NDAs, apparently.
- jsty 4y agoTo hazard a guess - the delayed delivery of Aurora to Argonne National Labs, originally planned (in different form) for 2018 and now expected "late 2022" https://insidehpc.com/2020/08/exascale-exasperation-why-doe-gave-intel-a-2nd-chance-can-nvidia-gpus-ride-to-auroras-rescue/ https://insidehpc.com/2020/08/exascale-exasperation-why-doe-...
- defrost 4y agoIn a nutshell (bound by a single tweet of 13): > The U.S. should have had two exascale supercomputers on the Top 500 in 2021. And Aurora, which has been plagued by Intel’s delays since 2017, should have been first—well before “Frontier” at Oak Ridge National Lab appeared. But Intel dropped the ball over. And over. And again. It does acknowledge that recent deliveries will allow the project to place on the current supercomputer list by virtue of finally being able to run LINPACK tests ... but that's still a few years late and well short of what was promised to be delivered, tested, bedded, and deep into working by now.
- unnah 4y agoIt's about Intel's Aurora supercomputer, which was delayed 4 years due to Intel's production problems and delays in their GPU development: https://en.wikipedia.org/wiki/Aurora_(supercomputer) https://en.wikipedia.org/wiki/Aurora_(supercomputer) According to the tweets, researchers who reserved time for their projects on the supercomputer had to sign NDAs so they cannot complain about the delays... not exactly a good look.
- ac29 4y agoIt should be noted that during that 4 year delay the computer was also upgraded by an order of magnitude (180 petaflops -> 2 exaflops). Intel deserves criticism for their various delays for sure, but the proposed 2018 machine and the shipping 2022/23 machine really are only the same in name.
- ciphol 4y agoA handful of post docs haven't been able to complete their research projects because Intel's CPU development is behind schedule.
- ur-whale 4y agoAre people still doing science on Intel silicon? Why? What is it exactly that an Intel-based "supercomputer" can do that a hangar full of NVidia GPU's can't? Looking to understand here, I thought GPU's had changed the HPC landscape for ever. [EDIT]: Are they workload where the I/O infrastructure required to feed the compute units and that on only Intel can deliver?
- zokier 4y ago> What is it exactly that an Intel-based "supercomputer" can do that a hangar full of NVidia GPU's can't? Run 30 year old fortran code?
- atemerev 4y agoBecause not every scientific library in the world is ported to GPGPU (or even can technically be). CPU-heavy computing is a rule, not an exception. E.g. in computational fluid dynamics, there are not too many GPU-ready codes available, and most of those are either beta-quality or already abandoned.
- jhbadger 4y agoAgreed. In computational biology it is similar. About 5-10 years ago there was huge excitement over GPUs and there were things like GPU-accelerated BLAST (program for comparing DNA/protein sequences against each other) and the like, but it really didn't revolutionize the field in general. HPCs like Biowulf (the HPC cluster used by the US National Institutes of Health, a pun on "biology" and "Beowulf") is overwhelmingly CPU-based with a few GPUS that you can request.
- Maursault 4y ago> Biowulf (the HPC cluster used by the US National Institutes of Health, a pun on "biology" and "Beowulf") Sorry to be satanic[0], but "Biowulf"[1] is not a pun. Thieves often make this mistake because they take things literally. [0] https://en.wikipedia.org/wiki/Pun https://en.wikipedia.org/wiki/Pun [1] https://en.wikipedia.org/wiki/Portmanteau https://en.wikipedia.org/wiki/Portmanteau
- LeanderK 4y agoThe aurora supercomputer is delayed 4 years...given the progress in compute I wonder whether it will be obsolete on arrival? In 4 years a lot of new competitors should have emerged, right? If my GPU would come 4 years late I would not be getting what I paid for (state of the art equipment). Or does intel continuously adapt it to new architectures?
