[HN Gopher] Cray versus Raspberry Pi
___________________________________________________________________
Cray versus Raspberry Pi
Author : flyingkiwi44
Score : 144 points
Date : 2025-06-11 05:58 UTC (4 days ago)
(HTM) web link (www.aardvark.co.nz)
(TXT) w3m dump (www.aardvark.co.nz)
| hoppp wrote:
| The cray 1 did look futuristic like something out of star trek.
|
| It kinda reminded me of the trash can mac. I wonder if it was
| inspiration for it
| Mountain_Skies wrote:
| If I ever have reason to build a Pi cluster, I'm putting in a
| Cray X-MP shaped case.
| v9v wrote:
| Related: a Pi Pico cluster that looks like a Cray computer
| https://hackaday.com/2023/04/09/parallel-computing-on-the-
| pi...
| einsteinx2 wrote:
| > It kinda reminded me of the trash can mac. I wonder if it was
| inspiration for it
|
| Ironically the trash can Mac actually looked strikingly similar
| in size and shape to actual small trash cans that were all over
| the Apple campus when I worked there. I'd see them in the
| cafeteria every day. They were aluminum though, but otherwise
| very similar. I always wondered if they had anything to do with
| the design of the computer, even if only subconsciously.
| delichon wrote:
| > but then again if you'd showed me an RPi5 back in 1977 I would
| have said "nah, impossible" so who knows?
|
| I was reading lots of scifi in 1977, so I may have tried to talk
| to the pi like Scotty trying to talk to the mouse in Star Trek
| IV. And since you can run an LLM and text to speech on an RPi5,
| it might have answered.
| Mountain_Skies wrote:
| Someday real soon, kids being shown episodes of 'Knight Rider'
| by their grandparents won't understand why a talking car was so
| futuristic.
| sublinear wrote:
| Was that point not almost a decade ago?
| Mountain_Skies wrote:
| Not really. My 1983 Datsun would talk, but it couldn't
| converse. Alexa and Siri couldn't hold a conversation
| anywhere near the level KITT did. There's a big difference.
| With LLMs, we're getting close.
| bsoles wrote:
| Commodore 64 had text to speech in late 80s.
|
| Also, my friend's father in the 80s was the driver of a
| French Consulate's member in Turkey. His car (a Renault)
| had speech functionality.
| nereye wrote:
| Early 80s (1982), according to Wikipedia:
|
| https://en.m.wikipedia.org/wiki/Software_Automatic_Mouth
| hulitu wrote:
| > Commodore 64 had text to speech in late 80s.
|
| Yes, and Windows had Narrator. And that's all. Since 20
| years.
| anthk wrote:
| Test to speech it's trivial with Dr. Sbaitso or Flite in
| ARMv5/Pentium 90 machines.
| mgerdts wrote:
| Your car had a tiny record player.
|
| https://www.autoweek.com/car-life/but-wait-theres-
| more/a1875...
| KineticLensman wrote:
| Like James Bond's Aston Martin with a satnav/tracking device
| in 1964's Goldfinger. Kids would know what that was but they
| might not understand why Bond had to continually shift some
| sort of stick to change the car's gear.
| anthk wrote:
| Gear shifting it's still a thing in Europe, and mandatory
| if you want to get your driver's license.
| prmoustache wrote:
| you can get a driver license with an automatic. But it
| just means you can only drive automatics.
|
| It would have been a huge deal not being able to drive
| manuals 20y ago but hybrid and ev all being automatic it
| is not that much of a downside nowadays unless you want
| to buy old cars or borrow friend's car. Most renting
| fleets have autos available nowadays.
| heelix wrote:
| The self driving aspect, amazingly, is already here and
| considered mundane.
| DrillShopper wrote:
| Oh really? What vehicle can I buy today, drive home, get
| twice the legal limit drunk, flop in the back alone to take
| a nap while my car drives me two hours away to a relative's
| house?
|
| I'd really like to buy that car so I await your response.
| tekla wrote:
| A Tesla is pretty close.
| https://www.youtube.com/watch?v=4RZfkU1QgTI
| more_corn wrote:
| Tesla is in no way close.
| 4ndrewl wrote:
| They're "cold-fusion" close. Which means a perpetual "few
| years".
| bigfatkitten wrote:
| They've been "close" for over a decade now.
