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Parallella: A Supercomputer For Everyone

kickstarter.com

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Re: Parallella: A Supercomputer For Everyone

#31

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…

OpenCL SDK support is provided. They also have a C/C++ compiler with OpenMP support.

edit: No OpenMP support.

Re: Parallella: A Supercomputer For Everyone

#32

Post by Qworg »

throwaway1979 wrote: post #25

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.…

As 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. =)

Re: Parallella: A Supercomputer For Everyone

#33

Post by DeepDuh »

compilercreator wrote: post #30
DeepDuh wrote: post #27

Earlier quoted context omitted.

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.

Ok, so that's 6.4 cores per mm^2 while Kepler has 4.8. Not bad, considering NVIDIA has already shrunk the scheduling ressources, register blocks and cache sizes per core to a bare minimum (something I don't agree with btw.).

Re: Parallella: A Supercomputer For Everyone

#34

Post by DeepDuh »

compilercreator wrote: post #31
DeepDuh wrote: post #27

Earlier quoted context omitted.

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…

OpenCL SDK support is provided. They also have a C/C++ compiler with OpenMP support. edit: No OpenMP support.

Sounds pretty good, thanks for the heads up. Now I'm curious to see some benchmarks as soon as someone puts 20 or 30 of these on a board with lots of GDDR 3 Ram :).

Re: Parallella: A Supercomputer For Everyone

#35

Post by wmf »

compilercreator wrote: post #30
DeepDuh wrote: post #27

Earlier quoted context omitted.

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.

Some of that GPU die area is used for graphics features that compute programs don't need. But a lot of it is providing performance even though it's not providing FLOPS. GPUs have caches and multithreading for a reason; if you could get better performance with an ultra-simple architecture then ATI/Nvidia would have done that already.

Re: Parallella: A Supercomputer For Everyone

#37

Post by gavanwoolery »

throwaway1979 wrote: post #25

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.…

The 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.
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