- JonChesterfield 4y agoI think the design has changed a few times but that probably doesn't help the delivery timeline
- SilverBirch 4y agoThe wikipedia page for this is great >In 2013 DOE presented their exascale vision of one exaFLOP at 20 MW by 2020.[6] Aurora was first announced in 2015 and to be finished in 2018. It was expected to have a speed of 180 petaFLOPS[7] which would be around the speed of Summit. Aurora was meant to be the most powerful supercomputer at the time of its launch and to be built by Cray with Intel processors. Later, in 2017, Intel announced that Aurora would be delayed to 2021 but scaled up to 1 exaFLOP. In March 2019, DOE said that it would build the first supercomputer with a performance of one exaFLOP in the United States in 2021.[8] In October 2020, DOE said that Aurora would be delayed again for a further 6 months and would no longer be the first exascale computer in the US.[9] In late October 2021 Intel announced Aurora would now exceed 2 exaFLOPS in peak double-precision compute.[10] So you announced a machine in 2015 to be delivered in 2018, so a project to take 3 years. In 2017 you then announced you're not going to deliver it at all. You announce a delay to deliver something different in 3 years. That's not a delay, that's just scrapping the project and starting a new one. Just because you call it the same thing doesn't mean anyone believes you. I do wonder how much cash Intel rinsed out of the DOE for delivering nothing. You would've thought that since the DOE announced a target of 1 Exaflop in 2020, and Intel delivers 0 exaflops, that Intel would make a big loss on this, I bet they didn't.
- q-big 4y ago> exaFLOP Nitpick: FLOPS (floating point operations per second) is singular. "FLOP" is "floating point operations per", which does not make sense. > https://en.wikipedia.org/wiki/FLOPS https://en.wikipedia.org/wiki/FLOPS
- mort96 4y agoTo make it even more confusing, FLOP is sometimes used to mean "floating point operation", so it can be correct to say that a computation takes 1000 FLOPs. A machine with 2000 FLOPS would do 1000 FLOPs in half a second.
- denton-scratch 4y ago> To make it even more confusing, FLOP is sometimes used to mean "floating point operation" Yes, sometimes people use words wrongly. > so it can be correct to say that a computation takes 1000 FLOPs. No; that is incorrect, and it's unsurprising that ignorant misuse of technical terminology results in confusion.
- throwawaylinux 4y agoThis is very dramatic. Big supercomputer projects are not actually a walk in the park, they are designed to intercept technology several years in the future that does not exist yet. It requires science and engineering to make these things. Sometimes they're late, sometimes they go over budget, sometimes they're cancelled, sometimes acceptance criteria have to be adjusted. This isn't unusual or limited to supercomputers. Look at the LHC, look at the James Webb telescope. They had delays and overruns and problems too. This isn't "failing science", it's a project having project problems. The big supercomputers aren't all that lucrative, Intel wouldn't be swimming in profit from this thing even if it did go to plan, as it is they'll quite possibly be losing money to penalties and cost overruns.
- xani_ 4y ago> This isn't unusual or limited to supercomputers. Look at the LHC, look at the James Webb telescope. They had delays and overruns and problems too. This isn't "failing science", it's a project having project problems. That is entirely uncomparable. They're not building a first supercomputer in the world, nor inventing much new tech aside from the usual progression of faster and smaller
- throwawaylinux 4y agoThey weren't building the first space telescope or particle accelerator in the world either. I'm not quite sure what the thinking behind pulling that one out like a trump card was. And believing silicon technology process shrinks and new processor designs that take advantage of it is nothing much new betrays an unfortunate misunderstanding of these technologies. Smaller and faster to you looks like your phone or PC get a little cheaper and faster every few years. The technology that enables that is staggering. These push the limits of materials science and chemistry and a bunch of fields of physics relating to electronics and photonics. Designing the chip requires again pushing boundaries in hard problems in computer science and mathematics to model and compile and optimize and verify the logic. The two most complicated machines ever made are the microprocessors on the silicon chips, and the factories which make them -- a single one of those costs double what it took to build the LHC at CERN, twice the GDP of Somalia. And that does not include all the R&D cost to reach the point they can be built. The supercomputer required predicting these things years into the future and intercepting that technology. Intel ran into unforeseen delays in these things which derailed the supercomputer. Not all that surprising that such efforts don't always go smoothly. There are 3 companies left which can manufacture high performance chips, and many that have fallen. There are only a handful that can design high performance CPUs and GPUs.
- kleiba 4y agoIs Intel's delay really a showstopper for US research? According to top500.org, 32 of the top-100 supercomputers in the world are located in the US. That's way more than any other nation.
- bayindirh 4y agoDisclaimer: I'm an HPC admin. Some problems are too big to run even on these supercomputers. These machines are bound by extremely fast (speed/latency-wise) networks, and the work can't be scaled to multiple sites. So yes, when you have a grand challenge, and no computer, you can't solve that challenge. You can continue playing with smaller versions of it though, but it won't give you the accuracy or detail you need/want. So, the count is important, yes, but the capabilities of the clusters you have is also important.
- kleiba 4y agoInteresting perspective, thank you. But at least US researchers cannot claim to be in an disadvantaged position compared to other countries?
