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Parallella: A Supercomputer For Everyone
- nnq 14y agoWTF: "45 GHz of equivalent CPU performance" (though I see the more informative "50 GFLOPS/Watt" below... and I like the prospect of something that would make it cheap to play with large scale real time neural nets...)
- compilercreator 14y agoTheir attempts at marketing talk are indeed very bad, but their technology is pretty interesting.
- alexchamberlain 14y agoVery good way of summing it up!
- adapteva 14y agoYes, agreed! We definitely got carried away with the marketing lingo and we apologize! This was our thought process: We have received a lot of negative feedback regarding this number so we want to explain the meaning and motivation. A single number can never characterize the performance of an architecture. The only thing that really matters is how many seconds and how many joules YOUR application consumes on a specific platform. Still, we think multiplying the core frequency(700MHz) times the number of cores (64) is as good a metric as any. As a comparison point, the theoretical peak GFLOPS number often quoted for GPUs is really only reachable if you have an application with significant data parallelism and limited branching. Other numbers used in the past by processors include: peak GFLOPS, MIPS, Dhrystone scores, CoreMark scores, SPEC scores, Linpack scores, etc. Taken by themselves, datasheet specs mean very little. We have published all of our data and manuals and we hope it's clear what our architecture can do. If not, let us know how we can convince you.
- microtherion 14y agoAs one of the HN contributors who mocked the GHz performance spec in an earlier discussion thread, I welcome the fact that you're engaging in debate about this. That said, I still think that the GHz stat is just about as BAD a metric as any (I suppose "pin count times # of cores" would be worse :-). About the only positive inference I can draw from this is that you have the thermal situation in your system under control. But piling up cores and cooling them is, IMHO, one of the easiest parts of designing a massively parallel system. The interesting part of the design is the interconnections between the cores, and any metric that multiplies single core performance by number of cores tells me nothing about that. So not only am I not learning a key part of the performance characteristics of your system, but by omitting it, you make me wonder whether the ENGINEERING of the system might be similarly misguided on this aspect as the MARKETING seems to be (i.e. does marketing omit this aspect of the system because it was not important to the engineers either?). Linpack at least has benchmarks both for showing off the cores in nearly independent scenarios, and for showing the system when actual communication has to take place. Obviously, each parallel application is different, but you'd at least show ONE indication of performance in situations that are not embarrassingly parallel (http://en.wikipedia.org/wiki/Embarrassingly_parallel http://en.wikipedia.org/wiki/Embarrassingly_parallel).
- adapteva 14y agoThanks for posting a very valid concern! Does the following FFT based image processing demo address the concern about communication bottlenecks in the approach? http://www.adapteva.com/white-papers/using-a-scalable-parallel-2d-fft-for-image-enhancement/ http://www.adapteva.com/white-papers/using-a-scalable-parall... Corner turns for 2D FFTs are usually quite challenging for GPUs and CPUs.[ref] Yaniv, our DSP guru, completed the corner turn part of the algorithm with ease in a couple of days and the on chip data movement constitutes a very small portion of the total application wall time.(complete with source code published as well if you really want to dig). It's hard to market FFT cycle counts to the general audience:-)
- microtherion 14y ago
- bdfh42 14y agoThis is an interesting project that deserves to reach it's funding goal but progress towards that is slow (I have been keeping an eye on it since launched on Kickstarter). I suspect the problem is that it has no compelling (and immediate) "use case". If they could communicate a set of application ideas then I suspect that a whole new raft of supporters will be happy to risk at least $99.
- imrehg 14y agoAlso their video is just mediocre. Very slow and very elevator-music like. I really want it to succeed, backed it already and got some more friends to do that too, but they have to do more as well. Fortunately these days they did make some progress by opening up the specs and more reward options. Also, the $3million stretch goal is just waaaaay too far, too bad that the better design is floated for just that level.
- compilercreator 14y agoI have backed this project. This is an interesting startup, with some good solid technology behind it. They have managed to design and tape out a chip with just a 2m dollar budget so far. The main draw of their architecture is not its peak, but rather its efficiency, both in terms of perf/watt and perf/die area. You can look at their manuals on the site. Hoping their funding drive succeeds. I am liking the fact that ISA is being fully documented and we will have a fully open-source toolchain to work with the system. (Disclaimer: Not associated with Adapteva in any way).
