parallella is died. So Long, and Thanks for All the Fish

[ed2k]

the lesson I learned is, parallel computing needs fast inter-communication and big cache. many individual computing core can not do much. maybe that is why we need to put smart people in the same room.

[e97]

I backed Parallella on Kickstarter. Super impressed that it shipped and works!

Sad to here that Andreas has moved on but it is understandable. Starting a company is hard. Building and shipping products is hard.

I don't think Parallella is dead. It needs a killer app to showcase its power and usefulness.

As a software guy learning about hardware, the board has all the bells and whistles: ARM SoC, FPGA, and Epiphany-III and there are tutorials out there: doing FFT building a cluster .. but I have yet to see an "HOLY SHIT" moment where I've seen someone do something amazing.

I've since bought a separate FPGA development kit because it has lots of materials and mini projects which help me learn how to build and create for an FPGA. Same with RaspberryPi and why its such a big success - lots of show and tell, community and documentation.

If someone showed me Tensorflow or some AI library running on Parallella at a better Compute / Power than GPUs or something - it would be an overnight success.

I will continue to tinker with it and learn and I'm currently deciding whether to keep or sell my Kickstarter edition A101040, if anyone is interested shoot me a PM.

edit: Right now the killer app is *coin mining .. if you could create something that was plug and play and you could efficiently mine *coin (BTC, Litecoin, Etherum) that would be the HOLY SHIT moment as of right now (2017-07-25)

[DonQuichotte]

Hi

(I don't enjoy electronic *coins: not ecology-aware.
Just for studying, why not.)

You have a riecoin solver in the Parallella examples.
It may inspire you.
Good luck

[KNERDY]

[dobkeratops]

[DonQuichotte]

False with a class of backtrackers too.
As long as a backtracker algorithm can be split into millions of independant subproblems with small memory footprint,
the Parallella is the best choice for the energy/performance ratio.
Epiphany V would have been tremendous :'(

(I never tried to learn about neural nets, but I was shocked recently when hearing about the Google AlphaGo that has beaten the human world champion.
About Go the computers just a few years ago were unable to beat a modest human amateur...
and now this IA crushing everything else AND being creative like a human genius mind is sometimes, this is just amazing.)

For neural nets there is a new actor with incredible performances: Fathom Movidius stick. 80 to 150 Gflops... for 1 W it seems hard to believe.
I wonder how it deals the IF/ELSE and if it can do anything else than video processing ; and probably this theoretic peak performance is only with an exotic instruction sequence. Anyway, appealing.

[dobkeratops]

[frankbuss]