- bayindirh 4y agoYou're welcome. Glad it helped. > But at least US researchers cannot claim to be in an disadvantaged position compared to other countries? I can't give a definitive answer to that, unfortunately. For one, I'm not working in the USA. Next, Europe has a lot of collaborations and cooperation under its belt in this regard. Lastly, China's ecosystem and prowess is completely opaque from me (both secrecy and not being interested/have time). However, the technology is evolving pretty fast. NVIDIA's DPU, AMD/NVIDIA GPUs and AMD processors change the landscape a lot. Intel's systems are not the best systems for heavily GPU accelerated clusters for a long time. So, they might look powerful in enterprise, but HPC is a completely different landscape. Intel is not the clear leader everything computing for some time now. They're not the worst, but they're not the best, either.
- TrueDuality 4y ago
- redwood 4y agoTwitter fails public discourse. What a painful format to read a presumably thoughtful statement from an intellectual. This medium is what our society has come to for public intellectual discourse in the sciences?
- idontknowifican 4y agohow else would you make 13 related statements to the broadest possible group, allowing them to react to each one? is your lack of understanding a platform because you don’t like it showing?
- greyw 4y agolike I'm reacting now to your sentence
- DannyBee 4y agoYou are kidding, right? Yes, how did discourse ever happen prior to twitter? We were all just cavepeople, smearing things on walls, until twitter saved us! I also like that you think any of the 13 statements is even worth individually responding to, when in fact, each one is written in a way to drive reaction, rather than be part of an overall coherent story or thought. They happen to be a reasonable writer, so they can make it overall seem reasonably coherent, but it's also 100% clear the writing would be better if they weren't trying to generate 13 statements that can be individually responded to. The platform has not made it better.
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- darkerside 4y agoWhat is so painful about it?
- halper 4y agoI find it a bit hard to understand the drama. A private company failed to deliver some speculative future technology according to expectations (and/or agreements?). Doesn't that happen all the time? If it is so important to have this supercomputer, isn't it the (US) government that "failed science"? Eggs in baskets and all that.
- arcanus 4y agoThankfully for US (and global) science AMD and HPE were able to deliver an Exascale computer at Oak Ridge National Lab earlier this year: https://www.ornl.gov/news/frontier-supercomputer-debuts-worlds-fastest-breaking-exascale-barrier https://www.ornl.gov/news/frontier-supercomputer-debuts-worl...
- phdelightful 4y agoBetween OpenMP (older computers), CUDA (Nvidia), HIP (AMD), now SYCL (Intel), not to mention more interesting architectures, DOE is probably plently busy and has plenty of very fast computers that are hard enough to keep their codes working on. Aurora being delayed has damaged Intel's reputation and gets chuckled about, but I'm not sure how big of an effect it's really had on the ground.
- imranq 4y agoPeople are too obsessed with more compute. Definitely having more clusters, ghz, flops is a good thing, but in my experience, experiments that take embarrassing amounts of computational resources are extremely low yield. Algorithmic advances are the real MVPs and remain underrated. They are usually the prerequisites for scientific breakthroughs. E.g. AlphaFold2, MapReduce, Blockchain, etc.
- 988747 4y agoAdding compute is easy. Coming up with algorithmic advances is anywhere from hard to impossible.
- Certhas 4y ago... correct me if I am wrong but I believe that AlphaFold2 required massive computational resources beyond the scope of what most university groups have access to. And Blockchain and MapReduce have absolutely 0 to do with enabling science. Which is a pity because I generally believe your statement the algorithms matter is on the money, it's just that the examples you give merely replace one uninformed hype with another uninformed hype that's even less relevant...
- imranq 4y agoAh you're absolutely right. Those examples are more about shifting paradigms over science. I just gave a few examples that came into my head at the moment. Some example of algorithm advances actually furthering science: Compressive sensing - improves MRI reconstruction above Nyquist frequency Union Quick Find - solving percolation problems way faster KD trees - makes particle simulation a tractable problem Sources Princeton Algorithms I and II https://www.cs.princeton.edu/courses/archive/fall18/cos226/assignments.php https://www.cs.princeton.edu/courses/archive/fall18/cos226/a... MIT 6.854 advanced algorithms http://people.csail.mit.edu/moitra/854.html http://people.csail.mit.edu/moitra/854.html
- imranq 4y agoAs for AlphaFold2 and the other DeepMind algorithms, they definitely require lots of compute but not so much that they are blocked by advances in supercomputing. This is evidenced by other teams with fewer resources starting to replicate their results.