| ptero wrote:
| That's a jurisdiction problem, not a technology problem.
| No tech is foolproof, but even with the current
| technology someone would be much safer (for others, too)
| in the back seat than trying to drive tired, borderline
| DUI at night in unfamiliar town. Which many folks
| regularly do, for example on business travel.
|
| The reason I cannot do this today is laws, not
| technology. My 2c.
| dmd wrote:
| The only thing stopping a Waymo from doing that is laws.
| more_corn wrote:
| You can do all that in a Waymo except for the "buy" part.
| When asked about that Sergey said "why do you want to own
| a car? You have to maintain it, insure it, park it at
| home and at work. Don't you really just want to get where
| you're going and have someone else figure out the rest?"
| This was back before google ate the evil pill. Now their
| philosophy is more like "don't fall asleep, we can get a
| good deal on your kidneys, after that we'll sell your
| mom's kidneys too"
| dizhn wrote:
| Kitt was funny though. (For its time)
| Havoc wrote:
| Tried explaining what a Tamagotchi was to someone recently.
| Looks of utter bewilderment
| azeirah wrote:
| Really? Tamagotchis seem to be one of those things that
| have charm beyond straight up nostalgia :o
| worik wrote:
| That is a natural reaction.
| tsoukase wrote:
| I grew up watching Kitt and when I watched it again a few
| days ago, I didn't feel anything. Much less my kids.
| hulitu wrote:
| > Someday real soon, kids being shown episodes of 'Knight
| Rider' by their grandparents won't understand why a talking
| car was so futuristic.
|
| Maybe in 100 years. The talking car was more intelligent than
| Siri, Alexa or Hey Google.
|
| It is not that we are not able to "talk" to computers, it is
| that we "talk" with computers only so that they can collect
| more data about us. Their "intelligence" is limited to simple
| text underestanding.
| olddustytrail wrote:
| I think maybe you missed the last three years. We're not
| talking about Alexa or Hey Google level.
|
| We're talking about Google Gemini or ChatGPT.
| qgin wrote:
| It's impossible to explain to kids now why it was funny on
| Seinfeld when Kramer pretended to be MoviePhone and says "why
| don't you just tell me the name of the movie you selected!"
| rahen wrote:
| No need for an RPi 5. Back in 1982, a dual or quad-CPU X-MP
| could have run a small LLM, say, with 200-300K weights, without
| trouble. The Crays were, ironically, very well suited for
| neural networks, we just didn't know it yet. Such an LLM could
| have handled grammar and code autocompletion, basic linting, or
| documentation queries and summarization. By the late 80s, a
| Y-MP might even have been enough to support a small
| conversational agent.
|
| A modest PDP-11/34 cluster with AP-120 vector coprocessors
| might even have served as a cheaper pathfinder in the late 70s
| for labs and companies who couldn't afford a Cray 1 and its
| infrastructure.
|
| But we lacked both the data and the concepts. Massive, curated
| datasets (and backpropagation!) weren't even a thing until the
| late 80s or 90s. And even then, they ran on far less powerful
| hardware than the Crays. Ideas and concepts were the limiting
| factor, not the hardware.
| adwn wrote:
| > _a small LLM, say, with 200-300K weights_
|
| A "small Large Language Model", you say? So a "Language
| Model"? ;-)
|
| > _Such an LLM could have handled grammar and code
| autocompletion, basic linting, or documentation queries and
| summarization._
|
| No, not even close. You're off by 3 orders of magnitude if
| you want even the most basic text understanding, 4 OOM if you
| want anything slightly more complex (like code
| autocompletion), and 5-6 OOM for good speech recognition and
| generation. Hardware was _very much_ a limiting factor.
| rahen wrote:
| I would have thought the same, but EXO Labs showed
| otherwise by getting a 300K-parameter LLM to run on a
| Pentium II with only 128 MB of RAM at about 50 tokens per
| second. The X-MP was in the same ballpark, with the added
| benefit of native vector processing (not just some
| extension bolted onto a scalar CPU) which performs very
| well on matmul.
|
| https://www.tomshardware.com/tech-industry/artificial-
| intell...
|
| John Carmack was also hinting at this: we might have had AI
| decades earlier, obviously not large GPT-4 models but
| useful language reasoning at a small scale was possible.
| The hardware wasn't that far off. The software and
| incentives were.