- tsmarsh 14y agoI'm also a backer and I've been completely surprised by the lack of interest. $99 to try what could represent the future of CPU design. I see it as a platform to really try out if the new wave of concurrent languages really make a difference on these platforms.
- lelf 14y agohttp://news.ycombinator.com/item?id=4583263 http://news.ycombinator.com/item?id=4583263
- mbenjaminsmith 14y agoI don't really have any comment on the project itself (not something I would ever use and I don't know the value of what they're proposing). But on purely geek terms this thing seems to warrant a "holy shit": http://www.adapteva.com/products/silicon-devices/e64g401/ http://www.adapteva.com/products/silicon-devices/e64g401/ Again I don't know how (un)common that sort of thing is but I wasn't expecting to see 64 cores in that tiny form factor. Does anyone here know how cutting edge this thing is if at all? [Edit] Also does anyone here want to address use cases for this thing?
- Swizec 14y agoDon't modern GPU's have essentially thousands of cores?
- sspiff 14y agoYes, but modern GPUs also use upwards of 100W of power, and their cores operate mostly in lock-step, which means they aren't fast for all kinds of tasks.
- stonemetal 14y agoIt really depends on what you consider a core. http://www.anandtech.com/show/2918/2 http://www.anandtech.com/show/2918/2 That first picture shows 4 cores made of 4 sub cores with 32 processing elements each. Now Nvidia would claim each of those 32 processing elements is a core, but each of those cores can not act independently. So it is more like a very wide, very hyper threaded 16 core processor.
- DeepDuh 14y agoI think NVIDIAs definition of a 'core' has some merit. First of all, they have some independency in that you can introduce branches over a subset of them, so they're not just SIMD vector units. Secondly, their threaded programming model is pretty well suited for many computational tasks. Executing the same operations over a whole 2D or 3D region of data is a pretty common thing in computing. If you can't parallelize your task that way, chances are it's not even parallelizeable on N x86 cores. If you compare this to x86 however, you'd have to count n Cores times the SSE vector length on each core to be fair. GPUs still come out ahead for most of heavy computational tasks though - which is why Intel is now fighting back with their Xeon Phi stuff (which sounds very promising btw., looking forward to play with our prerelease model that's coming soon ;) ).
- sspiff 14y agoDoes anyone know what kind of cores these RISC cores will be? Will it be some lower end ARM version, or MIPS? Will it be something for which a wide array of tooling already exists, or will this have its own custom architecture which only works with their toolchain?
- willvarfar 14y agoThey have the cores and they are custom, if I read the blurb right. They already have the cores!
- rsneekes 14y agoArchitecture reference manual can be found here: http://www.adapteva.com/support/docs/e3-reference-manual/ http://www.adapteva.com/support/docs/e3-reference-manual/
- fuzzy 14y agoAccording to the kickstarter page the RISC cores are ARM A9.
- wtracy 14y agoThere are two ARM A9 cores (running Ubuntu) and 16 custom Epiphany cores.
- willvarfar 14y agoI would enjoy making a ray-tracing GPU from one of these. That the cores don't run in lockstep can be shader heaven! I'm imagining using the cores in a pipeline with zoning so some core 'owns' some tile of the screen and does z-buffering, and other core does clipping of graphics primitives for each tile, and a sea of compute nodes between them chew up work and push it onwards. Some kind of using the cores as a spatial index too. Passing rays to other cores as they propagate beyond the aabb belonging to a core. Doubtless it wouldn't work like that. And wouldn't work well. But its fun thinking about it! :)
- plextoria 14y agoI'm so hoping this gets funded.
- jacques_chester 14y agoI think folk need to stop abusing the term "supercomputer". It is not really a performance designation. It doesn't define a certain architecture or design. It is pretty clearly an economic designation.
- scott_s 14y agoI agree that people tend to abuse the term, but I think it is a performance designation. It's just a sliding performance target. A supercomputer is a computer that can achieve the upper limits of what has been achieved in performance.
- jacques_chester 14y agoAnd what sets those upper limits? In general: money. Buying more of the most performant equipment available. So. It's an economic designation.
- scott_s 14y agoSure, you're limited by money. But if someone magically was able to produce a machine for $100 that was on par with Titan (http://en.wikipedia.org/wiki/Titan_(supercomputer) http://en.wikipedia.org/wiki/Titan_(supercomputer)) I would still call it a "supercomputer" until it became ubiquitous.