- nicohem 4y agoOh goodness. I usually hit HN in the am as I scan for news feeds and such. Didn’t expect to see my tweet here. This was written for my followers on Twitter, most of whom are in supercomputing. I understand how it might seem a bit over the top to anyone outside of HPC, but let me explain why I wrote it (not expecting it would have more mainstream views). People in supercomputing already know what I’m talking about so I didn’t give context. I’m glad some of the respondents here provided good background on the extended delays and the impact. The thread was written because a few months ago after a researcher let me know her work would not be completed since it hinged on Aurora’s completion. With Frontier (at Oak Ridge National Lab) oversubscribed, she can’t finish her work and her immigration status is in jeopardy. I felt badly for her but figured it was a one-off. Then I started to talking to more and more people. I never really connected the employment/post-doc/early career HPC researcher with problems with a machine. The employment and research and academic ‘economy’ around big systems like this is real. Even though by 2021 everyone figured the system wouldn’t be ready by target, it still created a mess. I talked to more, then more people about what the delay meant for their careers. They were all terrified to say anything publicly. Argonne’s under strict NDA and so is everyone else. Further, everyone was worried about losing funding or “being problematic” Since I’m not beholden to NDAs and have the freedom to say tough things about big companies and institutions I did. I did it so the people in the same boat as the people I talked to know that their career-jerking issues have been publicly noted. I considered a more formal article for TNP but it didn’t feel like a fit. What really pushed me to write the thread was all the hype around Intel Innovation this week. They dropped the ball over and over again in HPC since 2017. They hurt people’s careers with these delays. Yet to see them celebrate shipping of a processor that is so far behind (as were the promised ones before it that were to comprise Aurora) and to talk about zettascale ambitions when they have struggled to get a single machine out four years late. It just needed to be called out. I wanted people to see also that processor delays affect far more than server roadmaps. And yes, I understand semiconductor delivery and how difficult and unpredictable it is. It was the lack of transparency and the painfully awkward way NO ONE talked about it. Except most journalists who mentioned it offhand but didn't fully express what was at stake in terms of people costs. So while I’m kind of horrified the tweet for HPC people took off, the positive side of it is that people might think about it this more deeply when they hear “processor X has been delayed” because for comp sci and application domain scientists, the career disruption can be (and should be communicated as) dramatic. I have a pretty packed workday but can check in and answer/give more context as I have time/can. Thanks N
- bluedino 4y agoI wonder what the supply chain is doing to supercomputer builds for the last 2 years. We were waiting on servers, then waiting on GPUs, and now we're apparently waiting on power supplies. And this is just a small addition to a much smaller 'supercomputer' (800 nodes)
- xani_ 4y agoJust plain old servers take months instead of weeks now.
- Symmetry 4y agoFor context, the current state of the TOP500 supercomputer list: https://en.wikipedia.org/wiki/TOP500 https://en.wikipedia.org/wiki/TOP500 The top of the list is an AMD exascale DOE machine at Oak ridge, then Fujitsu's ARM half exaflop machine in Japan, then it drops off rapidly.
- throw7 4y agohttps://threadreaderapp.com/thread/1575233618170982400.html https://threadreaderapp.com/thread/1575233618170982400.html
- nn3 4y ago"The greatest shortcoming of the human race is our inability to understand the exponential function”. -Allen Bartlett What she is complaining about is that a exponential trend (Moore's law leading to more compute) is stuttering. In this case it was just for one company and the world was lucky and had backup options. But undoubtedly there will be more stutters in the future, and there will not always be backups. Science relying on an exponential trend like this it will have more challenges in the future. Same for all the the other trends built around brute force compute like "big AI" deep learning or a lot of the wasteful programming practices that fill the front pages of HN regularly.
- chazeon 4y agoWell all the newer HPC machines they built and we used are from AMD. They are incredible. Haven't been hearing about Intel for a while.
- jdthedisciple 4y agoWhat's the Author's stake in the matter? Why does she seem angry at Intel, a private company? Why doesn't she apply there and do a better job herself? Genuinely confused what this drama is about.
- TheBigSalad 4y agoHer friend's careers are delayed because Intel keeps promising a super computer and they are allotted time with it to work on their research. The super computer keeps getting delayed year after year. "Why doesn't she apply there and do a better job herself" - it's so simple!
- hulitu 4y agoBlaming Intel for US' lack of new supercomputer is a bit weak. IBM also can produce supercomputers. There are also others computer "manifacturers" in US: AMD, HP (itanium), Quallcomm.