|
| https://x.com/ID_AA_Carmack/status/1911872001507016826
| adwn wrote:
| > _EXO Labs showed otherwise by getting a 300K-parameter
| LLM to run on a Pentium II with only 128 MB of RAM at
| about 50 tokens per second_
|
| 50 token/s is completely useless if the tokens themselves
| are useless. Just look at the "story" generated by the
| model presented in your link: Each individual sentence is
| somewhat grammatically correct, but they have next to
| nothing to do with each other, they make absolutely no
| sense. Take this, for example:
|
| _" I lost my broken broke in my cold rock. It is okay,
| you can't."_
|
| Good luck tuning this for turn-based conversations, let
| alone for solving _any_ practical task. This model is so
| restricted that you couldn 't even benchmark its
| performance, because it wouldn't be able to follow the
| simplest of instructions.
| rahen wrote:
| You're missing the point. No one is claiming that a
| 300K-param model on a Pentium II matches GPT-4. The point
| is that it works: it parses input, generates plausible
| syntax, and does so using algorithms and compute budgets
| that were entirely feasible decades ago. The claim is
| that we could have explored and deployed narrow AI use
| cases decades earlier, had the conceptual focus been
| there.
|
| Even at that small scale, you can already do useful
| things like basic code or text autocompletion, and with a
| few million parameters on a machine like a Cray Y-MP, you
| could reasonably attempt tasks like summarizing
| structured or technical documentation. It's constrained
| in scope, granted, but it's a solid proof of concept.
|
| The fact that a functioning language model runs at all on
| a Pentium II, with resources not far off from a 1982 Cray
| X-MP, is the whole point: we weren't held back by
| hardware, we were held back by ideas.
| alganet wrote:
| > we weren't held back by hardware
|
| Llama 3 8B took 1.3M hours to train in a H100-80GB.
|
| Of course, it didn't took 1.3M hours (~150 years). So,
| many machines with 80GB were used.
|
| Let's do some napkin math. 150 machines with a total of
| 12TB VRAM for a year.
|
| So, what would be needed to train a 300K parameter model
| that runs on 128MB RAM? Definitely more, much more than
| 128MB RAM.
|
| Llama 3 runs on 16GB VRAM. Let's imagine that's our
| Pentium II of today. You need at least 750 times what is
| needed to run it in order to train it. So, you would have
| needed ~100GB RAM back then, running for a full year, to
| get that 300K model.
|
| How many computers with 100GB+ RAM do you think existed
| in 1997?
|
| Also, I only did RAM. You also need raw processing power
| and massive amounts of training data.
| rahen wrote:
| You're basically arguing that because A380s need millions
| of liters of fuel and a 4km runway, the Wright Flyer was
| impossible in 1903. That logic just doesn't hold.
| Different goals, different scales, different assumptions.
| The 300K model shows that even in the 80s, it was both
| possible and sufficient for narrow but genuinely useful
| tasks.
|
| We simply weren't looking, blinded by symbolic
| programming and expert systems. This could have been a
| wake-up call, steering AI research in a completely
| different direction and accelerating progress by decades.
| That's the whole point.
| alganet wrote:
| "I mean, today we can do jet engines in garage shops. Why
| would they needed a catapult system? They could have used
| this simple jet engine. Look, here is the proof, there's
| a YouTuber that did a small tiny jet engine in his
| garage. They were held back by ideas, not aerodynamics
| and tooling precision."
|
| See how silly it is?
|
| Now, focus on the simple question. How would you train
| the 300K model in 1997? To run it, you someone to train
| it first.
| rahen wrote:
| Reductio ad absurdum. A 300K-param model was small enough
| to be trained offline, on curated datasets, with CPUs and
| RAM capacities that absolutely existed at the time,
| especially in research centers.
|
| Backprop was known. Data was available. Narrow tasks
| (completion, summarization, categorization) were
| relevant. The model that runs on a Pentium II could have
| been trained on a Cray, or across time on any reasonably
| powerful 90s workstation. That's not fantasy, LeNet 5
| with its 65K weight was trained on a mere Sun station in
| the early 90s.
|
| The limiting factor wasn't compute, it was the conceptual
| framing as well as the datasets. No one seriously tried,
| because the field was dominated by symbolic logic and
| rule-based AI. That's the core of the argument.