- lotyrin 14y agoIf they only had one, it doesn't matter how much it cost them to make, it's worth much much more than $100 dollars to someone. If there were enough supply that it were possible for it to be only $100 then it would have to already be ubiquitous. I agree with jacques_chester that it's an economic distinction.
- scott_s 14y agoChange "able to produce" with "willing to sell for" and my point remains the same. I agree that you're not going to get a "supercomputer" for less than about $100,000. But supercomputers are defined by what they can do. Their cost is secondary. Necessary in a world without magic, but secondary. I can spend $100,000 on a computer, but that alone does not make it a "supercomputer".
- deleted 14y ago[deleted]
- batgaijin 14y agoI'd rather see a kickstarter for a book on greenarrays programming :(
- deleted 14y ago[deleted]
- err 14y agoglad to know i'm not alone. perhaps some instructional videos will suffice for now? http://www.youtube.com/user/GreenArraysInc?feature=CAQQwRs%3D http://www.youtube.com/user/GreenArraysInc?feature=CAQQwRs%3...
- throwaway1979 14y agoI picked up a raspberry Pi a few days ago. Initially, I was blown away by the low price point. Since then, I've been reflecting on what makes a computer useful. For personal computers - desktops and laptops - I think we don't have a shortage of processor cycles. The minimal specs of the Raspberry Pi make it useable - 256MB of RAM, 700 MHz CPU, a few GB of storage and enough MB to saturate a home broadband connection. What is compelling about the best contemporary personal computing devices is form factor. How easy is it to provide input; how nice is the screen; if it is a mobile device, how heavy is it and does the battery last long enough, etc. Does a personal parallel computer really help me? At first blush, I am having a hard time seeing how. Clearly, there are CPU intensive workloads that people have mentioned in this discussion - ray tracing is one. The video mentions robotics and algorithms. I have mixed feelings about that since I personally believe the future of robotics lies in computation off the physical robot itself - aka cloud robotics. A use case I personally would find beneficial is the ability to run dozens of VMs on the same machine. Heck ... each of my 50 open browser tabs could run inside separate VMs. I know light weight container technology is around for a while. e.g. jails, LXC. But what about hypervisor-based virtualization - e.g. VMWare, Xen, etc.? While the parallelization offered by this tech would be awesome, what seems to be missing is the ability to address lots and lots of memory.
- Qworg 14y agoAs the majority of robotics research in the US is paid for by the military, I think there's more of a market for "fast computation on board" than you'd think. Communication and networking is expensive and hard. As a practicing roboticist, I'd love to work with a few of these. =)
- gavanwoolery 14y agoThe real value is in pushing forward a general compute device with many cores. Overall our programs are still stuck in the 1-2 thread era, and there is a bit of a chicken/egg problem. Without a very effective multicore processor, the payoff in writing parallel programs is small. GPGPU is still to expensive and not very practical due to memory constraints and the GPU/system memory bottleneck. This probably wont be the device to change all of that, but even failure is progress.
- ksadeghi 14y agoYes but can they mine Bitcoins? They come with OpenCL drivers so in theory they could as most Bitcoin miners have OpenCL interfaces to the GPU.
- runako 14y agoWithout commenting on the merit of this project, I'm alarmed to see a VC-backed making a Kickstarter pitch.
- deweerdt 14y agocould you expand?
- runako 14y agoSure, Adapteva has raised ~$1.5mm in VC and another ~$850k in debt. Now they are raising $750k on Kickstarter, the "funding platform for creative projects." There's a big disconnect there. If well-funded companies like Adapteva are successful raising on Kickstarter, why wouldn't even bigger companies milk the Kickstarter sheep for R&D funds too? While it wouldn't violate the letter of Kickstarter rules for Intel to run a campaign like this, certainly it's not in the spirit. And yes I get that it's open source blah blah blah, but this project is certainly part of the plan for an institutionally-funded business to make money. Adapteva is a .com, not a .org. Separately: if Adapteva is only 8 months from delivering completed product to users, shouldn't they be able to raise more funds through traditional channels? They clearly have/had VC buy-in and can raise through institutional channels. If they are just finishing the final debugging/SDKs/etc. at this point, it's not a good sign that they can't raise another $750k from their existing backers to cover final launch costs. I don't have a horse in this race, but it doesn't feel quite right to me.
