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Parallella, a $99 Linux Supercomputer

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81–90 of 171 posts

Re: Parallella, a $99 Linux Supercomputer

#81
post #50

I'm really disappointed about how shallow the discussions about Adapteva are, and have been, on HN. To remind everyone, the H = hacker. This device is a godsend, as far as I'm concerned. For the first time ever I get fully documented access to compute array on chip. No the architecture wasn't designed for anything specific, like graphics, but that means I don't get bogged down in details I don't care about, like some…

  Stop asking what existing things you can do with it,
Ask away, I'll keep linking http://en.wikipedia.org/wiki/Embarrassingly_parallel

Re: Parallella, a $99 Linux Supercomputer

#82
post #68

Earlier quoted context omitted.

ask what future things having something like this on a SoC would enable. I asked that and came up blank. And I haven't seen answers from anyone else, either. Has Adapteva themselves shown any examples where their chip beats a GPU?

In the comment thread on the article someone points out that the Adapteva chip doesn't do double precision floating-point, which limits its usefulness (to put it mildly). If the goal is to provide people with a low-cost platform to experiment with parallel programming, surely a decent NVidia card gives you less expensive (given you can plug it into a PCI slot and it will work) access to more CPUs that run faster and…

Well, you can still do double-floats, combining two 32-bit floats for a greater precision. While that doesn't get you full double precision, it just might be enough. And of course you can extend the same idea to implement quad-floats and so on.

http://andrewthall.org/papers/df64_qf128.pdf

Re: Parallella, a $99 Linux Supercomputer

#83
post #48
post #18

Can anyone explain what the practical differences between something like this and a gpgpu approach? It doesn't sound particularly performant compared to modern gpus otherwise. Maybe they add in some more general purpose instructions for a little more flexibility?

A typical GPU can execute a small number of threads on a large number of streams of data carefully laid out in memory. Every time you want to do something conditionally on just one data stream, you waste a lot of capacity. In contrast, the Epiphany chips can execute individual threads on each core in parallel on data either local to the core (fastest), on any other core, or in separate main memory. The current Epipha…

Awesome explanation, thanks. I love that you can learn about things outside your field here without it being super dumbed down or having to google half a dozen domain specific terms.

Re: Parallella, a $99 Linux Supercomputer

#85

This is really cool. Since it's linux I assume it can run the JVM, correct? That's incredibly powerful, as even GPU programming requires bridge libraries. And what, $99? That's incredible. I'm going to get one...

IIRC Linux does not run on Adapteva. Linux runs on the ARM which is next to the Adapteva chip.

Re: Parallella, a $99 Linux Supercomputer

#87
post #62
post #50

I'm really disappointed about how shallow the discussions about Adapteva are, and have been, on HN. To remind everyone, the H = hacker. This device is a godsend, as far as I'm concerned. For the first time ever I get fully documented access to compute array on chip. No the architecture wasn't designed for anything specific, like graphics, but that means I don't get bogged down in details I don't care about, like some…

Good reminder! Do you see applications in an embedded sense, or are you looking at it to augment a regular computer's capability?

I'm actually thinking Adapteva has a lot of future in present areas of growth.

1) On the mobile side, you can have Epiphany, their compute fabric, as a unit directly on the mobile SoC. You can do codec offload, like WebP, WebM, SILK/Opus. You can do basic computer vision for augmented reality applications, or image recognition. Or perhaps physics, integrate gyro output, position the device in absolute three space. I dunno, the point is the compute is open, there for exploitation. It's not like OpenCL where I have to beg the drivers to be available, correct, or performant. Nor is it like Qualcomm's Hexagon, where who knows if I can use it, and I sure as hell won't without signing an NDA.

2) As far as cloud and heterogenous compute goes, again I see an embedded Epiphany being useful. Everybody whines about various things, like for example missing double-precision. Firstly, it's not like the architecture can't be extended in future. But more importantly they miss little details. Each node in Epiphany can branch and do integer. You can see it doing wire-speed protobuff de/coding and other parallel data shuffling of long-living data, that could be compressed, or interleaved somehow.

I'm more of a low-power, cloud kind of guy. So that's what I'll be playing with the most when I get my hands on the kit. That and maybe some parallel graph rewriting. Who knows, the sky's the limit.

Re: Parallella, a $99 Linux Supercomputer

#88
post #68
post #50

I'm really disappointed about how shallow the discussions about Adapteva are, and have been, on HN. To remind everyone, the H = hacker. This device is a godsend, as far as I'm concerned. For the first time ever I get fully documented access to compute array on chip. No the architecture wasn't designed for anything specific, like graphics, but that means I don't get bogged down in details I don't care about, like some…

ask what future things having something like this on a SoC would enable. I asked that and came up blank. And I haven't seen answers from anyone else, either. Has Adapteva themselves shown any examples where their chip beats a GPU?

I can think of two: documentation and simplicity. Comparing Parallella with GPUs only in performance is missing the point. The board is open and quite understandable for non-experts like me. It's a platform for learning and experimenting, like a Raspberry Pi but more geeky. You will probably have an easier time tinkering with this and getting it to do useful things, that's the point. I feel, like the parent commenter, quite excited about this.

Re: Parallella, a $99 Linux Supercomputer

#89
post #50

I'm really disappointed about how shallow the discussions about Adapteva are, and have been, on HN. To remind everyone, the H = hacker. This device is a godsend, as far as I'm concerned. For the first time ever I get fully documented access to compute array on chip. No the architecture wasn't designed for anything specific, like graphics, but that means I don't get bogged down in details I don't care about, like some…

Exactly. I'm very excited to get my board and break into it. It really is intended to be a testbed for multiprocessing and hacking.

One thing that I'd like to see is what other people do with this product. I think that really will be the best part of this board. I'd equate it to minecraft (if I may be so bold). They didn't create a computer in minecraft, they created the possibility to create a computer and that was enough. That's how I see this board.

Re: Parallella, a $99 Linux Supercomputer

#90
post #68

Earlier quoted context omitted.

ask what future things having something like this on a SoC would enable. I asked that and came up blank. And I haven't seen answers from anyone else, either. Has Adapteva themselves shown any examples where their chip beats a GPU?

In the comment thread on the article someone points out that the Adapteva chip doesn't do double precision floating-point, which limits its usefulness (to put it mildly). If the goal is to provide people with a low-cost platform to experiment with parallel programming, surely a decent NVidia card gives you less expensive (given you can plug it into a PCI slot and it will work) access to more CPUs that run faster and…

It took a long time for GPU's to get double precision floating point and plenty of GPGPU work was done with them prior to that, so it's not a deal breaker

Not sure if world first or AMD's first, but it was around this timeframe, 2007: "AMD Delivers First Stream Processor with Double Precision Floating Point Technology" http://phys.org/news113757140.html

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