| alganet wrote:
| > Reductio ad absurdum.
|
| My dude, you came up with the Wright brothers comparison,
| not me. If you don't like fallacies, don't use them.
|
| > on any reasonably powerful 90s workstation
|
| https://hal.science/hal-03926082/document
|
| Quoting the paper now:
|
| > In 1989 a recognizer as complex as LeNet-5 would have
| required several weeks' training and more data than were
| available and was therefore not even considered.
|
| Their own words seem to match my assessment.
|
| Training time and data availability determined how much
| this whole thing could advance, and researchers were
| aware of those limits.
| fentonc wrote:
| I think a quad-CPU X-MP is probably the first computer that
| could have run (not train!) a reasonably impressive LLM if
| you could magically transport one back in time. It supported
| a 4GB (512 MWord) SRAM-based "Solid State Drive" with a
| supported transfer bandwidth of 2 GB/s, and about 800 MFLOPS
| CPU performance on something like a big matmul. You could
| probably run a 7B parameter model with 4-bit quantization on
| it with careful programming, and get a token every couple
| seconds.
| JdeBP wrote:
| You should have been _watching_ lots of SciFi, too. (-:
|
| I have a Raspberry Pi in a translucent "modular case" from the
| PiHut.
|
| * https://thepihut.com/products/modular-raspberry-pi-4-case-
| cl...
|
| It is very close to the same size and appearance as the "key"
| for Orac in _Blake 's 7_.
|
| I have so far resisted the temptation to slap it on top of a
| Really Useful Box and play the buzzing noise.
|
| * https://youtube.com/watch?v=XOd1WkUcRzY
|
| Obviously not even Avon figured out that the main box of Orac
| was a distraction, a fancy base station to hold the power
| supply, WiFi antenna, GPS receiver, and some Christmas tree
| lights, and all of the computational power was really in the
| activation key.
|
| The amusing thing is that that is not the only 1970s SciFi
| telly prop that could become almost real today. It shouldn't be
| hard -- all of the components exist -- to make an actual _Space
| 1999_ commlock; not just a good impression of one, but a
| _functioning_ one that could _do_ teleconferencing over a LAN,
| IR control for doors and tellies and stuff, and remote computer
| access.
|
| Not quite in time for 1999, alas. (-:
|
| * https://mastodonapp.uk/@JdeBP/114590229374309238
| Cheer2171 wrote:
| > If AI systems continue to improve at the current rate and we
| combine that with improvements in hardware that are measured in
| orders of magnitude every 15 years or so then it stands to reason
| that we'll get that "super-intelligent GAI" system any day now.
|
| Oh come off it now. This could have been just a good blog post
| that didn't make me want to throw my phone across the room. GenAI
| is a hell of a drug. It's shocking how many technical
| professionals fall into the hype and become irrationally
| exuberant.
| Cheer2171 wrote:
| Even if you are a GAI / super intelligence booster, the
| limiting factor is clearly software and data. If it is
| possible, the big tech AI labs already have all the compute
| they need to make one deployment work. Hardware is limiting for
| deploying at scale and at a profit.
| moffkalast wrote:
| I was more about to point out that the 10x per 15 years for
| hardware hardly holds anymore for silicon and it's ridiculous
| to expect that to continue.
| Y_Y wrote:
| > it stands to reason that
|
| The upper-class "trust me bro"
| bombcar wrote:
| What happened to the programs/problems the Cray 1 solved? If
| anyone can do it on commodity hardware - is it being done? Is it
| all solved?
| criddell wrote:
| Most are not solved but modern systems can generate better
| solutions. Think about problems like forecasting weather or
| finite element analysis of mechanical systems.
| Cheer2171 wrote:
| It was pretty basic models for tasks like weather forecasting
| and simulating nuclear reactions. We've come a long way on both
| the software modeling and hardware front.
| acidburnNSA wrote:
| We still use a lot of the same software for nuclear reactor
| simulations. They just run a lot faster.
| cratermoon wrote:
| Work in computational fluid dynamics is limited by computing
| power. Bigger and faster computers give more accuracy and
| speed.
| whartung wrote:
| A "famous" instance was the use of a Cray to render the
| collapse of Jupiter in the movie "2010". A very early example
| of CGI in cinema.
| johannes1234321 wrote:
| No. With more computing power the level of detail increased.