- adapteva 14y agoLet's correct some of your assertions: 1.) Adapteva raised $1.5M from a small board business (not a VC) because it couldn't get a VC investor. 2.) A "well funded" semiconductor is one that takes in $100M like Calxeda. Adapteva has done "more with less" than any chip company in history. 3.) Adapteva is a chip company. The Parallella project is not an "R&D effort" it's about bringing the cost down for an open board product that the developers clearly want and that the industry needs. 4.) Adapteva has talked to >50 large institutional investors. Mostly they are either afraid of going up against Intel, Nvidia or they flat out don't invest in chips. 5.) Kickstarter is not just for non-profits.
- segmond 14y agovapour, it's not going to happen. anyone who wants to crunch massive amount of data or utilize ridiculous amount of cpu cycles can spin up multiple instances in the cloud.
- unix-junkie 14y agoWhat's the point in having such a RAM/core ratio? By assigning 4 threads per core (which is fairly common to exploit manycore architectures) you don't even have 4Meg of memory per thread. I would totally agree that memory constraint is sort of tied to manycore architectures, but in this case I find it pushed to the limits.
- wmf 14y agoThey don't have multithreading.
- wtracy 14y agoSince I thought I saw an Adapteva person posting here earlier: If the Kickstarter falls through, what options could you still make available to hobbyists? Is there some version of your current prototype setup that you could sell, even if it's not one convenient board?
- adapteva 14y agoWe would rather not think of that option:-) if the ks project fails, we'll do our best, but seems unlikely that we could support selling kits to hobbyists and they would certainly cost thousands of dollars each due to a lack of volume.
- vidarh 14y agoIf you don't reach it in time, collect pre-orders. Seriously. Getting an escrow setup in place that in effect gives you a similar payment mechanism as Kickstarter (money handed over to you once the $750k is met; returned if criteria are not met) does not need to be expensive. Even without Escrow I think that if you get close to the target, a substantial number of those of us who've committed on Kickstarter will be ok with taking the risk. And it'd let you set longer/more flexible terms to make reaching it easier.
- perlpimp 14y agois it me or erlang would sort of fit nicely into the core's ideology of data processing? Seems that LD is like set constant. there are external STR commands. You can have data loaded into registers from the code - MOV. Not an expert in Erlang but it seem that two ideologies can beneficial to one another. And if it is so, should expecting Erlang compiler be out of the question? :)
- ricksta 14y agoParallel computing is limited by Amdalah's Law. Having more core does not mean you can have have more speed because it's not easy to use all those cores. Most imperial languages are not designed with running codes on multiple core and few programers are taught how to design their algorithm for using a handful of cores. I can see this platform being a good tool for students and researchers to experiment with algorithm speedups by making their sequential code, parallel. In my parallel programming class, our teacher had to rig together a computer lab to connect the 12 quad core computers to simulate a 64 core cluster. Then again, 64 core cluster of Parallella would cost like $7000. You can get the same 64 core setup by buying 8 x 8 core consumer desktop computer for under $3000, which will still be more cost effective and probably have ten times more computing power because of the x86 architecture. http://en.wikipedia.org/wiki/Amdahls_law http://en.wikipedia.org/wiki/Amdahls_law
- jamieb 14y ago"Pledge $199 or more: 64-CORE: You get everything in the SUPPORTER reward and a 64-core Epiphany-IV based Parallella board"
- AustinGibbons 14y agoIf you like Amdahl's law you may also like... http://en.wikipedia.org/wiki/Gustafsons_law http://en.wikipedia.org/wiki/Gustafsons_law It is a more powerful expression of the benefit of scaling with parallelism. Principally, instead of scaling speed with respect to a fixed data size, you scale the data size with respect to a fixed speed. Having more cores means you (sometimes) can have more data. You still need those parallel programmers with their parallel algorithms though :-)
- IsTom 14y agoAs to parallel algorithms, there's probably not that many of them. https://en.wikipedia.org/wiki/P-complete#Motivation https://en.wikipedia.org/wiki/P-complete#Motivation
- jayhawk 14y agowe got into a big discussion on super computers (the definition), the meaning of what a core is and a whole bunch of other issues... but the low power requirements of this are being completely ignored... as for applications... well portable and/or remote devices/sensors that need parallel computing capabilities and where high energy usage is prohibitive are possible applications. But the greatest asset of this is to spark the next gen of app developers and programmers to fully embrace parallel programming and truly make software scalable...