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Parallella: A Supercomputer For Everyone

kickstarter.com

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Re: Parallella: A Supercomputer For Everyone

#21

Post by stonemetal »

mbenjaminsmith wrote: post #7

I 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/ 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 cuttin…

http://en.wikipedia.org/wiki/TILE64

Tilera did a very similar looking 64 cores on a chip in 2007, which is the oldest instance I know of off the top of my head. Their devices cost(or at least they used to) a few grand though. Tilera has bumped it up to around 100 per chip these days. I don't know anything about either architecture so it is hard to say if 64 1Ghz adapteva cores compares with 64 1.5Ghz Tilera cores.

So not quite cutting edge just an under explored side channel.

Re: Parallella: A Supercomputer For Everyone

#23

Post by stonemetal »

Swizec wrote: post #9
mbenjaminsmith wrote: post #7

I 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/ 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 cuttin…

Don't modern GPU's have essentially thousands of cores?

It really depends on what you consider a core.

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.

Re: Parallella: A Supercomputer For Everyone

#24

Post by scott_s »

jacques_chester wrote: post #19

I 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.

I 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.

Re: Parallella: A Supercomputer For Everyone

#25

Post by throwaway1979 »

I 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.

Re: Parallella: A Supercomputer For Everyone

#27

Post by DeepDuh »

mbenjaminsmith wrote: post #7

I 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/ 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 cuttin…

Well, NVIDIAs Kepler GPUs have 1536 cores on something like 320mm^2. I can't really find the die size of that adapteva product but I'd say it comes out at a similar range.

Having looked at the data a bit more: I like their specs concerning system balance. 100 GFLOPS over 6.4GB/s gives you a system balance of 15.625 FLOPS per memory access, that's about the same balance as a Westmere Xeon - pretty good for real world algorithms.

For comparison: NVIDIA Fermi has a system balance of about 20. Meaning: Fermi is sooner bounded by memory bandwidth, which is very often the limiting factor in real world computations.

One thing though: High Performance Computing is all about software / tooling support. If this company comes out with OpenCL in C (even better Fortran 90+) support, then we're talking.

Edit: By similar 'range' I meant core per mm^2 ratio.

Re: Parallella: A Supercomputer For Everyone

#28

Post by DeepDuh »

stonemetal wrote: post #23
Swizec wrote: post #9

Earlier quoted context omitted.

Don't modern GPU's have essentially thousands of cores?

It really depends on what you consider a core. 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.

I 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 ;) ).

Re: Parallella: A Supercomputer For Everyone

#29

Post by imrehg »

bdfh42 wrote: post #3

This 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.

Also 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.

Re: Parallella: A Supercomputer For Everyone

#30

Post by compilercreator »

DeepDuh wrote: post #27
mbenjaminsmith wrote: post #7

I 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/ 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 cuttin…

Well, NVIDIAs Kepler GPUs have 1536 cores on something like 320mm^2. I can't really find the die size of that adapteva product but I'd say it comes out at a similar range. Having looked at the data a bit more: I like their specs concerning system balance. 100 GFLOPS over 6.4GB/s gives you a system balance of 15.625 FLOPS per memory access, that's about the same balance as a Westmere Xeon - pretty good for real world…

Prepare to be surprised. The die size estimate for the Epiphany IV is 10mm-sq according to Adapteva. It is more appropriate to compare it to embedded GPUs than desktop GPUs in die size, power and performance.

For example, one particular embedded 40nm GPU design that I know about can deliver about 25 GFlops or so in the same die area.

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