|
| And some problems are even more complex.
|
| My father spent his career on researching coil forms for
| Stellerator fusion reactors. Finding the shapes for their
| experiments then was a huge computational problem using then-
| state of the art machines (incl. cray for a while) and even
| today's computing power isn't there, yet.
|
| Other problems we now solve regularly on our phones ...
| benob wrote:
| Cray1 should be compared to nowadays raspberry pi pico 2 / rp2350
| which has similar specs (using external ram).
| jgalt212 wrote:
| I won't rest until the average microcontroller in an optical
| mouse is more powerful than a Cray 1.
| 1oooqooq wrote:
| try as you may, but that mouse will never work as a lounge
| center piece.
| kdndnrndn wrote:
| I'm not aware of any optical mouse using a general purpose
| MCU, to my knowledge they are all using ASICs
| Rohansi wrote:
| Some gaming mice do for running RGB lights, macros, or
| whatever.
| sweetcocomoose wrote:
| Nordic dominates the market for keyboards and mice.
| Programmable MCUs with BLE radios are required for any
| wireless devices.
| bigfatkitten wrote:
| There are millions, if not tens of millions of USB and PS/2
| keyboards and mice out there powered by Cypress MCUs with
| 8051 cores.
| qooiii2 wrote:
| A lot of touchscreens meet that requirement. Turns out it's
| often cheaper to solve problems with algorithms than avoid
| them by design.
| zouhair wrote:
| These comparisons are fun at all but a better one would be the
| difference between whatever "computer" a citizen lambda would
| have used back in the day and the cray1 and whatever on can use
| now and the current "cray" (or whatever humans use now) and see
| the difference of cost.
| cratermoon wrote:
| The first Cray-1 was installed at Los Alamos National
| Laboratory in 1976. That same year Gary Kildall created CP/M
| and Steve Wozniak completed the Apple-1.
| kayodelycaon wrote:
| I did a little poking round and I think the modern equivalent
| to old super computers is a mainframe. Modern super computers
| take up entire warehouses, cost upwards of $100 million, and
| are measured in exaflops.
|
| Cray 1 costs US$7.9 million in 1977 (equivalent to $41 million
| in 2024) (Source: Wikipedia)
|
| I have no idea what IBM z-series mainframes cost but I think it
| would be less.
|
| $41 million can buy you one or more thousands of rack-mounted
| servers and the associated networking hardware.
|
| My rough guess would be the difference in 2024 iphones to
| mainframes is an order of magnitude more between them than Cray
| and anything else on the market at the time.
|
| It's also interesting to note how much software has changed.
| The actual machine code may be less optimized, but we have
| better algorithms and we have the option of using vast amounts
| of memory and disk to save cpu time. And that's before we get
| into specialized hardware.
| giantrobot wrote:
| Mainframes aren't supercomputers. The point of a mainframe
| (anymore) is reliable transactions without downtime. They're
| not necessarily beasts at computation.
|
| Supercomputers were and are beasts of not only computation
| but memory size and bandwidth. They're used for tasks where
| the computation is highly parallel but the memory is not. If
| you're doing nuclear physics or fluid dynamics every particle
| in a simulation has _some_ influence on every other. The more
| particles and more state for each particle you can store and
| apply to every other particle makes for a more accurate
| simulation.
|
| As SCs have improved in memory size and bandwidth
| simulations/modeling with them has gotten more accurate and
| more useful.
| ajsnigrutin wrote:
| Hardware has gone a long way...
|
| ...software... well, that's a different story.
|
| While a cray could compute millions of things and did a bunch of
| usable stuff for many groups of people who used it back then, a
| raspberrypi today has trouble even properly displaying a weather
| forecast at "acceptable speeds", because modern software has
| become very bloated, and that includes weather forecast sites
| that somehow have to include autoplaying video, usually an ad.
| adgjlsfhk1 wrote:
| otoh a pi running stockfish would beat deep blue 100-0
| lawik wrote:
| No benchmarks. Hard to take this seriously.
| _fat_santa wrote:
| Reading this I wonder, say we did have a time machine and were
| somehow able to give scientists back in the day access to an
| RPI5. What sort of crazy experiments would that have spawned?
|
| I'm sure when the Cray 1 came out, access to it must have been
| very restricted and there must have been hoards of scientists
| clamoring to run their experiments and computations on it. What
| would have happened if we gave every one of those clamoring
| scientists an RPI5?
|
| And yes I know this raises an interface problem of how would they
| even use one back in the day but lets put that to the side and
| assume we figured out how to make an RPI5 behave exactly like a
| Cray 1 and allowed scientists to use it in a productive way.
| maxerickson wrote:
| Do you think they would have run experiments that have been
| missed in the meantime? Why?
| mikewarot wrote:
| First of all, how would they talk to it? You'd have to give
| them an RPI5 with serial console enabled, and strict
| instructions not to exceed the 3.3 volt limits of the I/O. Now
| it's reasonable that you could generate NTSC video out of it,
| so they could see on the screen any output.
|
| When you then explained it was just bit-banging said NTSC
| output, they'd be amazed even more.
| Aardwolf wrote:
| Give it also an hdmi screen and usb keyboard, what more do
| you need to type code and see the result
| dottedmag wrote:
| Serial port
|
| Cray 1 was released 1975, teletypes were old tech at that
| time.
| username223 wrote:
| > What sort of crazy experiments would that have spawned?
|
| Scientists then (at least a lot of them) knew what they wanted
| to do, and it required faster computers rather than more of
| them. A lot of that Cray power at the national labs was doing
| fluid simulation (i.e. nuclear explosions), and with the
| computers they had in the 80s, it was done in one or two
| dimensions, relying on symmetry. Going from n^2 to n^3 grid
| cells was the obvious next step, but took a lot more memory and
| CPU speed.
| Havoc wrote:
| Finding more & more that power efficiency is what's driving me
| towards new gear rather than lack of horsepower.
|
| A few niche uses aside (gaming, llm) a vaguely modern desktop is
| good enough regardless of details.
| dgacmu wrote:
| Comparing against a raspberry pi 5 is kind of overkill. While a
| Pico 2 is close to computationally equivalent to a cray 1 now
| (version 2 added hardware floating point), the cray still has
| substantially more memory - almost 9MB vs 520k.
|
| For parity, you have to move up to a raspberry pi zero 2, which
| costs $15 and uses about 2W of powerm
|
| A million times cheaper than a cray in 2025 dollars and quite a
| bit more capable.
| nereye wrote:
| The memory in the Cray was external and there are RP2350 boards
| with 16MB of QSPI flash, here's one of them:
|
| https://www.olimex.com/Products/RaspberryPi/PICO/PICO2-XXL/o...
| omega3 wrote:
| Are there any details or examples of computational work the Cray
| 1 used for?
| dahart wrote:
| My former boss (Steve Parker, RIP) shared a story of Turner
| Whitted making predictions about how much compute would be needed
| to achieve real-time ray tracing, some time around when his
| seminal paper was published (~1980). As the story goes, Turner
| went through some calculations and came to the conclusion that
| it'd take 1 Cray per pixel. Because of the space each Cray takes,
| they'd be too far apart and he thought they wouldn't be able to
| link it to a monitor and get the results in real time, so instead
| you'd probably have to put the array of Crays in the desert, each
| one attached to an RGB light, and fly over it in an airplane to
| see the image.
|
| Another comparison that is equally astonishing to the RPi is that
| modern GPUs have exceeded Whitted's prediction. Turner's paper
| used 640x480 images. At that resolution, extrapolating the 160
| Mflops number, 1 Cray per pixel would be 49 Tera flops. A 4080
| GPU has just shy of 50 Tflops peak performance, so it has
| surpassed what Turner thought we'd need.
|
| Think about that - not just faster than a Cray for a lot less
| money, but one cheap consumer device is faster than 300,000
| Crays.(!) Faster than a whole Cray _per pixel_. We really have
| come a long, long way.
|
| The 5090 has over 300 Tflops of ray tracing perf, and the Tensor
| cores are now in the Petaflops range (with lower precision math),
| so we're now exceeding the compute needed for 1 Cray per pixel at
| 1080p. 1 GPU faster than 2M Crays. Mind blowing.
| magicalhippo wrote:
| > 1 Cray per pixel would be 49 Tera flops. A 4080 GPU has just
| shy of 50 Tflops peak performance
|
| Interesting, wonder how it compares in terms of transistors.
| How many transistors combined did one Cray have in compute and
| cache chips?
| dahart wrote:
| The Wikipedia article says the Cray-1 has 200k gates. I
| assume that would mean something slightly north of 2x the
| number of transistors?
| https://en.wikipedia.org/wiki/Cray-1#Description
|
| 200k * 300k Cray-1s would be 60B gates, whereas the 4080
| actually has 46B transistors. Seems like we're totally in the
| right ballpark.
| hattmall wrote:
| Nice, but the ~40 year latency is kind 0f high.
| nottorp wrote:
| But the Cray had a general purpose CPU while the GPUs have
| specialized hardware. Not exactly apples to apples.
| monocasa wrote:
| The main part of the Cray was a compute offload engine that
| asynchronously executed job lists submitted by front end
| general purpose computers that ran OSes like Unix.
|
| It was actually pretty close to the model of a GPU.
| ForOldHack wrote:
| Adjust the price of the Cray-1, for inflation, but not the power,
| for Moore's law? Need I get my napkin out for a few calculations?
| or do we just FORGET MOORE'S LAW ( that is mention no less that 4
| times, without quantification? Cray-1 (1976 ). RPi ( 2012 ). 37
| years of elapsed time. 24. 2/3 elapsed generations. 26,509,000
| times increase in power. Cray 1 160Mf. In a 26M times faster,
| would yield 4,241Gf ( 4.2Pf) , while the PI1 is capable of
| 13.5Gf, so the RPi-1 ( 2012 ) is about 0.31% of where Moore's law
| power doubling is.
|
| Now lets compare this to the top 500. ( see the point? )( do not
| speak of Moore's law, while ignoring the mathematical
| implications. ) ( and yes, 3/1000s is three thousandths ).
|
| Top 500 is 1.7 Exaflops, but by Moore's law should be 4,241Gf or
| 4.2Xf. So the top 500 is not keeping up with Moore's law.
| lttlrck wrote:
| However Moores Law refers to the number of transistors. Not
| FLOPS.
| grubrunner666 wrote:
| This thread should be a MasterClass. Awesome reading. Seriously.
| -a gen x'er.
| smcameron wrote:
| And you can 3D print a Cray YMP case for your Raspberry Pi:
| https://www.thingiverse.com/thing:6947303
| jwr wrote:
| What I find somewhat puzzling is that these machines were used
| for the "really big problems". We used supercomputers for weather
| forecasting, finite element simulations, molecular modeling. And
| we were getting results.
|
| I don't feel we are getting results that are thousands of times
| better today.
| motorest wrote:
| > I don't feel we are getting results that are thousands of
| times better today.
|
| You are getting results that are way better than thousands of
| times. You just aren't aware where they are showing up.
|
| To give you a glimpse, the same modelling problems which a
| couple of decades ago tool days to come up with a crude
| solution are now being executed within a loop in optimization
| problems.
|
| You are also seeing multiphysics and coupling problems showing
| up in mundane applications. We're talking about problems that
| augment the same modelling problems that a couple of decades
| ago tool days to solve with double or triple the degrees of
| freedom.
|
| Without the availability of these supercomputers the size of
| credit cards, the whole field of computer-aided engineering
| would not exist.
|
| Also, to boot, there are indeed diminished returns. Increasing
| computational resources unblocks constraints such as being able
| to use doubles instead of floats. This means that lowering
| numerical errors in 3 or 4 decimal places comes for free at the
| expense of taking around 4 times longer to solve the same
| problem.
|
| To top things off, do you think the results of two decades ago
| were possible without employing a great deal of simplifications
| and crude approximations? As legend has it, the F117 Nighthawk
| got it's design due to the computational limits of the time.
| Since then, stealth planes became more performant and with a
| smoother design. That's what you get when your computational
| resources are a thousands times better.
| adgjlsfhk1 wrote:
| We aren't getting results thanks of times better. we're getting
| results 10s of times better on problems with cubic (or worse)
| scaling. e.g. 3 day forecasts as of 2017 are more reliable than
| 1 day forecasts in 1990 https://external-
| content.duckduckgo.com/iu/?u=https%3A%2F%2F...
| ziofill wrote:
| It is a frequent fantasy of mine to bring tech back to historical
| figures, like to show my phone to Galileo or to take Leonardo da
| Vinci for a ride in my car. But I guess you don't need to go that
| far to blow minds.
| prmoustache wrote:
| Just show it to someone being released after 30 to 40 years in
| jail.
| Animats wrote:
| Back in 2020, someone built a working model of a Cray-1.[1] Not
| only is it instruction compatible, using an FPGA, it's built into
| a 1/10 scale case that looks like a Cray-1.
|
| The Cray-1 is really a very simple machine, with a small
| instruction set. It just has 64 of everything. It was built from
| discrete components, almost the last CPU built that way.
|
| [1] https://www.cpushack.com/2010/09/15/homebrew-
| cray-1a-1976-vs...
| _tom_ wrote:
| The pi has a sub $100 accelerator card that takes it to 30
| TFLOPs. So you can add three more orders of magnitude of
| performance for a rough doubling of the price.
| dale_huevo wrote:
| > the Cray had about 160MFLOPS of raw processing power; the Pi
| has... up to 30GFLOPS. Yes... that's _giga_ FLOPS. This makes it
| almost 200 times faster than the Cray.
|
| Imagine traveling back to 1977 and explaining to someone that in
| 2025 we've allocated all that extra computing power to processing
| javascript bundles and other assorted webshit.
| usrnm wrote:
| That actually wouldn't be so bad, but in reality the number one
| usecase for raspberry pi is blinking leds for some time and
| collecting dust afterwards
| darkwater wrote:
| Still a better user than crunching Javascript to show you ads
| and track you around.
| hagbard_c wrote:
| No, the number one use case for Pies is being built into
| commercial hardware in the form of compute boards.
| qingcharles wrote:
| In 2013 I'd just built a new top-spec PC. I looked up the
| performance and then back-calculated using the TOP500+ and I
| believe it would have been the most powerful supercomputer in the
| world in about 1993. If you back-calculated further, I think
| around 1980 it became more powerful than every computer on the
| planet combined.
|
| + https://en.wikipedia.org/wiki/TOP500
| noobermin wrote:
| I guess I'm old because this hasn't really been that insightful
| of interesting observation just by itself anymore. People often
| talk about technological advancement of computing as if it is a
| force of nature whereas the amazing specs of say a rp2350
| compared to the cray-1 is more of a story of the economies of
| scale as opposed to merely technical know-how and design. The
| reason a rp2350 is a few dollars is because of fabs,
| infrastructure, and institutional knowledge that likely dwarf the
| cost of producing a cray-1. I wouldn't even be surprised if
| someone bothered to do a similar calculation of the cost of
| infrastructure needed behind each cray-1 at the time that it
| could even be less what is needed to produce rp2350s today. The
| unit price of a rp2350 to consumers being so cheap (right now
| that fabs still want to make it) somewhat elides the actual costs
| involved.
|
| Animats below said that the Cray-1 was made from discrete
| components. Good luck making a rp2350 from discrete components,
| it likely wouldn't even function well at the desired frequency
| due to speed of light and RF interference issues--it would likely
| be even worse for GHz broadcoms used in the rpi5. This means that
| in a post-apocolyptic future you could make another cray-1 given
| enough time and resources. In 20 years when the fabs have stopped
| making rp2350s there simply will not be any more of them.
| adgjlsfhk1 wrote:
| I think the really interesting post here is that a reasonably
| high level of computer is basically free. you can get a 32 but
| microcontroller with 16mb of ram at above 100mhz for well under
| $1. you can buy a USB cable and it has 2 full computers inside
| it.
| username223 wrote:
| That was a weird turn to AI at the end, but otherwise an
| interesting reflection. I'm a little too young to have grown up
| in the era of the Cray-1, but even in the early 90s, processors
| ran at 90 MHz and hard drives cost $1 per megabyte. Back when
| personal computers ran at single-digit megahertz and had
| kilobytes of RAM, a Cray was mind-blowing.
|
| The exciting part back then was that, while computers were never
| "good enough," they were getting noticeably better every few
| months. If you were in the market for a computer, you knew you
| could get a noticeably better one for the same price if you just
| waited a little while. The next model was exciting, because it
| was tangibly better. At some point personal computers became
| "good enough" for most people. Other than compensating for
| creeping software bloat, there hasn't been much reason for most
| people to be excited about new computers in a decade or more.
| qgin wrote:
| Yes but can you sit on your Raspberry Pi like this
| https://volumeone.org/uploads/image/article/005/898/5898/hea...
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